Regional differences in the cost of health care are due to differences in both the price and volume of medical care.  Since, Medicare sets prices, there should be little variation in prices…right?

Actually, Medicare payments have geographic adjustments based on a number of factors.  For instances, the hospital wage index gives pay hospitals more in areas with higher labor costs.  Similarly, Medicare pays physicians more in high cost areas through the geographic practice cost index (GPCI).

In order to compare differences in volume across regions, one must also make the following adjustments

• additional payments to hospitals above the standard rates in the inpatient prospective payment system including graduate medical education, indirect medical education, and disproportionate share payments.
• additional payments to physicians above the standard rates in the physician fee schedule in provider scarcity areas and health provider shortage areas.
• additional payments to rural hospitals above standard rates in the inpatient prospective payment system, including special payments for sole community hospitals, small rural Medicare-dependent hospitals, and critical access hospitals.
• beneficiaries’ health status, as measured by the MSA’s average risk score from the CMS–hierarchical condition category (HCC) risk adjustment model.
• the rate of beneficiaries’ enrollment in Part A and Part B of the Medicare program—in some areas, the percentage of beneficiaries with only Part A or Part B coverage differs significantly from the national average.

After taking these factors into account, a recent MedPAC report finds that although raw per capita spending is 55% higher for beneficiaries in the area at the 90th percentile than for beneficiaries in the area at the 10th percentile, medical utilization use in higher use areas (90th percentile) is only about 30% greater than in lower use areas (10th percentile).  Approximately, 45% of the FFS population lives in areas that have service use within 5 percent of the national average.

The metro area with the highest service use was Miami.  In fact, Miami’s medical service use was twice the level of the services provided in the metro area with the lowest utilization levels (non-metropolitan Hawaii).  One reason for this difference is that “per capita spending on durable medical equipment and home health care in Miami–Dade County were both more than seven times the national average and dramatically above spending in neighboring counties.”

• Source: MedPAC (2009) “Measuring Regional Variation in Service Use: Report to Congress,” December 2009.
• Hat Tip:  Gooz News.

Accountable Care Organizations (ACOs) are the latest rage in the health policy world.  The question is, what are ACOs.  The Urban Institute’s Kelly Devers and Robert Berenson try to answer the following question: “Can Accountable Care Organizations Improve the Value of Health Care by Solving the Cost and Quality Quandaries?”

The goal of ACOs is to pay providers in a way that encourages them to work together, to pay providers in a way that does not encourage supplier induced demand, and to create an organization that is rewarded for providing high quality care.  What kind of organizations are currently poised to evolve into ACOs. This chart evaluates the prospects.

One question is why doesn’t Medicare just use their current Medicare Advantage program to accomplish these goals.  In the Medicare  Advantage program, Medicare pays a lump sum to private insurers and holds them accountable for all the medical care the beneficiary needs.  However, there are three main differences between ACOs and HMOs.

1. The “accountability” rests with the providers.  Providers or provider groups, rather than insurance companies, are evaluated on the quality and efficiency of care.
2. Direct contracting with provider organizations without the reliance on a health plan intermediary.
3. The ACOs allow for flexibility in the type of organization.  Some regions may prefer independent practice associations (IPAs) while others  may prefer a physician-hospital organization (PHO).

The physician-centered organization makes much sense to many policymakers because “the resources that flow from the decisions physicians make with patients account for a major portion of overall health care costs, regardless of where the care actually takes place.”

Medicare could pay ACOs with a “gainsharing” mechanism.  In the gainsharing framework, the fee-for-service payment structure remains, but a portion of patient cost savings gets passed through to the physician. On the other hand, Medicare could institute a partial capitation scheme.  This would be similar to Medicare Part D, where the prescription drug plans get a flat rate per person, but they also receive are involved in risk corridors, which “limit a prescription drug plan’s potential losses should the plan happen to experience much higher utilization and costs than expected.”

One problem with this framework is that physicians are good at treating patients, not at risk management.  Thus, many physicians may get stuck with high-risk patients and some ACOs may become insolvent unless there are adequate Medicare risk adjustment payments.

Secondly, patients may see ACOs as HMOs in disguise.  ”[I]f beneficiaries believe that ACOs are essentially tightly managed ‘HMOs in drag’ that are going to restrict their choices, undermine the doctor-patient relationship, and result in cheaper but lower-quality care, the concept will be met with skepticism, if not overt opposition.”

Other obstacles to ACOs include possible FTC and DOJ desires to quash ACOs on anti-trust grounds.  Further, state governments may need to change laws related to insurance regulation as well as organizational and professional liability.

• Devers K, Berenson R (2009) “Can Accountable Care Organizations Improve the Value of Health Care by Solving the Cost and Quality Quandaries?” Timely Analysis of Immediate Health Policy Issues, Urban Institute, October 2009.

Most workers have employer-provided health insurance. The old have Medicare and the poor Medicaid. Children have SCHIP and veterans have the VA. But what about the people who fall through the cracks? What about individuals who work for small businesses who don’t offer insurance, entrepreneurs, or illegal immigrants? Where can they get health care? An article in San Francisco Magazine discusses how the Bay Area provides health care for the uninsured.

Healthy San Francisco (HSF) is the city’s two-year-old health-access plan that provides healthcare access most uninsured resident aged 18 to 64, regardless of employment, citizenship, or preexisting conditions. In a city of 800,000 people, about some 63,000 people (~8%) use HSF. Journalist Justine Sharrock notes that “Healthy San Francisco isn’t insurance—it’s a system of providers that uses the city’s superb healthcare infrastructure: neighborhood clinics, community hospitals, public health centers, and the state-of-the-art resources of UCSF. It doesn’t replace other government programs, like Medicare or Medi-Cal; it just ensures that people who don’t qualify for them don’t fall through the cracks. To enroll, all you do is show proof of residency and income: The cap is now $54,150, though officials hope to open HSF to all income levels by the end of 2010. Other than a requirement that new participants be uninsured for three months prior to joining the program, there isn’t even a waiting period.”

HSF is, hands down, one of the best healthcare bargains anywhere. For individuals earning less than $10,830 annually, the program is free. For everyone else, basic enrollment is $20 to $150 per month (versus $409 for the average California insurance premium), with rock-bottom copayments: $10 for primary care visits, $200 for hospital admissions, and $5 to $25 for medications.

The main advantage of HSF is that sick people can get affordable health care. The article describes a woman named Sharon Donnelly who has hydrocephalus (i.e., a condition in which fluid develops in her brain) and found it “nearly impossible” to purchase nongroup coverage. Because she could enroll in HSF, she quit her library assistant job and gave up her private coverage. She is extremely satisfied with the care. In fact, the Kaiser Family Foundation found that 94 percent of users expressed satisfaction with HSF. Further, the program is inexpensive for users. “For those earning less $10,830 annually, the program is free. For individuals earning less than $10,830 annually, the program is free. For everyone else, basic enrollment is $20 to $150 per month (versus $409 for the average California insurance premium), with rock-bottom copayments: $10 for primary care visits, $200 for hospital admissions, and $5 to $25 for medications. Additionally, having HSF may attract more young, innovative people to San Francisco. These entrepreneurial people can work in small internet start-ups without worrying about how to get by without health insurance.

The main disadvantage of the plan is that it raises taxes and does not replace a comprehensive insurance plan. Let us return to the case of Sharon Donnelly. The availability of HSF allowed her to quit her job and employer the accompanying employer group plan in order to look for better employment. However, San Francisco taxpayers must subsidize such an expensive patient. In fact, the high cost individuals without access to employer-provided plans are the ones most likely to take up HSF. Small businesses cost are higher in San Francisco, partly because of a pay-or-play mandate which compels businesses to offer health insurance to their employees. “Businesses with 20 or more employees must contribute $1.31 to $1.96 per worker per hour toward some form of healthcare: either private insurance, a flexible spending account that sets aside money for health¬care needs, or the city option, including HSF.” However, the pay-or-play employer contributions to HSF make up only 11% of the program’s cost. No wonder San Francisco’s sales tax is 9.75%.

Additionally, the program only covers you when you’re in the city. If you’re injured outside of San Francisco—even in another Bay Area city such as Oakland or Palo Alto—then you must pay for care out of pocket. The HSF website even warns: “Healthy San Francisco is not insurance. If you have insurance, do not drop it. Insurance is always a better choice.”

Further, treatment can be slow. As part of being in the HSF, the author had to pick up her medications at San Francisco General’s pharmacy which she claims has “confusing or non-existent procedures” and took an hour to get her prescription filled. Although the Ms. Sharrock finds “the sense of camaraderie with the other people in line oddly comforting,” most people more likely believe that this is a serious inconvenience, especially for those with more rigid work schedules.

Finally, the creation of HSF will induce Tiebout sorting. If you am someone who earns $40,000 per year working for a small business in the city who does not offer insurance, living in San Francisco is a great way to get health insurance. However, if you make $200,000 working in the city with an employer-sponsored plan, you may choose to move to a nearby San Mateo county and commute to work. If this occurs, San Francisco will lose out on tax revenue from many of the high wage workers.

Overall, it is clear that individuals who participate in the HSF plan receive significant benefits. Because HSF is not self financing, those who do not participate in the plan will have to subsidize these costs. The effect of migration into/out of San Francisco is ambiguous: having HSF will attract workers but the higher taxes needed to pay for HSF will drive some people away as well. HSF is similar to the current health care reform proposals in that it will expand coverage, but does little to control costs or significantly change the healthcare system.

How does one evaluate a physician’s efficiency level?  This process has five main dimensions.

• Which resource use measurement methodology to use. There are two main profiling methodologies: per capita and episode-based.
• How to account for differences in patient health status. This is done through risk adjustment.  However, choosing the proper risk adjustment method is crucial in order to produce accurate physician scores.
• How to attribute resource use to physicians. Important attribution decisions include whether to assign a patient’s resource use: i) to the single physician who bears the greatest responsibility for the resource use, ii) to all physicians who bore any responsibility, or iii)  to all physicians who met a given threshold of responsibility.
• What benchmark(s) to use. Should the benchmarks be evidence-based, set relative to peers, or established by consensus through organizations such as the National Quality Forum.
• How to determine what is a sufficient sample size to ensure meaningful comparisons. This sample size can vary on two dimensions: i) the availability of enough data on each physician to compute a resource use measure and ii) a sufficient number of physicians to provide meaningful comparisons.

The GAO has a report analyzing whether physician resource utilization per-capita is stable over time.  The report looks at 4 specialties [cardiology, diagnostic radiology, internal medicine, and orthopedic surgery] in 4 metro areas [Miami, Phoenix, Pittsburgh, and Sacramento].  The data used include: (1) Medicare claims files; (2) Denominator File, a database that contains enrollment and entitlement status information for all Medicare beneficiaries in a given year; (3) Hierarchical Condition Category (HCC) files that summarize Medicare beneficiaries’ diagnoses; (4) files summarizing the institutional status of beneficiaries; and (5) Unique Physician Identification Number Directory, which contains information on physicians’ specialties.

Below are the specifications the GAO report uses to create physician scores.

• Physician resource utilization is constructed on a per-capita basis.
• Risk adjustment is constructed using Hierarchical Condition Categories (HCCs).  The risk adjustment model uses the same 70 HCCs as the model CMS uses to set managed care capitation rates.
• Attribution is given to the physician with the highest Evaluation and Management (E&M) cost for each beneficiary [except for diagnostic radiology where the physician with the most Part B costs was attributed the individual’s annual cost].  However, very little of each individual’s annual cost was accounted for by the attributed physician.  Institutional services accounted for 54 percent of expenditures. On the other hand, “services provided by a particular physician in our study directly to that physician’s patients accounted for only 2 percent of total expenditures or about $350 for each beneficiary in a physician’s practice.  All other services—those provided by other physicians, home health care, hospice care, outpatient services, and durable medical equipment—accounted for the remaining 44 percent of expenditures.”
• The benchmarks used was cost relative to one’s peers.  The report acknowledges that quality metrics should also be incorporated in the evaluation.  However, since there are few established quality metrics for most specialties, the potential for quality evaluation at this point is limited.
• For the sample size, the GAO required physicians to have treated at least 100 Medicare patients each year in the study.  The meant that 28% of physicians were excluded from the sample in 2005 and 29% were excluded in 2006.

The report finds that “58 percent of physicians and 30 percent of beneficiaries were in the same quintile of resource use in 2005 and 2006. The pattern was even more pronounced for the top resource use quintile: 72 percent of physicians and 35 percent of beneficiaries remained in that quintile. If the level of physicians’ and beneficiaries’ resource use was purely random, only 20 percent would be expected to have remained in the same quintile.”

One important aspect of physician evaluation is whether or not these scores will actually change physician behavior.  The authors review of the literature finds that “feedback alone generally has no more than a moderate influence on physician behavior.”  It is possible, however, because most insurers have a small share of the physician’s business.  Feedback from Medicare, however, may lead to a more significant behavior changes because it is so large.

Also, it likely that disaggregated scores (by patient or by episode type) will have a larger effect on physician behavior than a single overall cost.  The more detail the physician can receive, the more he can learn how to alter his behavior.  In fact, the top five insurers actually provide patient-level detail in addition to the overall physician grade.

• General Accounting Office (2009) “Per Capita Method Can Be Used to Profile Physicians and Provide Feedback on Resource Use,” Report to the Chairman, Subcommittee on Health, Committee on Ways and Means, House of Representatives, GAO-09-802.

How is the health care labor market in your area?  HWS Enterprises put together a gauge of the healthcare workforce labor demand throughout 30 large metropolitan regions in the United States.  The results for Q4 are available here.  The strongest healthcare labor markets are Sacramento, Riverside, Pittsburgh, Cleveland and Dallas.  The weakest is New York City.  My home, San Francisco, ranked 18th out the 30 large metro areas evaluated.

According to the Health Workforce Solutions’ press release:

The HWS Labor Market Pulse® Index (LMPI) provides a quarterly barometer of local market health care workforce expansion and contraction. Patterned loosely after the Case-Shiller home index and based on a proprietary algorithm, the LMPI identifies and enables comparison of 30 health care labor markets by tracking elements including temporary health workforce shortages and surpluses, facility and bed closures, announced layoffs and expansions, and local economic trends. The LMPI will be published quarterly as part of Labor Market Pulse® and distributed nationally to health care executives, the media and other interested parties.

Mortality during surgery is dependent on two factors.  The first is the probability of having complications during surgery.  The second is the probability of dying conditional on having a complication.  One would expect that hospitals with low mortality rates would have both fewer complications and lower probability of death conditional on a complication.  

A paper by Gheferi, Birkmeyer, and Dimick (NEJM 2009) shows that this may not be the case.  After risk adjustment complication rates were not significantly higher in high mortality hospitals.  However, conditional on there being a complication, mortality rates were much higher in high mortality hospitals than low mortality hospitals.  

How can doctors decrease mortality due to complications?  Gheferi, Birkmeyer, and Dimick recommend “timely administration of antibiotics in patients with sepsis, the rapid transfer of a patient to an intensive care unit (ICU), and the availability of interventional cardiologists during an acute myocardial infarction.”

• Gheferi, Birkmeyer, and Dimick (2009) “Variation in Hospital Mortality Associated with Inpatient Surgery” NEJM, 361(14):1368-1375.

Much of my own research has focused on how physician financial incentives affect the quantity and quality of medical care. It should come as no surprise that I found a recent New York Times article on the topic stimulating.  Dr. Sandjeep Jauhar examines how hospital and physician financial incentives affect the length of a patient’s hospital stay.  An excerpt is below.

My hospital, like all acute-care facilities, receives a set payment per admission based on the patient’s diagnosis. So the longer a patient stays in the hospital, the more money the hospital stands to lose. Of course, the longer a patient stays, the greater the likelihood of hospital-acquired infections or harm from tests and procedures, which means timely discharge in most cases is good for hospitals and patients alike.

But doctors, paid separately by Medicare, have little motivation to discharge patients quickly. As long as their patients are in the hospital, they can bill and be paid for each visit they make.

I discussed this issue with an internist in private practice, who requested anonymity because of the sensitive nature of the subject. His patients, it seemed to me, were often staying longer in my hospital than necessary. “I understand why hospitals want to cut down length-of-stay,” he told me matter-of-factly. “But if I discharge a patient early, I don’t get paid. It’s O.K. if you have enough patients in the hospital, but if you don’t, you sometimes have to drag out the stay. I don’t like to do it, but sometimes you have to.”

In 1998, Medicare enacted the sustainable growth rate (SGR) which would slowly bring down Medicare physician compensation.  However, each year, it gets reversed by Congress. Now, instead of a gradual decline, the implementation of SGR would  result in a 21.2% pay cut for Medicare docs.

Before the Thanksgiving holiday, however, Congress once again reversed the SGR.  Megan McArdle gives some solid reasons of why the reform of the SGR should be included in any health reform bill.

A paper by Thomas, Grazier, and Ward (2004) analyzes a variety of risk adjustment software products. Using these six risk adjustment products to calculate physician efficiency scores, they found “moderate to high levels of agreement were observed among the six risk-adjusted measures of practice efficiency.” However:

“And even though our analyses suggest that 50 percent to 60 percent of adult PCPs identified by their system as being high outliers are likely to be identified by other profiling systems as well, the client has no way to know which of the identified outliers are the ones that multiple systems would agree on. Thus the profiling client must deal with practice efficiency rankings knowing that, in all likelihood, 40 percent to 50 percent of PCPs identified as high outliers are actually not among the least efficient 10 percent of primary care physicians.”

The authors also compare two quality score metrics. The first is the ratio of the physician’s observed cost with the expected cost based on the physician’s patient’s risk scores. The O/E score is equal to:

• (O/E)_k=y_k/Y_k

Above, y_k is physician k’s observed score and Y_k is their estimated score. The authors believe, however that the O/E score is not ideal. It is biased against providers who have a small sample size of patients. Thus, physician’s with smaller patient panels in the data set are more likely to be considered outliers. On the other hand, the authors advocate using a standardized cost difference (SCD). The SCD is calculated as follows:

• SCD_k=(y_k-Y_k)/[σ/(N_k)^1/2]

The SCD measure explicitly takes into account the physician’s sample size. A large sample size will move the SCD more towards the difference in observed and expected costs; a small sample size will move the SCD score closer to the mean of 0.

Below is a list of the six risk adjustment tools used in the paper:

• Adjusted Clinical Groups from Johns Hopkins University. Adjusted clinical groups cluster health plan members having similar comorbidities into groups that have similar resource requirements and clinical characteristics. The ACG Case-Mix System then uses a branching algorithm to place each patient into one of 82 discrete, mutually exclusive categories based on the mix of clinical groups experienced during the time period under study.
• Burden of Illness Score from MEDecision, Inc. This system is based on MEDecision’s Practice Review System (PRS), which partitions care into episodes of illness and assigns services, severity levels, and medications to these episodes. The BOI Score is a linear-scaled measure that indicates relative health care cost risks associated with the particular mix of episodes experienced by a patient during a defined time period.
• Clinical Complexity Index from Solucient, Inc. The CCI methodology considers age, severity, comorbidity, hospital admissions, and categories of diagnoses (acute, chronic, mental health, and pregnancy) to assign patients into mutually exclusive CCI risk categories. Although the system provides for 1,418 different categories, 95 percent of patients fall into just 45 of these.
• Diagnostic Cost Groups from DxCG, Inc. The DCGsystem includes a whole family of multiple linear regression models.
• Episode Risk Groups from Symmetry Health Systems,Inc. Like BOI Score, ERGs are episode-based. The episodes underlying ERGs are created using Symmetry’s Episode Treatment Groups (ETGt) methodology, a basic illness classification system that uses a series of clinical and statistical algorithms to combine related services into more than 600 mutually exclusive and exhaustive categories. For a given patient, episodes experienced during a time period are mapped into 119 Episode Risk Groups, and then a risk score is determined based on age, gender, and mix of ERGs. For our analyses, we used the ERG retrospective risk score.
• General Diagnostic Groups from Allegiance LLC. General Diagnostic Groups were developed using the Agency for Health Care Policy and Research’s Clinical Classification Software (CCS). CCS aggregates individual ICD-9-CM codes identified on health care claims into 260 broad diagnosis categories for statistical analysis and reporting. The GDG system then lumps together CCS categories considered to be clinically similar and to have similar associated per-patient charges into 57 diagnostic categories. These 57 diagnostic categories are used as dummy variables in a multiple regression model for predicting health care costs.

Source:

• J. William Thomas, Kyle L. Grazier, and Kathleen Ward (2004) “Comparing Accuracy of Risk-Adjustment Methodologies Used in Economic Profiling of Physicians” HSR, 39(4):985-1004.

Efficiency in the field of economics increases when either 1) outputs are increased for a given level of inputs, or 2) inputs are decreased for a given level of output. Estimating efficiency in the medical field is more difficult, however, since the output (marginal health improvement) is difficult to measure. In the area of hospitals, some researchers have estimated the cost per hospital stay, or cost per patient-day as an estimate of efficiency. Newhouse (1994) offers a striking analogy of why this would not be a good measure of efficiency.

“Consider the following analogy. Among the amenities of first-class air travel are wider seats, better food, and a higher ratio of flight attendants to passengers than in the coach section. These amenities are obviously valued because some passengers pay an incremental amount for them. An analog to patient-days or stays in air travel is passenger-miles or the number of passengers; without additional adjustment, however, such output measures would make the additional costs associated with the first class section appear as inefficiency, not as something consumers valued.”

There are other difficulties in measuring hospital efficiency. For instance,

1. Many hospital inputs are typically omitted. For instance, capital inputs and the labor costs from physicians with admitting privileges are frequently omitted.
2. Case mix controls are not perfect and often hide significant variation in patient illness severity within each diagnostic cost group (DRG).
3. When using frontier analysis to measure efficiency, strong assumptions are needed. Data Envelopment Analysis (DEA) assumes no measurement error. ["Random measurement error that is inframarginal (off the frontier) will not affect the location of the frontier, though it will affect how inefficient any given firm appears to be, but sufficiently large error in a given direction will move the frontier itself, thereby increasing the measured inefficiency among firms lying near that segment of the frontier."]  Stochastic frontier estimation allows for measurement error, but makes specific assumptions on the error distribution.
4. There are many outputs to estimate.  Estimating aggregate efficiency for each hospital does not provide sufficient detail.  However, creating an efficiency measure for each disease type or patient types creates a more difficult estimation problem.  Further, there is no obviously superior manner in which to aggreate these disease specific scores into a single, hospital-wide efficiency score.

Newhouse J (1994) “Frontier Estimation: How useful a tool for health economics?” Journal of Health Economics, v13(3): 317-322.

This American Life has a two-part series on America’s healthcare system.  Below are some highlights from the first part: More is Less.

On supplier-induced demand

  My old partner that I joined here in 1971 was asked by a friend of his 

“…at what level of vision do you do a cataract operation?” 

And he said

  ”Well, if there’s one ophthalmologist in town, then its 20/200.  If there are two ophthalmologists in town then its 20/80.  If there’s three ophthalmologists in town, then it’s 20/40.”

• Dr. Frank Reed

On why doctor agree to do unnecessary tests:

Then, I said to him something that I had long known, but had never crystalized for me exactly in this way in that moment.  I said to him, “You know, for me, it really is the right thing for me to do the CAT scan.  If I don’t do the CAT scan, you’ll probably lodge a complaint about me.  If I do the CAT scan you’re be really happy with me.  In addition, I’m almost certain that you daughter is fine, but there’s a maybe a 1 in million chance that she isn’t; that maybe there is a hidden fracture and I’m missing it.  And if that’s the case, the CAT scan will save my butt.  On the other hand, if I do the CAT scan and your daughter gets cancer twenty years from now, no one will blame me.  In addition, I’m spending a lot of time talk to you that I would be doing other things.  If I got the CAT scan, I could do it in a second and it would be done with, it would be easy.  And finally, the really strange thing is, I’ll get paid more if I do the CAT scan…So everything about this was pushing me to do the CAT scan.”

• Dr. Jerome Hoffman.  In this case, Dr. Hoffman convinced the patient’s family not to do the CAT scan.  

On the need to control costs.

And now you always hear “No one should stand between you and your doctor.”  You know what that means, that means no one should ever control utilization, even if its unnecessary, if your doctor thinks its necessary.  No one should every say no.  Almost anyone who’s looked at the data says, “Oh yes, you should.”  

• Uwe Reinhardt, health economist

The NEJM recently reported on physician views about the public option and the possible expansion of Medicare.  It turns out, most physicians favor the status quo of a mix of public and private financing.  

Why would doctors support a public plan? It could be ideological. They may simply believe that more government health insurance would make society more equitable. Or they may believe that they can receive more money from government reimbursement than hard-bargaining private companies. Or it could be that dealing billing rules from multiple private insurance companies is much worse than dealing with billing issues from Medicare.

The Congressional Budget Office (CBO) periodically releases its 75-year health care spending projections. Current projections forecast the following health care spending levels:

• Total spending on health care would rise from 16% of GDP in 2007 to 25% in 2025, 37% in 2050 and 49% in 2082.
• Federal spending on Medicare (net of beneficiaries premiums) and Medicaid would rise from 4% of GDP in 2007 to 7% in 2025, 12% in 2050 and 19% in 2082.

U.S. Health Care System Overview

The distribution of health care spending between public and private sources can in this chart. Currently health insurance although public health insurance is gaining ground, employer-provided health insurance still covers most Americans. Overall, healthcare spending has increased from 4.7% of GDP in 1960 to about 16% of GDP now. According to the CBO (as well as most other researchers) the major driver of this long term cost growth “has been the emergence, adoption, and widespread diffusion of new medical technologies and services.”

CBO Projection Methodology

The simplest way the CBO projects health expenditures is to use excess cost growth models. Excess cost growth measures increases in health care spending above the level of GDP growth. For instance, between 1975 to 2009 excess cost growth was 1.9 percentage points. Medicare excess cost growth was 2.3%, Medicaid excess cost growth was 1.9% and all other insurance (e.g., private health insurance, other public programs) had excess cost growth of 1.8%.

In reality, the forecasting method is much more detailed.

• Medicare and Medicaid Projections. The CBO projects total spending for Medicare and Medicaid less the contributions from states and enrollee premium contributions. Premiums are assumed to be a flat percentage of part B and Part D premiums. State contributions for Medicaid are held constant at 57% of total projections after the expiration of the temporary increase enacted in the American Recovery and Reinvestment Act of 2009.
• Budget Scenarios. The CBO uses two budget scenarios. The extended-baseline scenario assumes current laws do not change and that physician payment formulas will continue to apply and will necessitate large reductions in these payments over the next several years. The alternative fiscal scenario assumes that Medicare physician payment will increase with inflation. Spending on the alternative fiscal scenario is greater because the physician reimbursement rates are assumed not to be cut.
• Long term projection Details.
  • CBO projections from 2009-2019 used the projections from the CBO March 2009 budget report under both the extended-baseline and alternative fiscal scenario.
  • In 2020, excess cost growth for spending in Medicare and Medicaid will equal its historical levels of 2.3 percentage points and 1.9 percentage points respectively.
  • From 2009 through 2020, excess growth in all other spending (e.g., private health care and other public programs) will equal its historical average of 1.8 percentage points.
  • Excess growth in all three categories–Medicare, Medicaid and other spending–slows beginning in 2021. The slowdown in Medicare spending is one-third the rate of slowdown in non-Medicare spending.
  • Excess cost growth for other health spending declines smoothly from 1.8 percentage points in 2020 to 0.1 percentage points in 2083.
  • The rate of excess cost growth from Medicare drops from 2.3 percentage points in 2020 to 0.9 percentage points in 2083. For Medicaid, excess cost drops from 1.9 to 0.1 percentage points between 2020 and 2083.
  • Overall, average excess growth of all health care drops from 1.9 percentage points in 2020 to 0.5 percentage points in 2083, averaging 0.8 percent over that period.

Why will excess cost growth slow? The CBO gives four reasons: i) higher cost sharing, ii) increased utilization management, iii) reduced insurance coverage by employers, and iv) greater scrutiny of new technologies (e.g., cost effectiveness review). Under these projections, “spending per person by 2035 would have growth by more than $14,000 (in 2009 dollars) but more than 80 percent of that extra money would be spent on health care. Although spending for other goods and services would grow by just 14 percent, spending for health care would nearly triple.”

Source:

• “The Long-Term Outlook for Health Care Spending“, Congressional Budget Office, November 2007.

Previous studies have found that paitents of staff/group model HMOs consistently report lower quality of care than patients of Network HMOs.  The finding of Rodriguez et al. (2009) contradicts these assumptions.  They find the following:

• Physicians belonging to integrated medical groups had better performance on the communication and care coordination measures.
• Physicians belonging to medical groups with greater numbers of PCPs had better performance on all measures. Larger practices may benefit from economies of scales and more investment in electronic patient records.
• Productivity incentives do not improve care.  Patients of physicians with strong incentives to see more patients per day may be more likely to experience longer office wait times compared with patients of physicians that do not have these incentives.

The Denver Post has an interesting article about employee theft of drugs from hospitals. Stealing from a hospital is not easy:

“Hospitals guard drugs carefully, requiring staffers to use individual codes or even fingerprints to unlock cabinets where drugs are stored. At Rose [Medical Center], an electronic system tracks narcotics from the time they arrive at the hospital until they are thrown away. The hospital also conducts a daily reconciliation of every drug used.”

So how do hospital employees get away with this theft? Easy, they used lessons from their teenage years:

• To Steal liquor from your parents liquor cabinet, simply drink the liquor and refill the bottles with water: “A surgical nurse at Boulder Community Hospital, has pleaded guilty to stealing large amounts of fetanyl and refilling vials with water.”
• To get out of class, write yourself a fake permission slip: “A Milliken hospice nurse was accused of writing forged prescriptions for more than 4,000 pain pills.“

Who said no one ever learned anything in high school.

Primary care doctors in Seattle are looking to eliminate insurers from the medical care process. 

“Qliance customers pay $99 to join, then a flat monthly rate of $39 to $119, depending on age and level of service. Patients can quit without notice and no one is rejected for pre-existing conditions…Co-founder Norm Wu said per-patient revenue is triple that of insurance-based clinics. He said many costs are fixed so the firm, now losing money, will turn to profit as business grows.  More than 50 noninsurance clinics operate in 18 U.S. states, based on different business models, Wu noted.”

In essence, primary care doctors are providing taking on the risk of excessive patient illnesses.  However, since Qliance only treats patients in the primary care setting, its risk is minimized.  If a patient gets too sick or needs to be hospitalized, Qliance is not liable for these types of medical treatment.  Patient who participate in the Qliance plan need to buy catastrophic health insurance in order to cover hospitalization and speicalist care visits.  This health care model seems feasible for Qliance’s end since primary care visits much more predictable than hospitalizations. 

Will the primary care docs at Qliance simply refer all patients to specialists to save money?  They will certainly have this incentive is the clinic becomes busy, but that will be tempered by competitive pressure to provide quality service.  If quality drops, patients may return to a traditional insurance plan. 

The key assumption here is that patients are able to judge quality in the primary care setting (e.g., physician friendliness, wait times to see a doctor, time spent with a doctor), whereas they may not be able to judge hospital quality or specialist quality when they are severely il and have complicated diseases.

I doubt the membership model will revolutionize healthcare, but I am willing to bet that it will carve out a significant market share from patients who are willing to pay for better primary care.

Measuring efficiency in health care is extremely difficult.  If there was an accurate scientific measure of patient health (e.g., a 1-100 scale) before and after treatment.  That way, one could measure changes in health before and after treatment per every dollar spent.  However, measuring health outcomes is very difficult. 

In the academic literature, hospital efficiency most commonly measured as: “risk-adjusted average length of stay (Weingarten et al. 2002); cost per risk-adjusted discharge (Conrad et al. 1996); and the cost of producing both risk-adjusted hospital discharges and hospital outpatient visits (Rosko 2004).”  Measures of physician efficiency often use RVU measures.

On the other hand, private vendors often uses “groupers.”  Groupers are algorithms that group different treatments into a single episode of care for a specific illness.  For acute illnesses, hospital and physicians treatments are grouped together into one episode of care.  For chronic illnesses, vendors look at costs over a specific period of time.  ”The market leaders among episode-based measures are Episode Treatment Groups (ETGs) and Medical Episode Groups (MEGs), which use algorithms primarily based on diagnosis codes and dates of services to group-related insurance claims into episodes.”

If the grouper algorithms are correct (a big if), I believe private vendor methodology provides a better measure of efficiency since they examine the entire episode of care.  Although they may be a superior measure of efficiency, they may not help improve efficiency.  If I see certain episodes of care are efficiency or not in certain areas, it may be difficult to pinpoint which providers are being inefficient if the patient visits multiple physicians or hospitals.  On the other hand, the academic literature is more likely to use the hospital or physician as the unit of measurement.  This allows each physician or hospital to improve on their efficiency measures, but may not reflect the true quality of care if patients see many physicians or are hospitalized at a number of hospitals.  For instance, a hospital may have a high efficiency score (low cost per procedure), but if they do a bad job and the patient is re-hospitalized at a different hospital, this will not show up in the academic efficiency measures, but will be captured by the vendor measures.   

• Hussey et al. (2009) “A Systematic Review of Health Care Efficiency Measures,” Health Services Research, v44(3):784-805.

Tests play an important role in modern medical care.  Is my leg broken?  Check the X-ray.  Do I have HIV?  Look at the blood tests.

But when are tests appropriate?  In some cases, tests will not alter treatment.  For instance, let assume that a person is either healthy or has Disease X.  Disease X is untreatable or does not require treatment.  This illness could represent a life-threatening disease for which there is no treatment, or it could also represent a minor ailment which would heal on its own.  Since we know that if a patient has Disease X it won’t be treated, should insurance cover the cost of the test?

In our example, the value of information to providers is $0.  If the physician finds out the patient does not have Disease X, they will not treat them.  If they do have Disease X, they will still not treat them since because this particular type of disease.  From the clinical point of view, the test is worthless.

However, if Disease X was a life threatening disease, most patients would want to know their prognosis.  In the absence of health insurance, individuals who wanted to find out if they had Disease X could pay for the test out of pocket.  Those who preferred to save their money and deal with extra uncertainty would not have the test done.

The question is, should insurance cover the test for Disease X?  If insurance does decide to cover the test, this will increase insurance premiums.  However, if everyone who potentially would have Disease X would always have the test, this would simply be a transfer of funds from all enrollees to those who potentially had Disease X.  If some individuals would forego the test in the absence of insurance, moral hazard would mean that more of these individuals would have the test done if it were covered by insurance.  

From an insurance company point of view, what is the correct evaluation tool?  As mentioned earlier, the test has no clinical value, but patients likely would value this information highly if Disease X were life-threatening.  Should insurance companies incorporate enrollee willingness-to-pay in their benefit packages or should they rely on a strictly clinical evaluation?  I would lean towards the clinical definition, since it is very difficult to model individual willingness-to-pay.  If the test is so valuable, the patients can pay for it themselves.

The cover story of this week’s Economist examings healthcare reform in America (“This is going to hurt“).  The story recounts some of the many ills of the U.S. healthcare system: too many uninsured, too expensive, and low quality outcomes.  This is not news.  What does The Economist propose to fix the American healthcare system?  

• Pay doctors a salary.  In general, I support this idea, but it only works if doctors are employees.  Medicare would never pay doctors a salary; they could never track how many patients they saw or how much work they did.  The only way Medicare physicians would be paid a salary was: 1) if they were direct employees of Medicare or 2) they worked for employers who decided to pay them a salary.  For instance, if large, centralized healthcare systems (e.g., Kaiser Permanente, Mayo Clinic) took payments from Medicare directly, it could pay their own physicians a salary.  Salaried remuneration decreases physician incentives to work hard compared to fee-for-service payment, but since overtreatment rather than undertreatment is one of the main problems in the U.S., the salary system could work.  See my own research on how physician compensation affects surgery rates.
• Get NICE.  The Economist believes that America could use a cost-effectiveness agency like the UK’s NICE.  I agree.
• Align incentives.  Will pay-for-performance improve health care?  The Economist thinks so but I am skeptical that it will have a large impact.  Medical care is so complicated that paying for better outcomes on one dimension will distract providers from focusing on less measurable, but perhaps more important dimensions.  For instance, the Economist advocates that paying bonuses in Sweden lead to shorter wait times.  However, in the UK, setting the goal that all patients should be treated within four hours of arriving at the emergency room, lead to some perverse incentives.  ”Thousands of people a year are having to wait outside accident and emergency departments because trusts will not let them in until they can treat them within four hours, in line with a Labour pledge.”

Overall, The Economist has some valid ideas of how to improve health care.  However, broad pronouncements will not get the job done.  We need a systems approach in order to decrease the amount of unnecessary medical services and increase the quality of the important medical services that are given.  Like any reform, this is easier said than done.

What are hospitals like in the Netherlands?  A paper by Blank and Van Hulst (2009) give some insight.  The paper studies Dutch general hospitals.  These hospitals make up 80% of beds on 70% of hospital costs.  Non-general hospitals include academic hospitals and specialty hospitals (e.g., eye clinics and rehabilitation clinics).

Hospitals in the Netherlands

“Hospitals, like other health-related institutions in The Netherlands, are owned and operated predominantly by locally controlled, private not-for-profit foundations (stichtingen).” [Saltman and de Roo (1989)]  The hospital sector in general is highly regulated.  Provider wages are regulated.  The central government regulates capacity and provides prospective payment budget.

“Budgets consist of a fixed component related to capacity and a variable component related to production. The fixed component is based on the so-called adherence (the number of patients potentially using the hospital), the number of beds, and the number of associated physicians. The production related component is based on regional agreements on the numbers of first-time visits, inpatient days, daycare patient days, and the number of discharges.”

Severity of cases and the type of specialists on staff can also affect budgets as well.  This budget, however, is a legal and not a monetary measure.  Insurance companies pay the hospital through prices set by the Central Tariffs Health Care agency.  Hospitals can not make a profit, but surplus revenue can go towards capital improvements.

“Another important feature of the Dutch hospital sector is that hospitals cannot choose their patients.Patients are referred to a hospital by general practitioners. They choose a hospital with a convenient location compared with other hospitals and based on availability of the appropriate specialties.Hospitals are obliged to treat any patient presented to them, provided that they have the medical knowledge required for the treatment. In practice, hospitals can attract patients by supplying particular specialties or a high quality of care. This implies that expansion of high-tech medical treatments may be another goal.”

Statistics and Trends

Statistics on the Dutch hospital industry can be found in this table.  We see that the number of general hospitals decreased from 109 in 1995 to 89 2002.  This was due to both closures and mergers.  First-time hospital visits increased at an annual rate of 4% per year, but the number of inpatient days decrease by about 4% per year.  This indicates a trend towards fewer overnight hospital stays.  Overall, costs rose by more than 6% per year in nominal terms or about 4% in real terms.

• Blank JLT, Van Hulst BL (2009) “Productive innovations in hospitals: an empirical research on the relation between technology and productivity in the Dutch hospital industry” Health Economics, Volume 18 Issue 6, Pages 665 – 679
• Saltman RB, de Roo AA (1989) “Hospital Policy in The Netherlands: The Parameters of Structural Stalemate” Journal of Health Politics, Policy and Law, Vol. 14, No. 4, Winter 1989

There is an interesting debate at the N.Y. Times discussing how to reform physician payment to increase quality and decrease cost.  Below is an excerpt from a Seattle emergency room doctor.

In this, they are half right: over-utilization is a driver of cost, and it is in part driven by doctors’ economic incentives. The underlying cause, however, is a bias within the physician compensation system that extravagantly rewards surgical procedures performed compared to “cognitive” services like diagnosis and medical management.

In the E.R., for example, sewing a facial laceration pays far better than accurately diagnosing a heart attack. The same principle applies to any procedure — from angiograms to colonoscopies.

The predictable consequence is that physicians gravitate toward lucrative procedural specialties. They perform more and more procedures, using expensive new technologies, driving costs ever higher.

The book Systems of Survival (review) describes two moral structures: commerce and guardianship.  Jane Jacobs describes the ethics of Commerce as a moral syndrome equal, antagonistic, and complementary to the ethics of politics, or Guardianship. 

• Commerce provides the economic engine and the ethical framework for trade, technological advance, and individual rights that combine to make governments worth living under.
• Guardianship:  Government protects commerce, provides stability, administers justice, and enforces uniform standards.

The two moral systems reflect societies dilemma of how to  pay doctors.   Republicans generally think of doctors as fitting into the Commerce ethic.  They are type-A personalities whose drive leads to medical advances and an increased standard of living.  Doctors are scientific and believe in objectivity.  

Democrats believe physicians should fit more into the Guardianship role.   One could think of doctors as “professionals” who distribute advice similar to a government official.  The doctor’s role is to provide medical care to those who need it, not maximize revenue or only treat those who can pay.

The Commerce doctor should receive FFS payment; the Guardian doctor should work on a salary.  The “guardian” doctor is best for standard day-to-day care, but the “commerce” doctor is needed to advance medical knowledge and technology.  Resolving this conflict between the doctor as a commercial agent and a guardian may hold the key to improve physician payment structures.

From the USA Today, here are the wait times to see a doctor in the following cities:

• Boston: 49.6
• Philadelphia: 27
• Los Angeles: 24.2
• Houston: 23.4
• Washington, D.C.: 22.6
• San Diego 20.2
• Minneapolis: 19.8
• Dallas: 19.2
• New York: 19.2
• Denver: 15.4 days
• Miami: 15.4 days

The first thing that jumps out from these numbers is that Boston has by far the longest wait to see a doctor.  Is this caused by the universal health coverage enacted in Massachusetts?  The answer is maybe.  Physician supply adjusts slowly (i.e., it takes a long time to finish med school).  On the other hand, Massachusetts decision to increase insurance coverage lead to a spike in the demand for medical services.  Thus, universal health care may have caused the run up in wait times, but this phenomenon may be short lived.  Physicians may migrate to Massachusetts as insurance coverage becomes more available.  

Do wait times reflect quality of care?  If Boston residents have very short waits to see nurse practitioners or physicians assistants, this could be a cost-effective substitute for services provided by physicians in the primary care setting.  Further, longer wait times for specialists could be a good thing.  While longer wait times would certainly hurt some patients–likely the most seriously ill patients–it would discourage other patients from waiting to see a specialist.  This patients could, instead, forego treatment if had a low marginal benefit to begin with or they could rely on their primary care provider.  

Let’s dig deeper into the numbers (see original report):

• Wait times for Boston cardiologists decreased from 37 days in 2004 to 21 days in 2009.  
• Wait times for Boston orthopedic surgery increased from 24 days in 2004 to 40 days in 2009.  
• Wait times for a Boston ObGyn increased from 45 to 70 days between 2004 and 2009 in Boston.
• Wait times for a Boston Family Practice physician was 63 days in 2009. 

We see that after the Massachusetts health reform was enacted, there was no uniform effect on specialist wait times, but there was a large increase in wait times for primary care providers.  This could be explained by a number of phenomenon:

• Those who gained health insurance after the Massachusetts health reform were a healthier population and used their new insurance coverage to increase the number of primary care visits, but not specialist visits.
• After the Massachusetts health reform, the increase in demand was homogenous across primary and specialty care.  However, physician supply adjusted.  Specialist may have been more attracted to practicing in Massachusetts, but primary care doctors were not.  Specialists may have moved to Massachusetts in larger numbers, particularly if New England health plans reimburse specialists at a much higher rate.  
• This could be a statistical anomaly.  Sample sizes in were less than 20 for five specialities in Boston.

Whatever the case, further study is needed to understand how health insurance expansions affect waiting times in both the short- and long-run.

Why does Medicare spend $7,500 for patients in El Paso, Texas but spends $15,000 for patients in McAllen, Texas?  It McAllen richer? Does McAllen receive better care?  Are patients sicker in McAllen?  

“Come on” the general surgeon finally said. “We all know these arguments are bullshit.  There is overutilization here pure and simple.”  Doctors, he said, were racking up chanrges with extra tests, services, and procedures.

The surgeon came to McAllen in the mid-nineties and since then he said, “the way to practice medicine has changed completely.  Before, it was about how to do a good job. Now it is about ‘How much will you benefit?’”

Since 2004, every service man and woman killed in Iraq or Afghanistan has been given a CT scan.  The military has a database of over 3000 of these scans.  This information “…has revealed deficiencies in body armor and vehicle shielding and led to improvements in helmets and medical equipment used on the battlefield.”

Mechanics not only diagnose what your car needs, they also fix it.  Doctors also both diagnose and treat the patient.  Both of these cases are examples of credence goods.

A working paper by Frankel and Schwarz (2009) looks at the economic environment where uninformed customers rely on experts to both diagnose and treat their problems. If experts can earn more money doing high margin procedures, then customers may not receive appropriate treatment.  However, experts must also take into account how doing unnecessary treatments will affect their reputation.

“In the 1950s, Bower was summoned to Los Angeles by billionaire Howard Hughes, who wanted him to study Paramount Pictures…. But Bower sensed that nothing good could come of working for Hughes. He found the entrepreneur’s approach to business ‘so unorthodox and so unusual’ that he felt he would never be able to help Paramount. Instead of taking the assignment and reaping a big fee, he walked away. The move was classic Bower. He built McKinsey into a global consulting powerhouse by insisting that values mattered more than money” (Byrne (2003)). In other words, by publicly rejecting a profitable action, McKinsey increased its future business. 

Because of reputational concerns within a  in a repeated game framework, the authors show a truthful equilibrium will emerge.  ”The promise of future business removes the incentive to play major treatments over minor ones. Customers only need to look at the most recent action taken. If it was a minor treatment, they return to the last period’s expert with high probability. If it was a major treatment, they return with a low probability.”

• Frankel and Schwarz (2009) “Experts and Their Records” NBER Working Paper #14921.

• 23 percent of tympanostomy tubes placed for middle ear infection are inappropriate (Kleinman et al. 1994);
• 5–35 percent of adult asthma care are inappropriate (Starfield et al. 1994);
• 16 percent of hysterectomies are inappropriate (Bernstein et al. 1993);
• 9.4 percent of hospital admissions for pneumonia are considered inappropriate (Payne et al. 1995); and
• 20 percent of pacemaker implantations are inappropriate (Greenspan et al. 1988).

Source: Binder and Rudolph (HSR 2009)

Last week a consortium of health insurers, health providers, hospitals and pharmaceutical manufacturers claimed that they could save the country $2 trillion in health care costs.  I was skeptical of this claim.

It turns out now that the American Hospital Association (AHA)–one of the signees of the letter–is also skeptical.  Fierce Healthcare reports that AHA president Richard Umbdenstock says “we did not say that we would save this country $2 trillion on our own.”  Looks like the letter to Obama is no more than empty promises.

• HT: Joe Paduda

A recent study found that “Acupuncture is an effective treatment for chronic back pain. People receiving acupuncture are more likely to get better.”

How does it work? The treatment’s placebo effect explains the study’s findings. Researchers found that acupuncture was effective whether or not the skin was punctured.

In a letter to President Obama today, AdvaMed, AHIP, AHA, AMA, Pharma, and SEIU all claimed that they would save the country $2 trillion.  Saving, however, is a relative term.  The goal is to reduce the rate health care expense growth by 1.5%.  Thus, this is not a true savings in the typical sense of the word, but a goal to have health care costs grow less than expected.  How do this consortium of “private sector stakeholders” attempt to  accomplish this savings?  Below are proposed solutions and my response.  

• Administrative simplification, standardization, and transparency that supports effective markets.  This would certainly make the health care system more efficient.  Much time and money is wasted arbitrating what procedures and services are and are not covered.  However, some health care administrative spending is useful; it makes sure that wasteful health care services are not paid for.  Further, in 2004, only 7.3% of health care spending was attributable to administrative costs (Borger et al. Health Affairs 2006).  Even cutting administrative costs in half will not solve the problem of high insurance premiums.
• Reducing over-use and under-use of health care by aligning quality and efficiency incentives among providers.  This gets to the heart of the matter.  My “Operating on Commission” paper shows that the manner in which physicians are compensated has dramatic effects on surgery rates.  While choosing optimal levels of care would vastly improve health care quality and reduce cost, it is extremely difficult to do in practice.  How does one define over/under-use?  Should a 40 year old male get surgery to repair an ACL injury?  This will not impair his ability function, but will affect his ability to play sports.  Should insurance cover this?  If we want to reduce health care costs, will have have to make some difficult choices and cut benefit generosity significantly.
• Encouraging coordinated care and adherence to evidence-based best practices and therapies. Coordinated care and more frequent use of evidence-based medicine should increase quality.  Fewer mistakes can lead to fewer hospitalizations and thus less care.  As always, the devil is in the details.  How is care to be coordinated?  Will there be nation-wide electronic medical records?  Large, centralized health providers–such as Kaiser Permanente–are good at implementing evidenced-based medicine. It is more difficult, however, for physicians in small group practices to keep up with the latest techniques.  Large, centralized health plans are the best way to implement evidence-based medicine, but concentrating health care in the hands of a few insurers could decrease competition and raise premiums.
• Reducing the cost of doing business by addressing cost drivers in each sector and through common sense improvements in care delivery models, health information technology, workforce deployment and development, and regulatory reforms. I’m not exactly sure what this means.  It basically means, make healthcare better, but not specifics are involved.
• Reform should include a specific focus on obesity prevention.  Decreasing obesity will help improve health and quality of life overall.  However, I do not believe that this should be accomplished at the cost of individual liberty to choose what to eat and how much to exercise.  Further, reducing obesity may actually increase health care costs (since obese people die sooner).

Why have “physicians, hospitals, other health care workers, payors, suppliers, manufacturers, and organized labor” come together now?  Although they claim they want to cut costs, it is in the interest of most of these stakeholders to increase cost.  Michael Cannon notes that “Lobbyists never advocate less revenue for their members.  Ever.  If they did, they would be fired and replaced with new lobbyists.”  Cannon claims the lobbyists are writing the letter because they want universal health insurance.  It could also be the case, that these groups fear the advent of a government-run health insurance system that would compete with private insurers.  

Whatever the case may be, these associations are providing no guarantees of anything.  They say they’ll cut costs by $2 trillion, but what if they don’t?  Nothing will happen. They may argue that government projections underestimated certain factors.  Health care spending may decelerate on its own even if these groups do not change their behavior.  In fact, with the economic slowdown, medical costs will likely decrease as workers lose insurance coverage when they lose their job.  

In essence, what did the letter to Obama say: a lot of cheerleading, not a lot of action.

Four months ago, I wrote that the health care sector added jobs despite the overwhelming job losses in the rest of the economy.  Looks like the health care sector has not been fully insulated against the economic woes:

“ Six out of ten hospitals nationally are seeing a greater proportion of patients without insurance coming through their emergency departments, according to a new survey from the American Hospital Association (AHA). At the same time, nearly half of hospitals reported they have cut staff. Recent employment information from the Bureau of Labor Statistics confirms that hospital employment is no longer growing and that the number of mass layoffs for hospitals reported in February was more than double what it was a year ago.”

You can view the results of the AHA survey here.

Carl Coleman say no.  

Working during a pandemic is a supererogatory behavior — i.e., acts that are commendable if done voluntarily, but that go beyond what is expected.  Coleman argues that “…while health care professionals can legitimately be sanctioned for violating voluntarily-assumed employment or contractual agreements, they should not be compelled to assume life-threatening risks based solely on their status as licensed professionals. In place of singling out health care professionals for punitive measures, the Article argues that policy-makers should institute mechanisms to promote volunteerism.”

• H.T.: Marginal Revolution

According Economics 2.0’s review of Huckman and Pisano (2006):

WIth each additional operation the surgeon preforms in a clinic, the mortality factor of his or her patients there drops by 0.018 percentage points.  When that doctor performs an operation in another clinic during the same three-month period, patients’ death rates decline by only 0.001.  

Few heart surgeons are employed directly by hospitals.  Most cardiac surgeons work as independent contractors who operate on their patients in a variety of hospitals. It seems that when cardiac surgeons are more comfortable with their surroundings and have more established relationships with the nurses, anesthesiologists, and other support staff in the hospital, performance improves. The authors claim the following:

“The quality of a surgeon’s performance at a given hospital improves significantly with increases in his or her recent procedure volume at that hospital but does not significantly improve with increases in his or her volume at other hospitals. Our findings suggest that surgeon performance is not fully portable across hospitals (i.e., some portion of performance is firm specific). Further, we provide preliminary evidence suggesting that this result may be driven by the familiarity that a surgeon develops with the assets of a given organization.

• Robert S. Huckman, Gary P. Pisano  (2006) “The Firm Specificity of Individual Performance: Evidence from Cardiac Surgery ” Management Science, Vol. 52, No. 4, April 2006, pp. 473-488.
• Norbert Häring and Olaf Storebeck (2009).  Economics 2.0: What the best minds in economics can teach you about business and life.  Palgrave MacMillan, New York, NY.

How do hospitals estimate the cost of different inpatient stays?  A paper by Clement et al. (2009) reviews 3 techniques:

Microcosting. “With microcosting, a detailed list of each component of a patient’s care is created and costed separately for each facet of a patient’s hospitalization. Given the level of detail, microcosting is generally considered the ‘gold standard’ for costing inpatient stays.”  Direct and indirect (overhead) costs are allocated over the patient’s entire hospital stay. “…nursing hours, the electricity required to light the recovery room, the catheter implanted, the operator’s time, food costs, etc. are captured and detailed. Given its labor-intensive nature, microcosting is not implemented in many hospitals.”

Refined-grouper number. Canada implemented the first DRGs in 1967.  “The system classifies patients into categories capturing cases of similar clinical, utilization, and length of stay characteristics. The categories were then further subdivided based on secondary diagnoses, sex, age, and discharge status creating DRGs.”

In 1983, Medicare adopted the the DRG system as a prospective payment instrument.  Later the rDRG was created.  The rDRG “applies a complication and comorbidity overlay to the DRG. Thus, the principal diagnoses group similar cases, as in the original DRG system, and the secondary diagnoses are used to subsequently classify cases into rDRG. In Alberta, a system based on rDRGs was used to group cases into groups comprising similar cases … The groupers are developed using a two-step process. First, based on the principal diagnosis or procedure code, cases are grouped together. Subsequently, cases are further grouped within the principal diagnosis group, based on secondary diagnoses and procedural codes. The two-step grouping process classifies cases into RGN that correspond to the rDRG grouping system.

A cost is developed by Alberta Health and Wellness (AHW) for each RGN using the microcosting data. A weighted average of each RGN cost across hospitals in Alberta is calculated and subsequently adjusted for the severity of case mixes within hospitals.”

Case-mix-groupers. Introduced in Canada in 1983, CMGs constitute a Canadian grouping system that is analogous to, but different from the DRG system developed in the United States…Cases are classified into CMGs based on the most responsible diagnosis as opposed to the principal diagnosis used in the DRG methodology…Thus, CMGs attempt to capture the diagnosis responsible for the greatest proportion of the hospitalization instead of the admitting diagnosis. An ‘average patient cost’ is calculated from all the microcosting data…Each CMG is assigned a relative index weight (RIW) that represents the complexity of the case in comparison to the average patient. The average annual cost per admission can then be determined for specific CMGs…A cost for each hospitalization can then be estimated by multiplying the CMG-specific RIW by the average Canadian cost per case ($3,103 per case).”

• Fiona M. Clement (Nee Shrive), William A. Ghali, Cam Donaldson, Braden J. Manns (2009) “The impact of using different costing methods on the results of an economic evaluation of cardiac care: microcosting vs gross-costing approaches” Health Economics, Volume 18, Issue 4  (p 377-388)

Arnold Kling and Michael Cannon believe that the idea of the physician as a lone independent craftsment is out-of-date.  The authors contend that healthcare quality would improve and costs would drop if physicians adopted a more corporate environment.  Larger organizations, such as the Mayo Clinic, Kaiser Permanente and Veterans Affairs all benefit from economies of scale and a team-based medical approach.  Nevertheless, physicians generally are loath to accept this organizational structure, because they do not want their own authority and decision-making abilities undermined by a larger corporate structure.  Below are some excerpts from their article “Does the Doctor Need a Boss?”

• “Medicare’s payment system generally does not reward coordination. Instead, Medicare and other fee-for-service payers tend to favor technologically intensive specialist services over those of general practitioners who might be best suited to play the role of project manager. The mismatch between payment systems and patients’ needs can be seen in the fact that the supply of gerontologists is not increasing, in spite of the obvious demographic basis for greater demand and the value gerontologists can add as project managers for those who are least able to coordinate their own care.”
• “…the markets for legal and accounting services are dominated by corporate providers that can hire, coordinate, and monitor the services of those specialists. In medicine, transaction costs include the costs of soliciting input, sharing information, and coordinating treatment among multiple clinicians, often across space and time. Thus it is not unreasonable to think that delivering health care effectively, particularly for complex patients, could require a corporate model of organization.”
• “In a corporate setting, a doctor would not have a business or administrative function. The doctor would not worry about what is billable and what is not. Instead, the doctor’s job would be to serve patients according to corporate standards. The doctor would be paid a salary, with increases, bonuses, and other incentives that take into account direct observation of the doctor as well as patient satisfaction and peer evaluations.”
• “There is nothing magical about a corporation as an organization. Corporate bureaucracies are inherently inflexible, imperfect, and unimaginative. Competitive market pressures force corporations to overcome those limitations and are therefore essential to improving medical care. If corporations risk losing customers when they fail to keep pace with market standards for excellence, they will find a way to improve—or go out of business.”

Citation

• Kling, Arnold and Cannon, Michael F. (2009)  “Does the Doctor Need a Boss?” Cato Institute Breifing Paper #111, Jan 13, 2009.

At the turn of the century, California passed laws mandating minimum nurse-to-patient ratios.  These laws went into effect in 2004.   Initially, the nurse patient ratio was 1:6, but those ratios were decreased to 1:5 in 2005.  Do minimum nurse staffing laws increase the quality of medical care or do they simply increase costs and drive up nurse employment?

A paper by the California HealthCare Foundation attempts to answer this question.  The authors use data from the  Office of Statewide Health Planning (OSHPD) and the California Employment Development Department (EDD) to measure hours of work for registered nurses, licensed vocational nurses, aides and orderlies.  AHRQ data is employed to identify hospital-specific quality measures which could be affected by changes in nurse staffing patterns.  

“… nurse staffing legislation resulted in higher use of registered nurses in most California hospitals. Implementation of the staffing regulations could not be tied to changes in hospital finances; rather, changes in Medicare and Medi-Cal payment rates and demands to address seismic building requirements had far greater effects on finances. Hospital administrators found that it was challenge to meet the staffing requirements, particularly in ensuring that staff were available at all times, including during breaks and meals. Finally, many of the health care leaders interviewed for the study expressed an expectation that the minimum staffing ratios would increase the quality of care due to increased interaction with patients; however, there was no evident change in patient length of stay or adverse patient safety events. None of these findings were affected by hospital ownership, financial position, or patient mix.”

• California HealthCare Foundation, UCSF Center for California Health Workforce Studies, (2009) “Assessing the Impact of California’s Nurse Staffing Ratios on Hospitals and Patient Care.” Issue Brief, February 2009.

In Turkey, the number of private hospitals has expanded from 250 in 2006 to 375 in 2008. Healthcare Europa reports that Turkish private hospitals previously charged whatever prices they pleased.  The government health insurance plan would pay the basic rate to the private hospitals, and the patient would be responsible for any difference between the government and the private sector rate.  This is known as “topping off.”

With the recent economic swoon, “the  government limited top-ups to a 30% ceiling in July 2008 -that spelt disaster for the private sector.  Lavish A-group hospitals, offering equivalence to top US and European hospitals, were typically adding 150% plus, more modest B-group hospitals 100% and C group hospitals – described as the same as a public sector hospital - were adding 20-50%.”

With declining demand and price controls, hospitals were seeing red.  However, “Filix Cevirme, General Coordinator at the Association of Private Hospitals (OHSAD), says the government is expected to up the ceiling to 70% after regional elections in March.”

Joe Paduda of Managed Care Matters has a two great posts on Medicare’s new payment structure.  

The first post reports how exactly Medicare is changing its reimbursement for medical services.  ”It looks like reimbursement for cognitive services – the 99xxx codes for readers expert in CPT-4s…office visits and similar services for others – will be increased while payments for surgeries, imaging, and other ‘procedures’ will be reduced.”

The question remains, will these changes stick?  For years, policy experts have advised CMS to increase primary care compensation and decrease specialist compensation.  However, specialists are a smaller, more cohesive group.  This facilitates the formation of compelling lobbies for specialists.  Mr. Paduda accurately predicts that these Medicare reimbursement changes will create a “loud, violent, and ugly” political backlash from specialists.

In the second post, Mr. Paduda reveals some insight as to how Medicare reimbursement changes will affect Medical care contracting in the short- and long-term.

A hospital is a place of healing.  It can also be a place of injury.  In the U.S., 2.9% of people who enter the hospital are actually harmed by the care they receive.  Yet what are the costs of these injuries?

A paper by Encinosa and Hellinger (HSR 2008) attempts to estimate the cost of hospitals failing to prevent advser medical outcomes.  The authors examine 14 patients safety indicators (PSIs) such as: anesthesia complication, accidental laceration, foreign body left in, iatrogenic pneumothorax, transfusion reaction,  infections due to medical care, sepsis, pulmonary embolism and deep vein thrombosis, acute respiratory failure, physiologic and metabolic derangements, hemorrhage/hematoma, wound dehiscence, postoperative hip fracture and decubitus ulcer. 

The authors found the following results:

“Excess 90-day expenditures likely attributable to PSIs ranged from $646 for technical problems (accidental laceration, pneumothorax, etc.) to $28,218 for acute respiratory failure, with up to 20 percent of these costs incurred postdischarge. With a third of all 90-day deaths occurring postdischarge, the excess death rate associated with PSIs ranged from 0 to 7 percent. The excess 90-day readmission rate associated with PSIs ranged from 0 to 8 percent. Overall, 11 percent of all deaths, 2 percent of readmissions, and 2 percent of expenditures were likely due to these 14 PSIs. ”

• Encinosa WE, Hellinger FJ (2008) “The Impact of Medical errors on Ninety-Day Costs and Outcomes: An Examination of Surgical Patients” Health Services Research, v43(6): 2067-2085.

How do doctors know which drugs to give to which patients?  Of course there are clinical trials giving the relative efficacy of each drug.  With less than perfect adherence, however, clinical trials may not accurately predict a drug’s efficacy or the potential side effects.

A paper by  Chintadunta, Jiang and Jin (2008) look at two types of physician learning about pharmaceuticals: learning across patients and learning within patients.  Across patient learning occurs when the physician learns about the average quality of a drug.  Physicians figure out which drugs are best suited for individual patients through within-patient learning.

The authors look at physician learning in the setting of Cox-2 Inhibitors:

“Between 1998 and 2001, the FDA approved three Cyclooxygenase-2 (Cox-2) Inhibitors: Celebrex (Dec. 1998), Vioxx (May. 1999), and Bextra (Nov. 2001). All of them were heavily advertised as safer alternatives to then existing pain killers. By September 2004, the class had more than 10 million patients, annual sales had reached $6 billion in 2003, and total advertising dollars spent in 2003 were as high as $400 million. After a clinical trial associated Vioxx with severe cardiovascular (CV) risks, Merck withdrew the blockbuster drug in September 2004. CV risks and enhanced concerns on skin irritation led to the withdrawal of Bextra in April 2005. As of today, Celebrex is the only Cox-2 Inhibitor remaining on the market, with warnings added in April 2005. ”

Data and Methods

The authors use data from four sources to identify physician learning: 

1. patient-level prescription and satisfaction data from the IPSOS patient diary database (IPSOS-PD), 
2. monthly advertising expenditures obtained from the New Product Spectra (NPS) database, 
3. the number of news articles covering Cox-2s derived from Lexis-Nexis for the period 1999 to 2005, and
4. the number of academic articles covering Cox-2s from Medline from 1999 to 2005. 

Patient level satisfaction is importance because the more satisfied a patient is with the prescription, the less likely the physician will decide to switch brands.  Physician learns which brands are well-suited to which type of patients.  Advertising, media coverage and academic articles all play a roll in across-patient learning.  

The authors use a Bayesian model to identify learning.  The authors assume each physician has a prior about the relative efficacy and safety of each of the Cox-2 Inhibitors.  Patient satisfaction, advertising, media coverage, and academic articles all will update the posterior probabilities.  

The utility of each of patient, p, from using each drug, j, at time, t, is:

• U_pjt = β_0j + β_sE(satis)_jt + β_xjX_pt + β_zZ_jt +ε_pjt

The patient’s utility depends on a drug specific constant, the patient’s average satisfaction rating up to that date, patient specific factors, X, and drug specific information, Z.

Results

The authors find that there is significant physician learning based on the evolution of patient satisfaction measures.  Other types of information seem to have less of an effect on physician prescribing behavior.  Physicians hold strong priors which leads to slow updating.

Interestingly, “News articles have a positive influence on prescriptions, no matter whether these titles sound negative or non-negative. This suggests that the major role of news articles is informing doctors/patients of the existence of Cox-2s, rather than revealing the quality of Cox-2s…In contrast, a medical article about Cox-2s has a significant negative impact on prescription sales, even if its title and abstract are non-negative.”

Thus, the authors find that doctors learn more within-patient than across patient.  

FDA updates have no impact on physician behavior.  How can this be?  By the time the FDA issues a warning on the risks of the potential risk of different drugs, there almost always have been academic articles published on these issues.  This is not to say that the FDA updates are useless, only that they often come after the academic research has already taken place and the physicians have already updated their priors.

For policy makers, the conclusions of this study may be worrisome for proponents of evidenced based medicine.  Currently, physician learning from new information is very slow.  Secondly, physicians seem to focus on tailoring treatments to individual patients rather than updating whether or not the treatment is worthwhile in the first place. 

•  Pradeep Chintadunta, Renna Jiang, Ginger Z. Jin (2008) “Information, Learning, and Drug Diffusion: the Case of Cox-2 Inhibitors” NBER WP #14252.

Health Economist Uwe Reinhardt supports expanding the DRG system to all payers.  

“Under Medicare’s approach, hospitals are paid one price for an entire inpatient episode, rather than piece-rate (fee-for-service) for every single supply and service delivered in that episode…To eliminate the rampant price-discrimination inherent in current hospital pricing, all hospitals under this system would be required to charge all patients the same price for a given D.R.G. Ideally, this stricture should apply even to patients covered by Medicare or Medicaid, as is done in the “all payer” system that has long been operating in Maryland and seems to have worked well there…Payments in addition to the case-payment would have to be made for highly complex cases — so-called “outliers.” Medicare has decades of practical experience with that problem as well.”

If economists decided to re-write the Ten Commandments, “Thou shalt love Competition” may make the list.  However, does competition always improve quality?  Even in the case of health care?

A paper by Scanlon et al. (2008) “…found no evidence of a strong and consistent relationship between HMO competition (measured either by the HHI or the number of HMOs) and plans’ scores on the CAHPS and HEDIS measures of health plan performance.”  The authors did find, however, that increased competition can lead to lower health premiums.  

Because price is easily observable and quality is not, it seems sensible that increased competition will push down prices, but may not improve quality.  Further, more competition means more fragmented medical care, which can increase the cost to provide quality health care services. 

• Scanlon DP, Swaminathan S, Lee W, Chernew M. (2008) “Does competition improve health care quality?” HSR, v46(3):1931-1951.

In the news, you often hear that there are shortages of nurses and physicians.  We need more nurses and physicians, right?  According to an editorial by Laurence Baker in Health Services Review, we should be a little skeptical of calls for more and more healthcare providers.  If supplier-induced demand is a problem, more providers will only increase the amount of medical care provided.  For instance:

• Bunker (1970) found that in 1967, “there were 39 surgeons per 100,000 persons in the United States, and less than half as many—18 per 100,000—in England and Wales. America, he also found, had a much higher rate of surgery, about 7,400 surgeries performed per 100,000 people in 1965, about twice the 3,770 reported for 1966 in England and Wales.”
• Fuchs (1978) “estimated that 10 percent increases in the surgeon/population ratio resulted in about a 3 percent increase in per capita utilization of surgeries.”
• “Sloan and Schwartz (1983) concluded that a 10 percent increase in the supply of physicians would be associated with a 4 percent increase in spending for physician services.”
• Fisher et al. (2003 a, b) “…argued that in the Medicare program, having more specialists per capita in an area is associated with higher surgery rates and higher procedure rates.”
• “Baicker and Chandra (2004) showed that states with the more specialists tend to rank lower in quality than states with fewer, and vice versa for generalists.”

Does expanding supply the of physicians unambiguously improve health care quality?  No.  It is likely that increasing the supply of primary care physicians will increase quality and increase cost at a slower rate.  On the other hand, an increase in the supply of specialist may or may not improve quality and will almost certainly increase costs.  Increasing the supply of physicians may improve health care system, but it should not be dogma that this is always the case.

One of the perennial questions of interest for health services researchers how to pay for health care.  A paper by Chalkley and McVicar (2008) examines this question in the contest of a reform in Britain’s National Health Service (NHS).

“After 1990 hospitals, which had previously been under the direct control of Health Authorities, could apply for NHS Trust status whereby they would be given discretion over employment, remuneration scales and the disposal of assets. This discretion was subject to limits and reservations and could ultimately be revoked if the appropriate authority, in this case the Secretary of State for Health, deemed their actions to be against the ‘public interest’.”

There are three types of payment contracts between the NHS and health authorities.  The first is a block contract where hospitals receive a flat contract to care for a patient population regardless of the actual care given.  The second contract is a cost-per-case contract where the hospital is paid based on the cost of the medical services supplied.  Volume contracts similarly base payment on the quantity of care provided.  The final contract is a sophisticated block contract.   This is similar to the simple block contract but requires the NHS to monitor the hosptials to ensure that they are providing the required care.

The authors offer 4 conjectures of when different contracts will be adopted.  When contracts will be adopted depends on 3 characteristics: variability in cost, variability in volume and easy of observing patient treatment.

1. When variability in cost and volume is small or variability of cost is small and volume is easily observable]then block contracts will be favored.
2. When monitoring costs are low, variability of volume is large, variability of cost is small then sophisticated block contracts will be favored.
3. When variability in cost is large and variability of demand is large then cost-per-case payments will be favored.
4. Characteristics of purchasers and/or providers that mitigate monitoring costs will give rise to a greater use of volume-dependent and sophisticated block contracts relative to simple block contracts. 

The results from a multinomial logit regression support these conjectures.  

Thus, although policymakers would prefer a one-size-fits all contractual arrangement, the authors show that contractual arrangements between the health purchaser and the provider must take into account the variability inherent the good being supplied.  For instance, simpler contracts should be favored when monitoring costs are high, but more complex contracts may be feasible with lower contractual cost.  Low variation in cost and volume makes block payments very attractive.  However, when there is significant variation in cost or volume, cost-per-case or volume-dependent contracts can help mitigate the providers financial risk.

•  Chalkley and McVicar (2008) ”Choice of contracts in the British National Health Service: An empirical study ” Journal of Health Economics, v27(5): 1155-1167.

Europe is known for having single-payer, government provided healthcare.  But  just because there is significant government involvement in the financing of medical services does not mean that private hospitals are non-existent.

An interesting series of post by HealthcareEuropa looks at private hospitals that operate in Bulgaria, Turkey and Germany.

From the researchers at the Dartmouth Atlas of Health Care:

“Regional differences in Medicare spending are largely explained by the more inpatient-based and specialist-oriented pattern of practice observed in high-spending regions. Neither quality of care nor access to care appear to be better for Medicare enrollees in higher-spending regions.”

• Fisher ES, Wennberg DE, Stukel TA, Gottlieb DJ, Lucas FL, Pinder EL. (2003) The implications of regional variations in Medicare spending. Part 1: The content, quality, and accessibility of care. Ann Intern Med. 2003 Feb 18;138(4):273-87

Bob Laszewski has a great posts on 5 false  “solutions” to reduce health care costs.  These are:

• EMR: Making electronic medical records universal will greatly improve health care quality, but the impact on cost will be minor.  Better quality care can reduce iatrogenic injuries and reduce cost, but the cost reduction–if any–will likely be small in magnitude.
• Prevention.  From the CBO: any gains from reducing obesity would be concentrated in the short and intermediate period “because some of the savings will be offset by increased longevity and the cost of disease that are most prevalent during old age.”
• Outcomes Research:  Laszewski claims that “inefficient use of technology is the key driver in health care spending accounting for an estimated 38% to 65% of spending growth.  The problem…with the suggestions that more outcomes research will save us money is that more than twenty years of outstanding outcomes research, Dartmouth for example, has not kept our health care costs under control.”  Outcomes research is important; it is imperative for physicians to prescribe cost effective treatment.  However, I agree with Laszewski that if financial incentives are not aligned to promote physician use of evidence-based medicine, then health outcomes research will have little impact.
• P4P: Laszewski doesn’t like pay-for-performance because in order for it to save money, it must lead to a reduction in physician payment on average.  Another reason why P4P won’t work is that paying individuals to check a diabetic’s A1C level may increase the frequency the physician monitors this metric, but it also may compel the physician to substitute their time away from other necessary medical services.
• Universal Coverage.  Universal coverage should reduce the percentage of individual who go to the emergency room for primary care needs;.  Nevertheless, providing universal health insurance coverage will certainly increase healthcare spending due to the moral hazard problem as well as supplier-induced demand.

In the U.S., 2.9% of individuals who enter a hospital are actually harmed by the medical care they receive.  Reducing these preventable iatrogenic injuries is one of the goals of any hospital administrator.  Paul Levy of Running a Hospital lists 3 goals to achieve in the new year which will help reduce these adverse events.

1. Eliminating central line infections [Metric: The number of CLIs, as defined by the CDC. Goal = 0]
2. Adopting the IHI bundle to help avoid ventilator associated pneumonia [Metric: Percent compliance with the bundle. Goal = 100%]
3. Adopting the WHO protocol developed by Brigham and Women’s Hospital’s Atul Gawande for surgical procedures [Metric: Percent of surgical cases in which the pre-op, time-out, post-op checklist has been followed. Goal = 100%]

The Center for Studying Health System Change gives some insight into how patients choose their doctor:

“Among consumers who found a new provider, few engaged in active shopping or considered price or quality information—especially when choosing specialists or facilities for medical procedures. When selecting new primary care physicians, half of all consumers relied on word-of-mouth recommendations from friends and relatives, but many also used doctor recommendations (38%) and health plan information (35%), and nearly two in five used multiple information sources when choosing a primary care physician. However, when choosing specialists and facilities for medical procedures, most consumers relied exclusively on physician referrals. Use of online provider information was low, ranging from 3 percent for consumers undergoing procedures to 7 percent for consumers choosing new specialists to 11 percent for consumers choosing new primary care physicians.“

I have written in the past about the recent popularity of single specialty hospitals (see “Focused Factories” and “…Specialty Hospitals” posts).  A paper by Kathleen Carey investigates whether or not single specialty hospitals are more efficient than traditional mutli-specialty hospitals.  The study finds the following:

• Overall, single speciality hospitals (SSH) are not more cost efficient than competing, full-service, acute care hospitals.
• There was not a significant difference between cardiac SSH and full-service hospital cost inefficiency.
• There was a significant difference between orthopedic/surgical SSH and ful-service hospital cost inefficiency.

Patients choose hospitals based on the quality of the medical care they receive and the hospital’s distance from their home.  But what nonclinical criteria do patients value most?  The Salud y Gestión blog reviews the findings of a study in The McKinsey Quarterly.  The study found that patients rank the following as the most important nonclinical criteria influencing their hospital choice.

1. Keeping patients informed about treatment both during and after visit (77%)
2. Conducting Scheduled appointments on time (75%)
3. Room appearance (66%)
4. Ease of scheduling appointments (64%)
5. Food and entertainment options in room (63%)
6. Value for the money (62%)

Health economics, physicians and health services researchers have found that overuse, not underuse, is the major problem for many medical services.  Yet you rarely here a campaign to reduce that quantity of medical care provided.  Why is this?

An editorial in Health Services Research gives two important explanations for this.  First, measuring overuse is difficult.  ”For example, a health plan cannot easily determine whether a child receiving a tympanostomy tube for treating otitis media with effusion was ‘overuse.’ To assess appropriateness, at least one year’s worth of medical records documenting the number of episodes and duration of ear infections is necessary (Keyhani et al. 2008).”  Needless to say, this creates a significant data burden.  The RAND Appropriateness Method [Brook et al. 1990]  may provide some guidelines for which medical services are necessary, but even these methods are imperfect.

The second problem is that reducing overuse often cuts into the income of a politically powerful groups: doctors, medical device makers, and pharmaceutical companies.  

“One well-known illustration occurred when the Agency for Health Care Policy and Research (AHCPR), now known as the Agency for Healthcare Research and Quality (AHRQ), published guidelines that suggested that nonsurgical approaches were recommended in the initial management of acute back problems. The guidelines and underlying research supplying evidence led to lobbying efforts from the North American Spine Society, which felt that its scope of practice was threatened (Deyo et al. 1997). The end result was that the House of Representatives passed a resolution in 1996 for zero funding for AHCPR. The budget for the Agency was restored in the Senate after significant efforts by the research advocates. However, this experience led to the creation of a newly named Agency, with a mission that largely abandoned its role in guideline development.”

• Salomeh  Keyhani and Albert L.  Siu (2008) “The Underuse of Overuse Research,” Health Services Research, Volume 43, Issue 6, Pages 1923-1930.

How do financial arrangement between physicians within a medical group affect efficiency levels?  This is the question Gaynor and Pauly (JPE 1990) attempt to answer.

Theory

 The authors assume that the quantity of medical services is produced by the following production function:

• q_i = f(h_i, t_i, k_i, e_i, θ_i)
• h: physician hours, t: non-physician hours, k: capital, e: effort level, θ: other factors.

• u_i = y_i – v_i(e_i, h_i)
• y_i = α(P-C)q_i + n^-1(1-α)(P-C)Σ_{(1 to n)} q_i
  • The variable α represents the percentage of work that physicians receive 100% of the net profit they generate and (1-α) represents the net profit generated shared among the n physicians in the group.
• ∂u_i/∂e_i = [α + n^-1(1-α)](P-C)(∂f_i/∂e_i) – ∂v_i/∂e_i) = 0

So know we’ve done some math.  Who cares?  What do we get out of all these equations?   The first order equation, ∂u_i/∂e_i, shows that when physicians optimize their effort level, they trade off the benefit from extra effort (more money) versus the cost of more effort (they’d rather be golfing). The authors can also use comparative statics to to predict how they will affect physician effort.

• α: An increase in the percentage of work where the physician receives 100% of the profit generated will increase effort.
• P: An increase in the price of a medical service will increase physician effort.
• C: An increase in the cost of a medical service will decrease physician effort
• n: As the number of physicians increase, effort decreases.  This is because physicians will have to share more of their income with other doctors.  This results falls in line with the finding of Newhouse (1973).  This paper found evidence of “behavioral diseconomies of scale” whereby physicians shirk more as the number of physicians in the group increases.

• Martin Gaynor and Mark V. Pauly (1990) “Compensation and Productive Efficiency in Partnerships: Evidence from Medical Groups Practice” Journal of Political Economy, 1990, vol. 98, no. 3, p. 544-573.
•  Newhouse JP (1973) ”The Economics of Group Practice”  Journal of Human Resources, Vol. 8, No. 1, pp. 37-56.

Pay-for-performance (P4P) is the latest rage among health wonks as to how to improve the health care system. But does P4P really improve quality?

Mullen, Frank and Rosenthal (2008) hope to answer this question. One would initially believe that paying physicians to perform certain medically necessary tasks will improve quality. Further, some P4P involves structural rewards for physician practice EMR. If a physician installed an automated system to remind diabetic patients to get their A1C test, the quality benefits likely will extend to non-diabetic patients as well who will get more regular check-ups.

However, there are some reasons to believe that P4P may not work as expected. Until recently, P4P in the U.S. has been a very small component of a physician’s compensation. In the UK, P4P payments are large [the average GP practice earned $133,200 in P4P payments from the NHS] but since the P4P payments in the U.S. are a small fraction of the physicians income, it likely has little behavioral impact. Further, P4P may not result in better medical care, but better documentation of the care that has always been given. Most importantly, “providers may shift resources toward rewarded dimensions of quality at the expense of unrewarded dimensions, which may result in a decline in overall quality of patient care.”

Data

In order to test whether or not P4P is improving quality, Mullen, Frank and Rosenthal collected data from Pacificare. Pacificare experienced a wave of P4P innovations in the early 1990s until today.

• 1993: Pacificare begins collecting quality information on providers.
• 1998: Pacificare makes these quality reports public.
• 2003: Pacificare starts to pay bonuses based on the provider quality reports. this is named the Quality Incentive Program (QIP)
• 2004: Pacificare joins Integrated Healthcare Association (IHA) inauguration. IHA is a P4P program that has ten times the bonus payments as QIP and included six of California’s largest health plans.

The authors have Pacificare’s quality measures before QIP, during QIP and during IHA. As a control group, the authors use Pacificare provider quality measures in Oregon and Washington which were not subject to any P4P incentives.

The authors hypothesize the P4P will improve quality for the service for which providers receive bonuses. For non-P4P services, there will be quality improvements when a performance metric shares commonality in production with many other medical services. For instance, bonuses based on identification and scheduling will improve overall quality. On the other hand, bonuses who’s quality metric depends on physician time or effort will likely decrease quality on non-measured dimensions.

Results

“Of the six measures initially rewarded by IHA, only cervical cancer screening showed consistently positive returns.” Chlamydia screening also improved after it was added to the IHA list. “On the other hand, appropriate asthma medication rates actually decreased…when P4P was introduced in California…Preferred antibiotic usage, which was rewarded by the small-scale QIP but ignored by the larger IHA effort also declined…”

Conclusion

P4P is a very blunt instrument. In some cases it works fairly well but in other cases it does not. One problem with P4P is that it that it confuses three aspects of medical care: 1) getting patients who need medical care into the doctors office, 2) getting physicians to provide the correct care to the patients in the office and 3) documenting the care. The first problem is one of outreach and a reminder recall system, but also depends on the demographics of the physician’s patient based. The second aspect could be better measured with a missed opportunity metric. And the third would be made easier with EMR.

Is P4P rewarding doctors who have rich patients that see the doctor often? Is P4P rewarding doctors who document care more accurately? Or is P4P really improving the quality of medical care?

Because P4P is such a blunt instrument, policymakers and insurance companies cannot answer these questions.

• Kathleen J Mullen, Richard G Frank, Meredith B Rosenthal, (2008) “Can you get what you pay for? Pay-for-performance and the quality of healthcare providers” Working Paper.

The Bureau of Labor Statistics reports that Medical CPI is only 3.2%.  This is less than the 4.1% average inflation rate over the past ten years and the 6.0% average medical inflation rate over the past 30 years.  In most markets, a slowing economy reduces demand and reduces prices (see the recent decline in oil prices).  With the economic slowdown, will medical care get cheaper soon?

Joe Paduda predicts not.  Why?

1. Insurance.  Less people will have insurance for two reason.  First, as people lose their job, they will also lose their health insurance.  Secondly, as firms profits decline, it is likely that some firms will drop their health insurance benefits. When less people have insurance, this  will lead to more charity care by doctors and less on-time payment by patients.  Doctors will have to raise prices in order to compensate for the increased number of patients who don’t pay their bills.  However, for elective procedures where patients bear most of the cost, physicians may actual decrease costs (see “Red Light Special…“).  
2. Utilization.  How will the worsening economy affect medical care utilization.  Mr. Paduda claims that as the economy worsens, individuals that still have insurance will ”…get all their elective procedures done, prescriptions filled, and preventive care taken care of while still on their employer’s policy.”  However, the causation could go the other way as well.  If you have a health plan with significant deductibles or coinsurance, you may want to forego medical care in order to save more money (since you just lost your shirt in the stock market).
3. Retroactive Adverse Selection.  With the economy in a downturn, firms are most likely to layoff younger workers with less seniority.  This means that the insurance pool at the firm will be older and more expensive to serve.  Thus premiums increase which could lead to firms dropping health benefits (see point 1).

With the economy in a downturn, many firms have been hard hit.  Industries that sell luxury goods have been especially hard hit.  One example of a luxury good sector taking a beating is the elective surgery market. The New York Times reports that dermatologists, facial surgeons and plastic surgeons have all seen a significant drop in demand.  

Yet these physicians are not passive participants in the market.  In a move that Marginal Revolution’s Markets in Everything would appreciate, physicians are slashing prices.  

“In light of drastic consumer cutbacks on spending, some dermatologists, facial surgeons and plastic surgeons are promoting the kinds of markdowns, coupons or two-fers you might expect to find in supermarket circulars — complete with restrictions like ‘offer not good with any other promotion.’

…surgeons list promotions like $500 off a single operation or $1,000 off a combination of body or facial surgeries.“

Patients generally believe that managed care systems are put in place to restrict their access to care.  Many patients believe that physicians who receive capitation compensation will provide less care to their patients than physicians who are paid on a fee-for-service basis.  A paper by Fang and Rizzo (2008) investigates whether or not this is really they case.

The authors find that “both capitated and noncapitated managed care significantly increased physician incentives to reduce care during 2000-2001.”  This is just what economists would predict.  When physicians receive capitation payment, they receive non-positive marginal revenue, giving them an incentive to reduce care.

By 2004-2005, however, Fang and Rizzo found no statistically significant difference in physician desire to reduce care between physicians in managed care organizations and those who were not.  Capitation compensated doctors still were more likely to reduce care levels than other doctors but this was only marginally statistically significant (p<.08) and of a much smaller magnitude.

What can we conclude from this?  Likely it is the case that over time, managed care organizations have become less managed; non-managed care organizations have put in place more restrictions over time.  Separately identifying how managed care incentives (e.g., referral restrictions) and physician compensation incentives (i.e., capitation vs. fee-for-service) impact care levels is very important as insurance plans become more homogeneous.

If you are interested in how physician compensation affects surgery rates, you can read my paper “Operating on Commission: How physician financial incentives affect surgery rates.”

• Hai Fang, PhD; and John A. Rizzo, PhD (2008) “The Changing Effect of Managed Care on Physician Financial Incentives,” The American Journal of Managed Care, v14(10): 653-660.

Does physician compensation affect the quantity of medical care provided?  My paper “Operating on Commission” claims that the answer is yes.  I find that surgery rates increase 78% when patients switch from capitation to fee-for-service (FFS) specialists.

A paper by Devlin and Sarma (2008) examines a similar question for Canadian family physicians.  Since the inception of Canadian Medicare, 89% of family physicians have been paid on a fee-for-service basis.  The authors aim to estimate how fee-for-service compensation affects the quantity of medical care controlling for the fact that physicians who favor more aggressive treatments likely will sort into fee-for-service compensation schemes.  

The authors control for the endogeneity problem with using 2 econometric specifications.  The first uses an instrumental variables (IV) specification with 4 instruments.  The first three instruments are physician preferences for research, teaching, and non-work interests.  Physicians who enjoy teaching and research are more likely to prefer salaried compensation schemes.  The final instrument is the physician’s response to the compensation scheme they prefer.  Each of these four instruments is likely correlated with the actual way the physician is compensated, but the instrument must be uncorrelated with unobserved factors which effect physician quality.  

The second econometric specification is the treatment effects estimator (the restricted control function approach).  The treatment effects estimator assumes the following econometric structure:

• ln(q_i) = X_iα + βR_i + εi
• ΔV_i = Z_iγ + ui

The first equation shows how the physician remuneration scheme (Ri) affects the log quantity of medical care [ln(qi)] after controlling for covariates (Xi).  The second equation gives physician’s latent utility (ΔVi) of choosing one remuneration scheme over another.  The treatment effects specification estimates the coefficients based on functional form; the first equation is estimated with OLS and the second equation is estimated with a probit model.

With these two specifications, the authors find strong evidence that physicians select into different compensation schemes based on their practice styles.  ”…those who choose a non-FFS environment engaged in more patient visits per week than those who choose the FFS scheme.”  After controlling for the selection effect, the authors found that that the direct incentive effect of physician compensation was strong.  ”FFS schemes appear to strongly encourage physicians to see many more patients relative to alternative remuneration schemes.”

As I find in my “Operation on Commission” paper, financial incentives do matter.

• Devlin and Sarma (2008) “Do physician remuneration schemes matter? The case of Canadian family physicians” JHE 27(5): 1168-1181 .

Hospital-acquired, or nosocomial, infections are often caused by poor hospital care.  Patients arrive to the hospital and often leave with infections caused by unsanitary hospital conditions.  Should Medicare pay for these hospital-induced health care costs?

A knee jerk reaction would be to say no.  If the hospital adversely influence patient health, Medicare or other payors should not be responsible for those costs.  

However, if Medicare decided to implement a policy where they did not pay for nosocomial infections, doctors would report nearly all infections as community-acquired rather than hospital-acquired. Thus, not paying for nosocomial infections will adversely affect the reporting of these types infections.  If the infections are not reported, it will be difficult to eridicate them.

Thus, we are in a catch-22.  Paying for medical care resulting from nosocomial infections, discourages the prevention of these infections.  Not paying for medical care decreases the incentive to report an infection as nosocomial.  

Damned if you do, damned if you don’t.

Does an increase in family physicians (FPs) increase individual health? A naive research might believe that we could uncover whether or not this was true by comparing the average health levels of areas with lots of doctors with the average health levels of areas with few doctors. However, doctors often work where there are lots of sick people. Thus we can find a spurious correlation between FP quantity and individual health level.

Gravelle, Morris and Sutton (HSR 2008) aim to find the true relationship between FP quantity and individual health. They use data from the Health Survey for England and the General Medical Services (GMS) Statistics database. The authors note that family physicians may be attracted to areas where healthy patients live if these areas have attractive amenities not captured in the data. On the other hand, FPs might be attracted to areas where lots of sick people live since FP compensation is based on an age-related capitation payment. The authors claim that the following 2 instruments will be correlated with physician supply but uncorrelated with individual patient health: semidetached house prices and age-related capitation payments.

In the first stage, Gravelle and co-authors find that a larger age-related capitation payment attracts more FPs while increased house price decreases FP supply. The authors conclude the following:

“FP supply is positively associated with individual self-assessed health. If no allowance is made for the endogeneity of FP supply, the effect is not statistically significant…When FP supply is instrumented by age-related capitation, a 1 SD increase in FP supply increases the probability of reporting very good health by 4.1 percent. The results are robust to transformations of the health variable and to alternative specifications of the effects of individual age on health.”

• Gravelle, Morris and Sutton (2008) “Are Family Physicians Good for You? Endogenous Doctor Supply and Individual Health” HSR, 43(4) 1128-1144.

Appendix

In the paper, the authors use the ln(FP supply) as the key dependent variable. However, ln(FP supply) is an estimated figure. Thus, when the authors calculate the standard errors, they use a bootstrap methodology as follows:

1. Draw a sample of 351areas (local authorities) with replacement from the area-level data set.
2. Estimate the ln(FP supply) equations for each of the 3 years—1997, 1998, and 1999.
3. Estimate the individual-level health equation using predicted ln(FP supply) plus the individual and area-level covariates. The individual observations are weighted by the number of times the LA in which an individual lives was drawn in the first stage bootstrap sample.

The reported standard error of the instrumented ln FP supply coefficient is the standard deviation of the estimated coefficients on ln FP supply from 200 replications of this procedure.

The N.Y. Times writes about how hospitals have standardized patient warning wristbands.  Now, red wristbands will denote an allergy risk, yellow will denote a fall risk, and so on.  This should be the same at all hospitals, reducing the need to re-train nurses and other hospital staff who move between hospitals.

“The drive [to standardize hopsital bracelets] was spurred, in part, by a notorious 2005 Pennsylvania case in which a patient nearly died because a nurse used a yellow band thinking it meant “restricted extremity” (don’t draw blood from that arm), as it did at another hospital where the nurse sometimes worked, when at this hospital it meant D.N.R. [do not resuscitate]“

In the UK, a dental clinic has opened in a Sainsbury’s grocery store.  The grocery store dental clinics aim to fill a patient need caused by the shortage of dentists in the UK.   BBC News reports,

“Dentist Lance Knight said the practice aimed at “making dental healthcare more accessible and convenient to better meet patients’ needs.”

The private surgery will go head to head with the NHS, charging £16 for a check up, which is slightly less than NHS fees.”

• Hat tip: Carpe Diem

The Running a Hospital blog notes that a physician peer review system is absent in most hospitals.  Physicians are only critiqued when something goes wrong.  However, this need not be the case.

“Our Chief of Neurology, Clif Saper, originated a thoughtful practice… The doctors in his department do randomly assigned reviews of the case notes of their colleagues, with an eye towards deciding if the process and diagnosis and treatment seem warranted by the facts of the case. Those reviews, blinded by reviewer, are then shared with the attending physician. The idea is a good one, to help all of the doctors do a better job by allowing an objective review of real cases. It is specifically designed not to be threatening, though, and the results are not made public, even within the department.”

Why aren’t there supervisory physicians evaluating the work of attending physicians?  Paul Levy says “no place can afford to have dozens of senior physicians standing around judging the performance of dozens of attending physicians.”

Why not?  The reason is that most hospitals are paid not on quality but on a DRG or procedural basis. Hospitals do not get extra compensation for doing a good job, so their incentive to improve quality is small.  If the patient can easily observe hospital quality and the hospital can gain market share by providing higher quality, then it may be in the hospitals best interest to hire a supervisory physician.  It is more likely, however, that patients view hospital quality as a function of the reputation of the doctor, whether or not the hospital uses the newest technology equipment, and how the building looks.  These three items may or may not be directly related to hospital quality.

When quality of care is difficult for patients to observe, Paul Levy is correct in that it does not pay to hire supervisory physicians.

In the N.Y. Times, Sandeep Jauhar discuss the problems with P4P.  

• Hat Tip: Cato-at-Liberty.

The Carpe Diem looks at who is going to retail health care clinics.

“Roughly 90% of the patients came for one of 10 relatively simple treatments… ‘Most of the conditions cared for in retail clinics likely do not require the level of training of a physician.’”

Insurance companies are starting to support these retail health clinics.  Insurance paid for 67% of visits.

• Original Article: Mehrota et al. (2008) “Retail Clinics, Primary Care Physicians, And Emergency Departments: A Comparison Of Patients’ Visits,” Health Affairs27(5): 1272-1282.

Yesterday I wrote about the problems with fragmented medical care in America.  Is a single payer system the only solution?  A Commonwealth Fund report shows that the single payer system is not the only path towards improved, more integrated care.

What we want

The report outlines six general improvements that need to be made to improve the quality of care in the U.S.:

1. Patients’ clinically relevant information is available to all providers at the point of care and to patients through electronic health record systems.
2. Patient care is coordinated among multiple providers, and transitions across care settings are actively managed.
3. Providers both within and across settings have accountability to each other, review each other’s work, and collaborate to reliably deliver high-quality, high-value care.
4. Patients have easy access to appropriate care and information, including after hours.
5. There is clear accountability for the total care of patients.
6. The system is continuously innovating and learning in order to improve the quality, value, and patients’ experiences of health care delivery.

These are high ideals that need to be translated into specific action-items for providers.  However, a variety of different organizational structures have been able to accomplish each of these six goals.

Models

There are four general types of structures and all can be successful in delivering high quality care.

• Integrated delivery systems such as Kaiser Permanente and Geisinger Health System.
• Large multi-speciality groups such as the Mayo Clinic and Partners Healthcare.  Both groups are nonprofits.  While the Mayo Clinic directly employs doctors on a salaried basis, Partners contracts with over 1000 PCPs and 3500 specialists to provide high quality care to patients.
• Private networks of independent providers, such as Hill Physicians Medical Group and Northland Health Alliance, generally receive a capiation payment from insurers for each practice but doctors are compensated on a FFS basis.  This is similar to RVU compenation.
• Government-facilitated networks of independent providers.  Here, the government does not directly provide care, but instead coordinates care between providers.  This has worked will for Medicaid patients in North Carolina. Denmark’s universal health care system coordinates physicians, who are paid via fee-for-service plus a fee for serving as the patients medical home.  Ninety-eight percent of physicians have paperless offices, prescriptions and lab tests.

Shih et al. (2008) “Organizing the U.S. Health Care Delivery System for High Performance“, Commonwealth Fund Report  no. 1155.

The U.S. healthcare system is one of the more fragmented systems in the world. Traditionally, economists believe that a splash of decentralized planning with a heap of free markets is a recipe for efficient outcomes. In the case of health care coordination, however, information sharing, and collaborative work are needed if quality is to improve and decentralization may not be the best option. Cebul et al. (2008) describe some of the problems with America’s fragmented system. For instance:

• Health insurance is a high turnover product. About one-fifth of health insurance policyholders cancel their plans in any given year. Most of these changes are due to i) employees switching jobs and ii) employers cancelling their group plans in favor of other plans. When insurers have short term relationships with their customers, it likely does not pay for them to invest in preventive care or chronic disease management programs.
• Having a fragmented insurance market can give insurers an incentive to lower quality. When adverse selection is present, offering high quality medical care will attract sicker individuals which will drive up insurance premiums. Thus, insurers often do not have an incentive to provide high quality care.
• The fragmented insurance system means that hospitals must spend more money paying administrators to collect claims. Woolhander et al. (2003) finds that hospitals in the U.S. spend $315 per capita on administration compared with $103 in Canada.
• The fact that physicians are rarely employed by the hospitals has lead to some perverse behavior by nurses. For instance at Stanford Hospital, “Nurses were harshly blamed by surgeons for instrumentation failures, but nurses who delivered clean instruments on time achieved ’star status’ among surgeons. In this setting, some operating room staff shared instruments between surgical suites. Some nurses kept critical instruments in their personal lockers. Some surgeons also took instruments with them when they left the hospital.”
• Further, physician heterogeneity hurts efficiency by making standard operating procedures nearly impossible to implement. Generally, hospitals allow doctor to gets what they want in order to attract physicians with large patient bases to their hospital. However, this creates an incredible amount of complexity and possibility for error in the health care system.
• When providers do consolidate, it is often not done in the best interest of the patient. While vertical integration could improve quality, consolidation is often done with the purpose of locking-in profitable referrals or increasing bargaining power.
• “[Medicare] patients with diabetes see a median of eight physicians in five distinct medical practices.”

In future posts, I will give some examples of organizations that have been able to overcome these problems, as well as policy prescriptions to improve the health of America’s medical system.

See also: Fragmented Medical Care II (The Models) and III (Policy Options).

Cebul RD, Reibitzer JB, Taylor LJ, Votruba M (2008) “Organizational Fragmentation and Care Quality in the U.S. Health Care System” NBER WP 14212.

Between 1992 to 2003, the share of public hospitals in Germany has decreased from 45% to 36%, while the proportion of for-profit hospitals rose from 15% to 25%. Is this a good thing?

The economic literature has mixed findings with respect to efficiency and ownership structure. In general, economic theory predicts that private ownership is superior to private ownership; with respect to hospital ownership, however, this is not always the case:

“In his overview about non-profit ownership and hospital behaviour, Sloan (2000)…concludes that there is no clear empirical evidence for a difference between these two ownership types. Duggan (2000) uses a change in financing US hospitals to reveal that the difference between the three types is driven by the soft budget constraint of public hospitals.”

Other papers such as Brown (2003) find that non-profit hospitals are the most technically efficient while Farsi and Fillippini fund no difference in cost efficiency by hospital ownership in Switzerland.

Using data from the Statistical Offices of the Länder from 2000 to 2003, Annika Herr (2008) compares the cost and technical efficiency of three types of German hospitals: public and for-profit private, and non-profit private. To make a fair comparison between hospitals, cases are weighted by their severity. Severity is measured by the diagnosis (ICD-10) and the length of hospital stay.

Dr. Herr’s main finding is that “both private and non-profit hospitals are less efficient than public hospitals in Germany.” One of the reasons is that private hospitals were paid a per diem rate, thus increasing the hospitals incentive to increase the hospital length of stay. In 2004, capitation payments were introduced for hospital admissions so this may reduce some of the efficiency difference.

One major issue with this paper–and much of health of health economics–is that it ignores hospital quality. Once we take into account quality, then it is possible that private hospitals may out-preform public hospitals with respect to efficiency. It is also possible that private hospitals may have amenities (e.g., single rooms, newer facilities) that patients value, but do not directly affect their health. On the other hand, private hospitals could be more susceptible to supplier-induced-demand under a per diem reimbursement scheme which could further exacerbate the efficiency differences between public and private hospitals.

Another interesting item to note, Herr does mention that Augurzky et al. (2004) found that in Germany, “public hospitals face a much higher risk of insolvency and closure.”

• Annika Herr (2008) “Cost and technical efficiency of German hospitals: does ownership matter?” Health Economics, Volume 17 Issue 9, Pages 1057 – 1071
• Sloan FA. 2000. Not-for-profit Ownership and Hospital Behavior. In Handbook of Health Economics 1B, Culyer AJ , Newhouse JP (eds), Chapter 21. Elsevier: Amsterdam, 1141-1174.
• Duggan MG. 2000. Hospital ownership and public medical spending. The Quarterly Journal of Economics 115: 1343-1373
• Brown SIII. 2003. Managed care and technical efficiency. Health Economics 12(2): 149-158.
• Farsi M, Filippini M. 2006. An analysis of efficiency and productivity in Swiss hospitals. Schweizerische Zeitschrift für Volkswirtschaft und Statistik 142(1): 1-37.
• Augurzky B, Engel D, Krolop S, Schmidt CM, Terkatz S. 2004. Insolvenzrisiken von Krankenhäusern – Bewertung und Transparenz unter Basel II. Materialien 15, Rheinisch Westfälisches Institut für Wirtschaftsforschung.

A recent Robert Wood Johnson Report (see also press release) finds that uninsured children receive less needed medical care than individuals with health insurance.  The report finds that 91% of children who are insured have had a physician visit in the last year compared to only 69% of uninsured children.  Seventy seven percent of children with insurance had a well-child visit in the last year compared to 45% of uninsured children.

Does this mean that having health insurance increases the quantity of health care children receive?  Yes.  Holding health insurance decreases the marginal cost of a physician visit and this increases the probability a child will visit the doctor.

Do these statistics imply that giving health insurance to the uninsured will increase well-child visits to rates of insured children?  Likely no.  Children who have insurance are likely to be different than those without health insurance.  Those with private insurance are likely more educated, richer, and more likely to have an English-speaking household than those without health insurance.  These individuals have likely have higher demand for medical care than the average person.  Thus, giving all uninsured children insurance will likely increase well-child visit rates, but will not increase them to the level of the currently insured.  Conversely, if all insured people lost their insurance, well child visit rates would still be above individuals who are currently uninsured.

While health insurance coverage likely contributes to physician visit rates, it is not the only factor which determines a child’s frequency of physician visits.

I recently finished reading Management Lessons from Mayo Clinic by Leonard Berry and Kent Seltman. The book provides a glimpse inside one of the most successful health care organizations. While the book illuminates how Mayo Clinic has solved many of its operational issues and how it has built its reputation, the book is overwhelmingly positive. This should not be surprising since Kent Seltman was the director of marketing at Mayo Clinic from 1992 to 2006.

Thus, I would recommend this book for healthcare management professionals as long as it is read with the knowledge that the book is not an unbiased analysis of the Mayo Clinic but more of a chronicle of the Mayo Clinic’s successes.

Some of the highlights from the book are:

• The Mayo Clinic now employs over 20,000 individuals on its Rochester, MN; Scottsdale, AZ; and Jacksonville, FL campuses.
• “More than 62% of Mayo Clinic physicians have received some or all of their training at Mayo.” This helps to build a strong collaborative culture at Mayo, it does risk making Mayo insular.
• While many policy wonks advocate a “team approach” to health care, Mayo Clinics is truly one of the few health care organizations to accomplish this. This is due to the fact that all physicians are employed directly by Mayo, they are paid on a salary basis, and the culture of Mayo is very collaborative.
• The Mayo Clinic faces the debate of how fast to expand. Expanding its brand (through associated clinics, hospitals, and online contact) and increases revenues but may dilute its brand equity or reputation.
• The Mayo Clinic was one of the first organizations to organize medical records by patient rather than physician, thus allowing any physician to easily access patient information. In the digital age, Mayo is a leader in EMR.
• The Mayo Clinic has impressive systems engineering. There is centralized scheduling, and the testing facilities each day are allowed spare capacity to meet the need of current days patients (“downstream demand”), and Six Sigma management practices are in place.
• Departments are co-headed by physicians and administrators. Physicians make sure that administrators know understand how management choices affect patient care; administrators communicate with physicians so that they understand how medical practices affect patient flow and the bottom line.
• “The reality of labor intensive service organizations is that their people are their product.”

Berry, Leonard L; Seltman, Kent D. (2008) “Management Lessons from Mayo Clinic: Inside one of the world’s most admired service organizations,” McGraw-Hill, 256 pages.

Recently, the San Diego Union Tribune reported that the Sharp Grossmont Hospital in eastern San Diego county was cited for a number of preventable deaths. Reporter Cherl Clark found numerous problems, which included:

“staff members restraining a highly medicated, 25-year-old man with schizophrenia in such a way that he was allowed to suffocate. In addition, hospital workers caused the death of an 83-year-old woman who had undergone a hysterectomy by injecting a dangerous anti-narcotic into her bloodstream. Other problems included nurses who did not know or use proper CPR, an unsanitary operating-room mattress held together by tape and glue, unsafe storage and handling of food and kitchen equipment, and use of critical medications such as heparin that had expired up to a year earlier.”

CMS is threatening Sharp Grossmont that it could lose all federal money (i.e., Medicare and Medicaid). Since 50% of Sharp Grossmont’s business comes from Medicare and Medicaid patient, this would be a disaster for the hospital. What should we do with underpreforming hospitals?

In regular markets, when a product has lower quality, people stop buying that product and switch to another one. For instance, if GM stops making high quality cars, people switch to Toyota. The market compels companies to offer a desirable bundle of quality and price or else they will lose business. Because markets are so effective at maintaining high quality, withholding Medicare and Medicaid payments from Sharp Grossmont makes sense, right?

Maybe not in this case. First of all, some hospitals may not be in a competitive market. While urban hospitals must compete with other, nearby hospitals, Sharp Grossmont is supposed to provide medical care for the entire Grossmont Healthcare District, which covers 750 square miles in San Diego’s more suburban and rural East County. This area has more than 652,000 residents and Sharp Grossmont has the busiest emergency department in San Diego County. By reducing funding, individuals who have emergencies will receive even worse care than before.

This is similar to the no child life behind program. Low preforming schools lose money. But these are exactly the schools that need more money to survive. If students had the freedom to switch schools, then penalizing a failing school would make perfect sense since the students could opt for higher quality schools. The failure of low quality schools would not be a problem if students had other schools available for them to choose to attend. If individuals do not have any choice of which school they attend, however, withholding funding from schools or hospitals can make low quality schools worse.

Will Sharp Grossmont be decertified? The CMS threat to withhold funding is likely just a bluff.

“Among the 450 hospitals in [CMS certification officer Steven] Chickering’s jurisdiction of Hawaii, California, Nevada and Arizona, 10 to 12 a year have as many major lapses, he said. Ninety-nine percent of those facilities resolve their crises and keep their federal payments, Chickering said.”

The federal government knows that removing funding from the only emergency room in a 750 square mile area is not politically feasible. Although individuals may not have much choice of a hospital in an emergency situation, in non-emergency situations patients can decide to drive longer distances to visit physicians at more competent hospitals. If CMS payments are proportional to patient volume, then Sharp Grossmont may take a financial hit due to this lower patient volume without having the hospital decertified.

Decertification is likely not the answer, but having such serious quality lapses reflects poorly on the state of health care in San Diego, and in the U.S. in general.

• Additional information on Sharp Grossmont’s predicament can be found at KPBS’s the Editors Roundtable.

NPR’s Morning Edition reports on what happened when health economist Philip Musgrove brought a dying man to an emergency room.  The receptionist with whom Dr. Musgrove interacted would not treat a the man until his health insurance information was collected.

The New York Times reports (“Doctor and Patient, Now at Odds“) that the doctor-patient relationship is suffering. Patients no longer place absolute trust in their doctor for a variety of reasons. On the physician side, patients know that doctors are pressured by insurance companies reimbursement mechanisms to have shorter office visits. Reports from the media on medical errors and physician kickbacks from drug companies are not helping either. On the patient side, the internet has opened up a vast new store of easily accessible information on diseases and communication with other patients who have the same disease. The prescience of Dr. Rich’s foretold of “the loss of this doctor-patient relationship” in his book, Fixing American Healthcare.

Hat tip: Dr. Jay Parkinson

According to U.S. Census projections, the number of individuals 65 and older will increase from 12.4% of the populations in 2000 to 20.7% of the population in 2050. With the expected incredible rise in the number of elderly in the U.S., one would expect a concurrent rise in the number of geriatricians.

NPR’s Marketplace, however, reports that there are too few geriatricians. Currently there are only 7000 geriatricians, a 22 percent decline eight years ago. Why isn’t the increased demand for geriatricians–due to the aging popualation–causing more medical student to choose to specialize in geriatircs?

Brandeis professor Dr. Stuart Altman reveals the reason: the insurance system is biased against doctors–like geriatricians–who concentrate on preventive medicine. “The way the health system pays the workers in it, it has a very strong bias in favor of high-tech services, highly specialized services and primarily services for acute care.” Time-intestive, non-procedure based primary care is not as highly compensated. In fact, geriatricians make a quarter to a third less than other specialists.

Some physicians who focus on primary care, however, are discovering that concierge practices give physicians more time to spend with patients and can be more lucrative as well. In my hometown of Milwaukee, Froedtert is opening its own concierge clinic.

The Boston Globe reports that some of Massachusetts largest insurers are beginning to cover medical visits made at retail clinics at CVS and Walgreens drug stores.  Blue Cross/Blue Shield of Minnesota is waiving copays for visits to retail clinics.  The American Association of Family Physicians (AAFP) is not happy about this.

Carpe Diem says the AAFP’s resistance to accept retail clinics can be understood follows: “The family doc cartel is worried about increased competition.”

Primary care physicians can be compensated in a number of ways. The most popular are capitation, fee-for-service, salary, or some mixture of the three. But how does the physician compensation method affect care levels? This is the question Gosden et al. (2000) try to answer in their Cochrane review. The authors search the literature for randomized trials or controlled before and after studies in order to see how changing physician compensation affects the quantity and quality of care.

A summary of the 4 papers which met Gosden et al.’s criteria is below.

The original four articles:

• Stephen M. Davidson, Larry M. Manheim, Mina M. Hohlen, Stephen M. Werner, Beth K. Yudkowsky, and Gretchen V. Fleming, “Prepayment with Office-Based Physicians in Publicly Funded Programs: Results from the Children’s Medicaid Program” PEDIATRICS Vol. 89 No. 4 April 1992, pp. 761-767.
• Gerald B. Hickson, William A. Altemeier, and James M. Perrin “Physician Reimbursement by Salary or Fee-for-Service: Effect on Physician Practice Behavior in a Randomized Prospective Study ” PEDIATRICS Vol. 80 No. 3 September 1987, pp. 344-350.
• B. Hutchison, S. Birch, J. Hurley, J. Lomas and F. Stratford-Devai (1996) “Do physician-payment mechanisms affect hospital utilization? A study of Health Service Organizations in Ontario” Canadian Medical Association Journal, Vol 154, Issue 5 653-661.
• A Krasnik, P P Groenewegen, P A Pedersen, P von Scholten, G Mooney, A Gottschau, H A Flierman, and M T Damsgaard “Changing remuneration systems: effects on activity in general practice.” BMJ. 1990 June 30; 300(6741): 1698–1701.

A recent paper by Kitchener et al. (HSR 2008) investigates the actions of one nursing home chain to find how they maximized their profits. The authors find that Sun Healthcare Inc. employed three strategies to maximize shareholder value:

1. rapid growth through debt-financed mergers;
2. labor cost constraint through low nurse staffing levels; and
3. a model of corporate governance that views sanctions for fraud and poor quality as a cost of business.

Should the government impose a minimum nurse/patient ratio in order that quality care continues?

Most libertarians abhor almost any form of regulation, but the case of the nursing homes may be an exception. The “customers” of nursing home care are elderly patients who–by definition–are in some way not able to take care of themselves. Thus, if the patient is treated poorly, it may be nearly impossible for them to change facilities or often it is even difficult for the elderly individual to communicate to their relatives that their care level is poor. The Kitchener paper found that one nursing home chain is sacrificing quality by using low nursing staffing level; should the government mandate a minimum nursing staffing level for nursing homes?

I would argue that they should not. While nurses are of course one of the most–if not the most–important input which affects the quality of nursing home care, regulating inputs is not ideal. This regulation will likely stifle innovation. If new technologies are developed–such as a digital scale monitoring device mentioned in Akshay Kapur’s blog–it may be possible to substitute capital (technology) for labor (nurses) and achieve better medical care for lower costs.

Should nursing homes be exempt from regulation? On this point, I believe that there should be some regulation. The government must continue to monitor nursing home quality and register complaints. Nursing homes with low quality scores or who abuse patients should not receive Medicare or Medicaid patients.

It is important for the government to play a role in helping those who cannot help themselves; yet the government should not mandate how nursing homes should run their business, but instead insure that some minimum quality of care threshold is met.

• Martin Kitchener, Janis O’Meara, Ab Brody, Hyang Yuol Lee, Charlene Harrington (2008) “Shareholder Value and the Performance of a Large Nursing Home Chain” Health Services Research, Volume 43 Issue 3 Page 1062-1084.

The controversy as to how much Medicare should pay doctors is continuing to brew (see N.Y. Times article).  Congress passed a law overriding a pay cut to Medicare doctors.  Although the president vetoed the bill, Congress garnered enough support to override the veto.

Dr. Rich of The Covert Rationing Blog claims that the Medicare reimbursement mechanism “is so fundamentally ridiculous that it can only be understood by recognizing that it is a fairly typical bureaucratic attempt to covertly ration healthcare.”

How would you enjoy having legislators determine your salary?

Most people believe that vaccines are for kids. The CDC and public health departments have done a good job of keeping vaccination rates high for children. With the advent of new vaccines for adults, the key now is to increase vaccination rates for these older groups.

The Wall Street Journal (“Get your shots“) details a few of the vaccines that adults should receive.

Not included in the list is the HPV vaccine against cervical cancer.

Another point of interest is that it is increasingly difficult for physicians to supply vaccines to patients. With so many vaccines, the logistics of ordering all these perishable vaccines is very difficult. Further, as vaccines costs have increased, physicians will have to invest more and more capital into vaccine inventory.

For this reason, alternative providers such as pharmacies may a solution. With a vast experience in storage of drugs and supply chain management, pharmacies can easily absorbed the increased adult vaccine demand.

In the Wall Street Journal article, we have the following story:

The doctor didn’t have the shingles vaccine in stock, and recommended they try a walk-in clinic at a nearby drugstore, where the nurse practitioner provided a two-page handout on the vaccine and answered some of their questions. Though the price was about $219 each, all but $40 was covered by their drug benefit plan.

The next time you get a shot, it may be at your local CVS or Walgreens and not at the doctor’s office.

There is an interesting article a few weeks back in the Wall Street Journal (“Opting Out“) which describes the plight of Amish and Old Order Mennonites who refuse to buy health insurance. Further, since these groups also refuse to participate in Medicaid government assistance will not bail them out either.

Nevertheless, these societies do have one form of insurance: mutual aid. When one member of the community becomes ill, the rest will pitch in to help finance the cost of the needed medical care. “Thousands of Amish families rely on the age-old system of churches paying bills members can’t afford, through voluntary donations.”

Because they are very closed societies, however, many Amish and Old Order Mennonite individuals marry distant cousins which can lead to a handful of genetic diseases. With such a high rate of expensive-to-treat diseases, this mutual aid system is faltering.

Further, since the Amish and Mennonite are uninsured, they actually pay more for medical care than would someone with private or public health insurance. This phenomenon was documented in my “Uncompensated Care” post.

What is the solution?

The Amish hope to persuade their local hospital to lower medical costs, but it is unlikely that a hospital will negotiate a lower rate for uninsured Amish compared to the uninsured non-Amish. The local Lancaster General hospital “…has increased its discount for uninsured patients to 25% from 15%…uninsured patients now receive the same discount that commercial insurers do, though not as much as the government does.”

The moral of the story is that it is very difficult to receive medical care in America today without health insurance.

• H.T.: Chronic Positivity
• H.T.: Lancaster Online “Faith not paying bills“

A Side note: If everyone receives at least a 25% discount, isn’t that just the regular price?

Can technological change make people worse off? Most economists think technical improvements are always good. Producing more of the output with fewer input is considered a more efficient use of resources. But is this the case in the medical field? John Goddeeris shows that this may not always be the case in his 1984 paper.

The Model

Let us assume that individuals maximize utility of the for developed by Arrow (1976):

• V=Σ_i p_i uⁱ(x_i, h_i(m_i))

Here, i indexes the state of illness, where the probability that each stat of illness occurs is p_i. Individuals can spend their income on consumer goods, x_i, or medical care, m_i, where medical care is translated into health by the function h_i(m_i). A technological advancement is defined as h_i^a(m_i)≥h_i^b(m_i), for all m_i, and strict inequality for some m_i.

We can now introduce insurance into the model. Individuals who buy insurance pay a premium equal to π and a coinsurance rate z. The price of the medical premium must be equal to the expected value that the insurance company expects to pay out in medical benefits (less the copayments).

One would think that V*_a>V*_b, but this may not always be the case. For instance, let us assume that a person can either be healthy or sick (i.e., i=2). Further, assume the following utility functions:

• V=(1-p)u¹(x₁) + p u²(x₂,h₂)
• u¹(x₁) = -exp[-x₁]
• u²(x₂,h₂) = -exp[-(x₂+h₂)]

If individuals are endowed with income x₀, then:

• x₁ = x₀ – π,
• x₂ = x₀ – π – zm₂,
• π = p(1-z)m₂.

Assume p=.1, x₀=10 and the original technology is:

• h₂(m₂) = -10 if m₂ < 5
• h₂(m₂) = -4 if m₂ > 5

This means that if medical spending is above 5, health will be partially restored. Goddeeris finds that the optimal coinsurance rate to maximize utility is no coinsurance (i.e., z=0). With no coinsurance, sick individuals choose m₂=5. The utility level under the original technology (i.e., V*_b) equals -.000476. What happens when there is a positive technological changes as follows:

• h₂(m₂) = -10 if m₂ < 5
• h₂(m₂) = -4 if 5 ≤ m₂ <15
• h₂(m₂) = -3 if m₂ > 15

Again, the author finds that no coinsurance (i.e., z=0) is optimal. With no coinsurance, individuals of course choose m₂ = 15. However , tutility level under the new technology (i.e., V*_a) equals -.000592. How can this technological improvement have decreased utility?

In this example, the true cost of the innovation is so large relative to its benefits are so large, people only choose to use it since coinsurance is 0. A higher coinsurance rate would have induced individuals to choose m₂ = 5. According to Goddeeris, “the larger added expenditures in the ill state leads to an even greater reduction in expected utility. A ero co-insurance rate remains optimal after the innovation. Thus V*_a < V*_b, and the innovation –which clearly expands productive capabiities and is in fact adopted–is welfare reducing by our standard.”

The reason this occurs, is that individuals act ex post as if their expenditure decisions have no impact on insurance premiums. While no individual person’s actions will affect insurance rates, since all sick individuals act similarly, health insurance premiums increase much more after the technological innovation than before it.

Despite the finding that technology is welfare reducing in this particular case, technological improvement are of course welfare improving in other cases. One question that remains is how to operationally decide when a technology is welfare enhancing and when is it welfare reducing. In which category do MRI machines fall? What about CT scanners?

• Goddeeris, John H. (1984) “Medical Insurance, Technological Change and Welfare” Economic Inquiry, 22(1): 56-67.
• Goddeeris, John H. (1984) “Insurance and Incentives for Innovation in Medical Care” Southern Economic Journal, Vol. 51, No. 2, pp. 530-539.
• Arrow (1976) “Welfare Analysis of Changes in Health Coinsurance Rates” NBER.

According to a report by the The Colorado Health Institute, 68 percent of rural and 74 percent of urban dentists do not accept Medicaid patients.  Even for those dentists who do accept Medicaid, many are not accepting new Medicaid patients.  The full report is available here.

The N.Y. Times reports (“Concerned about costs…“) that Congress is trying to impose new restrictions on physician-owned, for-profit hospitals. The legislators fear that these hospitals 1) drive up costs and 2) provide poor quality.

Legislators worry that when physicians own the hospital, they may have more of an incentive to order more procedures to increase their profits. If this is true, I am not sure that physician owned hospitals are the problem, it may be the case that Medicare or insurance companies need to change how they compensate physicians in these hospitals.

The second case is also of dubious merit. It was shown in a previous post that ambulatory surgery centers and hospital outpatient departments have similar quality levels. It is true that ambulatory surgery centers generally have a healthier patient base, but treating healthier patients in a lower cost setting is not necessarily a bad thing. It is true that many of these physician-owned hospitals not equipped to handle complications requiring emergency care, but if the complications are lower, then the cost savings may be worth not having the emergency care equipment.

Of course, not all physician-owned hospitals will be subject to these new restrictions. Lobbyists have convinced politicians that facilities such as Aurora BayCare Medical Center in Green Bay, Wisconsin and Wenatchee Valley Medical Center in Wenatchee, Washington should be exempt from these restrictions.

Michael C. Burgess a Texas Republican and an obstetrician-gynecologist states that “This is a free country…If you want to invest in a hospital, if you are willing to put personal capital at risk, you should not be forbidden to do so just because you are a doctor.”

When you are sick and need a doctor, you need hope that you are given the best care possible. Most people assume that doctors will tailor their treatments to the individual patient needs. However, a paper by Frank and Zeckhauser (JHE 2007) explain that this may not be the case. The authors claim that there are four costs which may preclude physicians customizing treatments to individual patients.

• Communication costs: Whenever a physician prescribes a treatment outside of standard protocol, they will have to explain why they are doing this to the patient and this takes time. With patients armed with more information from direct-to-consumer advertising and the internet, communication costs have increased over time.
• Cognition costs: The authors claim that using brain power (cognition) has costs and there may be increasing marginal costs of cognition use. Thus, physicians may use heuristics to simplify the decision-making process.
• Coordination costs: As more and more physicians specialize, communication between physicians is increasingly important. Using standardized, less customized medical treatments makes communication between physicians regarding patient treatment much easier.
• Capability costs: Some doctors are trained to perform certain techniques. If a superior technique is developed, the physician may still decide to use the “old” technique since they have mastered the “old” technique and do not know how to preform the new, superior technique.

It is likely that customization of treatment varies significantly by treatment. For instance, in my “Operating on Commission” paper I find significant differences in surgery rates based on how physicians are compensated by insurance companies. Since this is a significant medical and financial decision by the doctor, one would expect there to be more customization than in other areas, since the benefits to surgery are so large relative to the costs outlined above.

The authors ennumerate how customization will vary accross patients as follows:

1. little is known about a patient and their responsiveness to various treatments
2. treatment is expected to be short-lived
3. there is little difference in the impact of different treatments on patients

On the other hand, Grand and Zeckhauser look at whether or not there is “norm-following behavior” in the length of office visits and physician prescribing behavior. They use data from the 2004 NAMCS and the Quality Improvement in Depression study. They find that physicians do customize treatment more for chronically ill patients than for patients with acute illnesses. Physicians do tend to spend more time in office visits with new patients, but the time spent with the patients does not vary by illness type or severity. Thus, the administrative and communication costs that new patients impose and not medical necessity seem to be dictating how the length of a visit varies. These results are similar to the ones found in Glied and Zivin (2002).

Thus, the authors conclude that some customization of prescribing practices and prescribing behavior does occur, but this behavior is not based on clinical factors.

• Frank RG, Zeckhauser RJ, (2007) “Custom-made versus ready-to-wear treatments: Behavioral propensities in physicians’ choices” Journal of Health Economics, v 26(6): 1101-1127.

How much care should doctors give to terminally ill patients in the ICU? This is a question which can be answered on many levels (e.g., societal, individual, technical). One physician gives his thoughts in an n+1 magazine article titled “First, do no harm.”

While advanced medical technology has lead to greater longevity and healthier lives, scientific advances are not always easily applicable to the ICU.

Well-conducted studies of medical interventions test a medically homogeneous population by manipulating one aspect of their care. ICU patients are so sick, in such diverse and unique combinations of ways, that there is shockingly little sound information on whether or how much the interventions we can offer will help. And so a day seldom passes on rounds without us standing around scratching our heads about what to do next. Dialysis? Could work. Twelve-thousand-dollar-a-day drug that is “effective,” at least temporarily, in 10 percent of cases? Let’s give it a shot.

Many of these patients would actually prefer less invasive treatment. The most important features of medical care for patients with chronic diseases are: being kept clean, maintaining their dignity, trusting their physician, and being free of pain. “Only 48 percent of patients felt it was important to ‘use all available treatments, no matter what the chance of recovery.’”

If the relative is not able to voice their own opinion (e.g., if they are unconscious), a relative often decides how much care the patient receives. In order to avoid the guilt burden of giving up on their loved one, many relatives will ask for the most intensive treatment possible. Since insurance companies often bear the full costs of these decisions, relatives are not hesitant to order as much treatment as possible.

Physicians often preform unnecessary intensive procedures for fear of malpractice lawsuits or “fear of withholding care in one of the rare cases when last-ditch efforts grant a patient extra months or years of quality life.”

Thus, we are left with lots of doctors flogging patients. In the words of the author, flogging is “slang term we use for performing these procedures on people unlikely to benefit from them.”

Many studies have attempted to determine how the manner in which physicians are compensated by health insurance companies affects the quantity of medical care provided. Today I will summarize some seminal studies in this field.

Epstein, Begg and McNeil (NEJM 1986)

In this study, the authors examine whether or not there is a difference in the rate of ambulatory testing between physicians in a large fee-for-service (FFS) group and a large prepaid group. The physicians were internists who were caring for patients with uncomplicated hypertension. The authors found that 50% more electrocadriograms (EKGs) were obtained in the FFS group and 40% more chest radiographs were obtained in the FFS group [compared to the prepaid group]. There did not seem to be any difference in testing rates between FFS and prepaid doctors for blood counts and urinalyses. This is not surprising, however, because the profit physicians earned from EKGs and chest radiographs was significantly higher than the profit they made from each blood count or urinalysis. Further, the cost of preforming EKGs and chest radiographs was much higher than the cost to preform blood counts and urinalyses.

Thus, this study concludes that patient testing rates are different between FFS and prepaid doctors, but this effect is only observed for high cost and/or high margin ambulatory tests.

Newhouse and Marquis (JHR 1978)

Physicians may treat patients differently based on how the patient’s insurance company pays them. However, the patient base of most physicians includes a wide variety of health plans and thus it may be difficult to discriminate care levels by insurance type. The “norms hypothesis” predicts that physicians treat patients in accordance with the average or modal insurance coverage in a given metropolitan area. In other words, “the level of a community’s insurance coverage determines physician norms.” If this were true, it would imply that there would be significant variation in medical care quantities across geographic regions but very little variations by patient for each physician.

The authors use data from the RAND Health Insurance Study in Dayton, Ohio. The authors test whether or not the patients own insurance rate will affect hospital admissions, the length of a hospital stay or the number of physician office visits. The authors find no evidence that community-level coinsurance rate impact hospital admissions, while the patient’s own coinsurance rate significantly affects hospital admission. In the 1963 data, neither the community insurance variable nor individual insurance variable had any affect on the length of a hospital stay or the number of physician visits, however in the 1970 data, individual coinsurance rates had a large impact on the length of a hospital stay or the number of physician visits, while the community level coinsurance rate had no impact on these dependent variables.

Hellerstein (RAND J Econ 1998)

Most health policy wonks believe we could significantly reduce health care costs without sacrificing quality by using more generic drugs. Many states have passed “permissive substitution laws” which allow pharmacists to substitute generic drugs in place of name-brand ones unless the physician explicitly instructs them not to do so. Other states use a “two-line” prescription method. With these prescription pads, doctors can sign their name in one of two spots: the first indicates that generic substitution is allowed and the other indicates that the brand name option is medically necessary.

Hellerstein uses data from the 1989 NAMCS, and finds that “30% of the unobserved (residual) variance in the prescription choice is physician-specific, rather than patient specific.” Does an individual’s health insurance influence the physician’s prescribing behavior? This paper finds that an individual’s health insurance does not influence prescribing decisions. However, “conditional on a patient’s insurance status, a patient who switches to a physician with a marginally greater fraction of HMO patients is 10.12% more likely to receive a generically written prescription.”

Summary

Why does the composition of the physician’s patient base seem to matter for Hellerstein (1998), but not for Marquis and Newhouse (1978) or Epstein, Begg and McNeil (NEJM 1986)? The main reason is likely that Hellerstein examines medical care in which physician do not receive any compensation. Physicians receive no more or less revenue from prescribing name brand compared to generic drugs and thus have no incentive to find out how they are being paid by each individual’s insurance company. On the other hand, Marquis and Newhouse found that hospital admissions, the length of the hospital stay, and the number of office visits is affected by an indvidiual’s health insurance variables since this type of medical care is high margin and high cost. Similarly, Epstein, Begg and McNeil (1986) found that how an individual’s insurance company compensates physicians matters for high margin, high cost EKGs and chest radiographs, but does not seem to matter for low margin, low cost blood counts and urinalyses.

• Epstein AM, Begg CB, McNeil BJ. (1986) “The use of ambulatory testing in prepaid and fee-for-service group practices: Relation to perceived profitability.” N Engl J Med. 314(17):1089-94.
• Newhouse JP, Marquis MS. (1978) “The norms hypothesis and the demand for medical care.” J Hum Resour. 13 Suppl:159-82.
• Judith K. Hellerstein (1998) “The Importance of the Physician in the Generic versus Trade-Name Prescription Decision,” The RAND Journal of Economics, Vol. 29, No. 1, pp. 108-136 .

Many patients have an idealized view that physicians customize their treatments for each individual patient.  For instance, do physicians tailor prescription dosage based on individual characteristics and responses over time, or will they simple prescribe the standard dosage?

A paper by Frank and Zeckhuaser (JHE 2007) find that norm-following behavior (rather than patient-by-patient customization) is very prevalent.  The authors claim that there are 4 reasons why a physician would strictly adhere to a professional norm rather than customizing their treatments to maximize the quality of care for each individual patient.

1. Communication costs. In order to prescribe treatment outside of the norm, the physician must communicate their reasons for doing this to the patient.  If patients have preconceived notions of how they want to be treated, physicians may have to expend significant effort to convince the patient that this individualized treatment is the best way to proceed.
2. Cognition costs. As every person knows, exerting mental effort is costly.  Physicians can cut down on the cost of diagnosis by using heuristics.  These shortcuts may not be optimal for every patient, but they generally “do a reasonable job for a broad array of cases” and also cut down on the physicians mental computing costs.
3. Coordination costs.  Physicians often have to work with other physicians.  The more physicians customize their treatment, the more difficult it is to communicate this alteration in care levels with specialists and thus more difficult to coordinate care.
4. Capability costs.  Physicians are trained in certain treatments.  If a new, better treatment comes along, the physician has a choice of either 1) doing the old treatment, 2) learning the new treatment poorly and performing the new treatment, or 3) learning the new treatment well and performing the new treatment.  Choice (3) may be optimal from the patient’s point of view, but for the physician it may involve significant fixed costs involved in acquiring the human capital necessary to preform the new procedure.  If the physician decides not to incur the cost to learn the new technique well, it may in fact be optimal to choose option (1) over option (2) and thus old techniques will persist.

While these four costs will push physicians towards following norms, superior patient outcomes may compel doctors to customize their care.

Results

Frank and Zeckhuaser use data from the 2004 NAMCS to determine whether or not physicians customize the length of the patient visit or prescribing behavior.  The authors find that customization in prescribing behavior occurs most frequently for patients with chronic conditions.  This is likely because altering the “standard” treatment has more benefit for ‘repeat-visit’ patients than those with simply an acute illness.  However, race, gender, number of physician visits and insurance type do not affect prescribing behavior.

Regarding length of the office visit, the most important factor is whether or not the patient is a new patient.  Individuals who were self-pay had shorter visits while those with had Medicare insurance had longer visits, but these results were fairly small in magnitude.  Twenty-eight percent of the differences in the length of an office visit was due to physician specific factors.

Overall, the evidence shows that physicians often follow norms rather than customize care.  Also, it seems that the manner in which physicians are paid has no bearing on how they treat patients.  However, this is likely due to the fact that 1) it is very difficult to customize visit length especially when physicians are dealing with eleven managed care contracts on average [see other evidence in "Time Allocation" post on Tai-Seale et al. (2007) or the "Doctors Behave" post on Glied and Zivin (2002)], and 2) physicians do not receive compensation for pharmaceuticals and thus have no financial incentive to tailor treatment to patients based on their individual insurance.

My “Operating on Commission” paper does find that physicians tailor surgery treatment based on how they are compensated, but this is likely because 1) these are high margin procedures where it is worth the physicians time to find out how they are being paid, and 2) unlike pharmaceuticals, the surgeon is the one who receives the compensation directly.

• Richard G. Frank and Richard J. Zeckhauser (2007) “Custom-made versus ready-to-wear treatments: Behavioral propensities in physicians’ choices” Journal of Health Economics, Volume 26, Issue 6, Pages 1101-1127.
• Tai-Seale M, McGuire TG, Zhang, W (2007) “Time Allocation in Primary Care Office Visits” HSR vol 42(5), pp. 1871-1894.
• Sherry Glied and Joshua Graff Zivin (2002) “How do doctors behave when some (but not all) of their patients are in managed care?” Journal of Health Economics, Volume 21, Issue 2, Pages 337-353.

The Economist (“Doctor on Call“) has an shows that mobile phones may have another use for doctors: a microscope.

“Mr Maamari is a member of a research team led by Dan Fletcher, a professor of bioengineering at the University of California, Berkeley, which has developed a cheap attachment to turn the digital camera on many of today’s mobile phones into a microscope. Called a CellScope, it can show individual white and red blood cells, which means that with the correct stain it can be used to identify the parasite that causes malaria. Moreover, by transmitting an image directly over the mobile network, the CellScope could greatly help with the remote diagnosis and monitoring of many illnesses.“

As the cost for health care has continued to rise, many Americans have looked for less expensive treatments in foreign countries. Living in San Diego, I can attest that many Southern Californians head to Tijuana to have their prescriptions filled. A Minot Daily News article (“Medical onshoring…“) claims that “more than 150,000 Americans traveled abroad for health care in 2006.” The article continues to state that Blue Cross and Blue Shield of South Carolina has formed affiliations with health care facilities in Thailand, Turkey, Ireland, Costa Rica and Singapore. Can anyone get affordable health care in the U.S?

The answer may be yes…on American Indian sovereign lands. C.A. Chien is proposing a Medical Onshoring project (see his Medical Onshoring blog). Health workers from foreign countries can be hired for lower wages and will not be subject to U.S. medical restrictions while they are on American Indian sovereign lands.

One wonders if the quality of care will suffer? Chien states that all his facilities “…will be accredited at JCI levels, equal to those in Japan, Singapore, Thailand, India, Europe, or the U.K.” In the Minot Daily article, Chien continues argues that “…his system and its proprietary technology could reduce U.S. health-care costs by at least 15 percent.”

Although the impact of this model may be limited to those who are living in areas near American Indian lands, I am in favor of any innovation which could lower costs while maintaining quality.

Many doctors claim that the medical malpractice system is broken and needs to be fixed. Doctors have high malpractice insurance premiums and often practice defensive medicine to protect themselves against lawsuits. To help alleviate this problem, many politicians have asked for some sort of tort reform. Tort reform can be generally categorized into 4 types of legal changes:

1. Caps on noneconomic damages. Noneconomic damages cover items other than monetary losses, such as pain and suffering.
2. Caps on punitive damages. Punitive damages are awarded in addition to compensatory (economic and noneconomic) damages in order to punish defendants for willful and wanton conduct.
3. Modifications of collateral-source rule. Under the common-law collateral source rule (CSR), amounts that a plaintiff receives from sources other than the defendant (e.g., from his or her own insurance) may not be admitted as evidence in a trial.
4. Modifications of the joint-and-several liability (JSL) rule. In a trial with more than one defendant, the first step is to apportion blame for the harm. Under JSL, the plaintiff can then ask the “deep pockets” defendant to pay all of the damages, even if that defendant was responsible for only a small fraction of the harm. Modifications to the JSL rule often hold that the “Deep pockets” defendant must be at least 50% liable for the harm in order to be held 100% responsible for the damages.

Which of these reforms are helpful? A paper by Currie and MacLeod (QJE 2008) aims to answer this question. The authors look at variation in tort laws across states between 1989 and 2001. They claim that malpractice laws put doctors more at risk for a lawsuit is a good thing because it will cause them to behave more carefully. When doctors fear expensive lawsuits or a blow to their reputation, they may behave with more caution. Thus, capping punitive and non-economic damages should decrease caution. On the other hand the JSL rule puts doctors more at risk. They will not be protected from a suit simply be associating with a deep pockets hospital.

Empirical Results

To test this, the authors look at the number of Caesarean sections performed and the rate of induction or stimulation of labor. C-sections are popular with doctors because they receive additional compensation compared to a “regular” birth. However, performing a C-section on a mother who does not need it exposes them to additional risks. The authors find that “JSL reform reduces C-sections and complications of labor and delivery…In contrast, caps on damages are found to increase procedure use, and hence costs. They also increase complications of labor and delivery in some specifications.”

For a robustness check, the authors look at C-section rates for high- and low-risk babies separately. The authors assume that doctors have less treatment discretion for high risk cases, and the results demonstrate that tort reform had less of an effect on procedure rates or outcomes for high risk cases.

• Currie, Janet; MacLeod, W Bentley (2008). “First do no harm? Tort reform and birth outcomes” Quarterly Journal of Economics, v 123(2): 795-830.

Traditional economic theory suggests that when the price of a good falls, the amount supplied will fall as well. Most economists always assume that the supply curve is upward sloping.

But that is not always the case in medical world. Because a physician serves both as the patient’s advisor and the supplier of medical treatment, physicians can induce patients to increase the amount of medical care they wish to receive. Patients are easily convinced because of 2 market failures: asymmetric information and moral hazard.

Asymmetric information means that the physician know more about your health condition than you do. Thus, patients rely on the advice of the physician. Moral hazard occurs because patients have health insurance. Since patients do not pay for the care they receive (or pay for it at a reduced rate), they are very amenable to follow the doctors orders.

A 1998 letter from the Health Care Financing Administration (HCFA) found that it was typical that a 50% offset will occur when Medicare payments are reduced. This means that a 20% reduction in price, will lead to a 12.5% increase in quantity. Overall, this will lead to only a 10% decrease in total cost. Since 10% is 1/2 of 20%, we have a 50% offset. Physicians are increasing the quantity provided in order to make up for the income lost from lower Medicare reimbursement rates.

This is a classic example of supplier induced demand.

An article by Yip (JHE 1998) found that this was the case for coronary artery bypass graft (CABG) surgeries as well.

• Winnie C. Yip, 1998. “Physician response to Medicare fee reductions: changes in the volume of coronary artery bypass graft (CABG) surgeries in the Medicare and private sectors.” Journal of Health Economics, Volume 17, Issue 6, December 1998, Pages 675-699

Simon Caulkin, management editor of The Guardian, has a great article titled “The rule is simple: be careful what you measure.”  The article discusses the fact that measuring performance leads to better performance on the dimensions measured, but can often lead to significantly worse performance on the unmeasured dimensions.  For instance,

What happens when bad measures drive out good is strikingly described in an article in the current Economic Journal. Investigating the effects of competition in the NHS, Carol Propper and her colleagues made an extraordinary discovery. Under competition, hospitals improved their patient waiting times. At the same time, the death-rate following emergency heart-attack admissions substantially increased. Why? As targets, waiting times were and are measured (and what gets measured gets managed, right?). Emergency heart-attack deaths were not tracked and therefore not managed. Even though no one would argue that the trade-off – shorter waiting times but more deaths – was anything but a travesty of NHS purpose, that’s what the choice of measure produced.

Hat tip to DB’s Medical Rants for this one.

The Retired Doc’s Thoughts has an interesting post as well.

“When regulators or policy makers succeed in improving the quality of care provided by some doctors, do patients even notice and/or care?” This is the question which Kenneth L. Leonard attempts to answer. Davies and Ware (1988) do state that patient satisfaction is correlated with average quality levels. One problem with most studies is that quality improvements take place over a long period of time. It is possible that as quality improves, patient expectations also increase and thus overall reported patient satisfaction may be unaffected.

How does a researcher get an exogenous change in quality? Leonard uses the Hawthorne Effect. The Hawthorne effect states that quality will improve whenever there is a change in environment. In this study, doctors are observed by researchers. The study finds that objective measures of quality improve immediately after researchers arrive, but the quality improvement slowly decays over time until after about 10 observations, the doctor returns to their original quality level.

So, do patients actually notice this quality improvement? Leonard find that:

“Patient do, in fact, recognize and value quality care. A 1% increase in protocol adherence (from an average adherence of about 53%) is associated with about a 0.40% increase in the probability that a patient will declare the consultation to have been “very good” (from an average level of about 12%).”

• KL Leonard (2008) “Is patient satisfaction sensitive to changes in the quality of care? An exploitation of the Hawthorne effect” Journal of Health Economics, 27(2): 444-459.
• A. Davies and J.J. Ware (1988). “Involving consumers in quality of care assessment, Health Affairs” 7, pp. 33–48.

Paul Levy, the president and CEO of Beth Israel Deaconess Medical Center in Boston made about $1 million dollars in 2005. Of this, $650,000 was base salary, $195,000 was made up of incentive bonus, and the balance was composed of compensation for health insurance, life insurance, and retirement.

How do I know these figures? Paul Levy told me. Well, he didn’t tell me directly, but he did post these figures on his Running a Hospital blog. Levy writes:

So, if you were on my board, how would you set an appropriate salary? You might look at the competition, and as the Globe notes, the salaries for most of the Boston-area hospital CEOs center around the same level. Would you look at salaries of people in for-profit companies, and, if so, how do you measure comparable size and complexity? Would you look at salaries of other types of non-profits, like universities and museums?

Does it matter that the average tenure of a hospital CEO is under six years? If that is roughly the tenure of a major league baseball player, should CEO salaries be in the same ballpark? Sorry, I couldn’t resist!

The New York Times recently posted an interactive page on executive pay. So the question remains, readers, how would you set Paul Levy’s salary?

An Annals of Internal Medicine survey sheds some light on physicians opinions regarding universal health care. Overall 59% of physicians support national health insurance and 32% oppose it. Support for national health insurance increased 10 percentage points since 2002 (49%). Unsurprisingly, surgical subspecialties, anesthesiologists, and radiologists, were the only specialities where more than half of respondents did not support universal health care.

Any economist would not be surprised by these findings. Primary care is not highly compensated now and universal health care would likely not alter this. Further, primary care would likely simplify the world of primary care: there would either be one insurance company (as in the case of government provided care), or it would likely be clearer which treatments would be covered. Further, since there would be no uninsured, the primary care doctors would not have to provide any uncompensated care.

For specialists, however, it is likely that national health insurance will reduce compensation for physicians. Some procedures may not be covered, or will be reimbursed at lower rates. More referral restrictions and likely rationing of care would lead to lower profits for specialists.

Even physicians are divided about whether or not national health insurance is a good idea.

GoozNews has more information on the article.

A recent article in the Journal of Health Economics found that increasing Medicare reimbursement may have no meaningful effect on hospital use or patient outcomes.

“There is widespread concern about the quality of health care in the US, and the effect of provider payments on the quality of care is an important and unsettled issue in this debate. The critical question is whether changes in provider payments affect health. To date there is relatively little research on this question. Here, we present evidence of the effect of plausibly exogenous changes in Medicare reimbursement – caused by geographical reclassification – on hospital staffing (nurses) and patient outcomes. We find that changes in Medicare reimbursement levels of approximately 10% have no meaningful effect on hospital use of resources or patient outcomes.“ 

• R Kaestner, J Guardado, 2008. “Medicare reimbursement, nurse staffing, and patient outcomes” Journal of Health Economics, 27(2): 339-361.

David Williams of the Health Business Blog reviews an article from the Boston Globe (“Immigrants…“)  stating that immigrants reduce the cost of health care.  How can this be with so many immigrants relying on government programs and free clinics to receive their care?

While it is true that immigrants are consumers of medical care, they are also producers as well.  A study of the health care workforce in Massachusetts finds that 40% of pharmacists, 28% of physician assistants, 22% of opticians, 21% of licensed practical and vocational nurses, 17% of dentists and 14% of paramedics are foreign born workers.  Twenty-eight percent of physicians and surgeons are foreign born.

An increased supply of health care workers from foreign countries can help decrease labor costs for medical care.

The N.Y. Times (“…No Rhyme or Reason“) has an interesting essay about how doctors financial incentives pressure them to run too many tests on patients and refer them to too many specialists.

Doctors are usually reimbursed for whatever they bill. As reimbursement rates have declined in recent years, most doctors have adapted by increasing the quantity of services. If you cut the amount of air you take in per breath, the only way to maintain ventilation is to breathe faster.

The Healthcare Economist believes that money matters in medical matters.  My research regarding specialist compensation shows that financial compensation has a huge impact on surgery rates.

Musing on the modern propensity for physicians to overtreat their patients, one hospital executive said:

“The hospital is a great place to be when you are sick…[b]ut I don’t want my mother in here five minutes longer than she needs to be.”

Most public health officials believe that increasing the supply of primary care doctors is almost always a good thing, while increasing the number of specialists can have mixed results. One problem is that physician supply is endogenous. One may believe that physicians prefer to locate in wealthier areas. If wealthier people are also healthier, then a correlation will exist between physician supply and health even though no causality exists.

In order to isolate the direct causal effect of increasing family physician supply, Gravelle, Morris and Sutton (2008) use an instrumental methods methodology. The two instruments for physician supply are: an index of local area housing prices and average age-related capitation payments. Since physicians location decisions are regulated by the Medical Practices Committee and do not include a cost-of-living adjustment, we would expect lower physician supply where there housing prices are higher. Local area average capitation payments should not effect any individual’s health, but should attract increased family physician supply.

These instruments are implemented on the Health Survey of England data set. Physician supply comes from the General Medical Services (GMS) Statistics database.

Health levels are either measured as very good, good, fair, bad, or very bad. In this case, an ordered probit regression is used. The authors also utilized the EQ-5D continuous scale health measure. With the continuous variable, a least squares regression model is used. What are the results?

When no instruments are used FPs [family physicians] have a positive but statistically insignificant effect on health. When FP supply is instrumented by age-related capitation it has markedly larger and statistically significant effects. A 10 percent increase in FP supply increases the probability of reporting very good health by 6 percent.

Since almost all medical care and pharmaceuticals are free to patients, increased physician supply will not act to reduce prices. Nevertheless, more family physicians can make going to the doctor more convenient and can reduce waiting times, thus increasing the number of family physician visits per individual per year.

One interesting econometric technique used in this paper is that of the anti-test. A paper by Dranove and Meher (1994) criticizes the use of instrumental variables because the use of some instruments can be used to “prove” that increased physician supply “causes” increased childbirth. This is obviously a nonsensical correlation. In this paper, the authors use instrumented and noninstrumented family physician supply to see these variables have any effect on the individual’s ethnicity. Neither the instrumented or noninstrumented physician supply has any impact on ethnicity. Thus, we have some indication that the two instruments chosen by the authors are valid.

• David Dranove and Paul Wehner, 1994. “Physician-induced demand for childbirths” Journal of Health Economics, v13(1): 61-73.
• Gravelle H, Morris S, Sutton M. 2008. “Are Family Physicians Good for You? Endogenous Doctor Supply and Individual Health.” Health Services Research, Early Online Articles.

Diarrheal disease is a leading cause of childhood mortality in many developing countries. The best treatment when diarrhea strikes is to give the patient Oral Rehydration Solution (ORS). Who provides better care for this disease, public or private providers?

A paper in Health Economics by Waters, Hatt and Black (2008) looks at data from the Living Standards Measurement Surveys (LSMS). This data set draw observations from Latin American and Caribbean countries.

The first item that Waters and co-authors note is that richer household are more likely to see the private physician. “Each additional quintile of household economic status is associated with an increase of 6.5 percentage points in the probability that a child with diarrhoea is taken to a private provider.”

But do these wealthier households receive better care? According to the authors, “treatments provided in the private sector are manifestly of worse quality than in the public sector. A total of 33.0% of children visiting a public provider received Oral Rehydration Solution, compared to 13.7% of those visiting a private provider. Conversely, children treated by a private provider are more likely to receive drugs, most commonly unnecessary antibiotics.”

Private physicians have an incentive to prescribe the more costly antibiotics because they make more money. The publicly financed providers do not have this incentive. The authors claim that prescribing antibiotics may also augment the provider’s reputation with patients. This would be analogous to an American physician preforming an MRI when it is not necessary. The physician makes money on the MRI, the patient believe they are getting high-tech care that is the best in the world, but the MRI may often be a waste of resources.

Winner: Public Providers

• Hugh R. Waters, Laurel E. Hatt, Robert E. Black (2008) “The role of private providers in treating child diarrhoea in Latin America” Health Economics, 17(1): 21-29.

An interesting article (“Sudden Death…“) at the Covert Rationing blog addresses the poor care given to cardiac patients in hospitals. Dr. Rich states that:

“…hospitalized patients who have cardiac arrest (sudden loss of cardiac function due to the onset of a heart arrhythmia known as ventricular fibrillation) are often not receiving defibrillation (an electrical shock delivered to the chest) within the recommended 2-minute window of opportunity. Further, patients whose defibrillation is delayed beyond the 2-minute window have a substantially reduced chance of surviving the cardiac arrest….An accompanying editorial (written by Dr. Leslie Saxon, an old friend of DrRich) points out that in public areas where Automatic External Defibrillators (AEDs) are available, such as casinos, the odds of surviving a cardiac arrest is over 50%. In contrast, the odds of surviving cardiac arrest in a hospital, according to this new study, is only 34%“

Why would this be the case?  Casino’s may have a business interest in saving people’s lives in order to get some good publicity and more consumer loyalty by survivors.  On the other hand, hospitals may actually save money by not treating cardiac patients appropriately since patients experiencing cardiac arrest are likely to be “individuals with chronic and expensive medical problems – most often they have coronary artery disease, diabetes, or heart failure – and (as DrRich has pointed out before) their sudden death today will save the system countless dollars tomorrow.”

Insurance companies do have a financial incentive not to treat cardiac arrest patients optimally.  The question is whether or not these financial incentive impact the manner in which physicians practice medicine in the hospital.  Dr. Rich gives some evidence that financial incentives may be playing a significant role in the quality of hospital care in the U.S. today.

There has been a recent trend for more and more surgeries to take place in ambulatory surgery centers (ASCs). In fact according to the Medicare Payment Advisory Commission, in 2004 up to 70% of surgeries took place in these ASCs. Do ASCs offer better quality surgical procedures than Hospital Outpatient Departments (HOPD)?

ASCs may be an improvement over HOPDs because these centers preform a high volume of a few specific procedures which may increase quality. Further, ASCs often have newer equipments than hospitals. On the other hand HOPDs generally have more resources than ASC to deal with complications and economies of scope may help hospitals to provide more effective care.

How do we find out which facility offers better quality? This question seems easy to answer: find a quality metric and measure whether ASCs or HOPDs score higher. The problem is that physicians may choose to conduct surgery on healthier patients at the ASC and perform the surgery on sicker patients in the HOPD. This way, if there are complications from surgery on a relatively sicker individual, the hospital will have more capabilities to deal with the situation. This selection problem, however, can bias studies which simply compare the quality levels of ASCs and HOPDs without taking into account difference in patient characteristics in each facility type.

A study by Chukmaitov et al. (HSR 2007) attempts to measure these quality differences using patient-level surgery data in Florida between 1997 and 2004. The authors attempt to eliminate the selection bias using physician diagnoses (i.e.: DRG/HCC methodology) to quantify the ex-ante and ex-post health status of the patient. The key to this methodology is that the authors also have information on any of the patients’ secondary diagnoses.

With this data, the author do in fact find that HOPDs do have a sicker patient base. Thus, it is important for researchers to correct for this selection problem. Secondly, Chukmaitov and co-authors found that “…neither organizational type (ASCs or HOPDs) performed better overall, there appear to be important differences in quality outcomes for certain procedures. These differences may be related to variations in organizational structures, processes, and strategies between ASCs and HOPDs.”

On problem with the study is that the authors use mortality as their quality metric. A more sensitive metric could better capture quality differences. Also, one may worry about the accuracy of the doctor diagnoses. HOPDs may be more sensitive to DRG creep than ASCs–or vice versa–and this may leaded to an incorrect selection correction methodology.

• Askar S. Chukmaitov, Nir Menachemi, L. Steven Brown, Charles Saunders, Robert G. Brooks “Comparative Study of Quality Outcomes in Freestanding Ambulatory Surgery Centers and Hospital-Based Outpatient Departments: 1997-2004”
  Health Services Research (OnlineEarly Articles).

Doctors are often perceived as benevolent professionals. They are hard-working individuals who extend their largesse by giving away free medical care to those in need. Studies by Cunningham and May (2006) and the American Hospital Association find that doctors provide uncompensated care equal to 6.3% or 5.6% of their cots annually respectively.

A recent Journal of Health Economics article by Gruber and Rodriguez concludes that these figures may be overstated. In fact, the study finds that physicians provide negative amounts of uncompensated care to the uninsured.

How is this possible? While it is true that doctors do give away free care to the uninsured and that many of those without insurance do not pay their bills, the uninsured patient often pay a large portion of the list price whereas those who have insurance receive a negotiated lower price. Thus, the authors find that “the majority of physicians actually make money, on net on their uninsured patients…12-14% of physicians found their uninsured patients more than twice as profitable as their insured patients; that is the net payments from the uninsured were more than twice the expected payments from the insured patients.”

Even when the authors ignore the higher list prices the uninsured pay, they still find that only about 1% of total revenues are given away as free care to the uninsured. Much of this amount, however, is due to non-payment by the patients rather than free care given away by the physicians.

Medicine may be a business after all.

• Gruber J, Rodriguez D. 2007. “How much uncompensated care do doctors provide?” Journal of Health Economics, 26(6): 1151-1169.

A New Yorker article (“The Checklist“) recounts Peter Pronovost’s efforts to improve the delivery of medical care. One of his simplest ideas was to invent a 5 step checklist to reduce line infections:

Doctors are supposed to (1) wash their hands with soap, (2) clean the patient’s skin with chlorhexidine antiseptic, (3) put sterile drapes over the entire patient, (4) wear a sterile mask, hat, gown, and gloves, and (5) put a sterile dressing over the catheter site once the line is in.

All doctors know these 5 steps, but in the distraction-filled world of the I.C.U., it is very easy for the physician to forget any one of the steps. Dr. Pronovost’s checklist idea has extended to other treatment areas as well. Yet he believes that Americans are still not getting serious about treating medical care as a science.

“The fundamental problem with the quality of American medicine is that we’ve failed to view delivery of health care as a science. The tasks of medical science fall into three buckets. One is understanding disease biology. One is finding effective therapies. And one is insuring those therapies are delivered effectively. That third bucket has been almost totally ignored by research funders, government, and academia. It’s viewed as the art of medicine. That’s a mistake, a huge mistake. And from a taxpayer’s perspective it’s outrageous.â€? We have a thirty-billion-dollar-a-year National Institutes of Health, he pointed out, which has been a remarkable powerhouse of discovery. But we have no billion-dollar National Institute of Health Care Delivery studying how best to incorporate those discoveries into daily practice.

Checklists are not the solution to every problem.  A large portion of medicine deals with complex condition with large uncertainties and many disease interactions.  Further, it may be more difficult for an insurance company to institute checklists than a hospital manager or someone further down the chain of command.  Nevertheless, standardization in medicine should help to dramatically improve quality.

A paper by Alexander S. Preker and April Harding at the World Bank analyze the roles of the public and private sector in health care.  One of the more interesting portions discusses medical care financing using some examples from ancient history.

“Ideological views on the roles of the state and the private sector belong to a long list of false antitheses in the field of medicine and health care. Since the beginning of written history, the pendulum has swung back and forth between minimalist and heavy-handed state involvement in the health sector.

During antiquity, people used home remedies and private healers when they were ill. Yet, as early as the second millennium B.C., the papyri give fascinating evidence that Imhotep, archetypal physician, priest, and court official in ancient Egypt, introduced a system of publicly provided health care with healers who were paid by the community.

At best, financing, organization, and provision of health care was limited to the royal courts of kings, emperors, and other nobility who might have a physician for their personal use and for their troops at the time of battle. The masses got by with local healers, midwives, natural remedies, apothecaries, and quacks.” 

•  Alexander S. Preker and April Harding. 2000. “The Economics of Public and Private Roles in Health Care: Insights from Institutional Economics and Organizational Theory.” HNP Discussion Paper, World Bank.

Economists and health researchers have generally shown that when doctors are paid on a fee-for-service basis, they will advice the patient to undergo more medical procedures than when the doctor is paid on a capitation or salaried basis (see my own paper: “Operating on Commission“). Which payment method maximizes welfare has not been proven and is likely to vary based on the medical procedure in question.

To add to the confusion, Astrid Selder writes in “Physician Reimbursement and Technology Adoption” that physician reimbursement mechanism may also affect the rate at which new technologies are adopted.

Selder lays out the following simple theoretical structure in which the social planner maximizes the following:

• (1-π)U(Y-P)+πU(Y-P-acm-ε +G(m) -nm)
• s.t.: P + πacm-%pi;R=πpm>=0
• s.t.: R + (p-c)m>=0
• s.t.: m<=B

The first constraints represent the zero-profit conditions for the insurer and the physician respectively and the third is a technology constraint. The probability of falling ill is π. Individuals have income Y, an insurance premium of P, and a coinsurance rate of a to may for the marginal cost, c, of a given level of medical treatment, m. Non monetary treatment costs (e.g.: side effects, time costs) are represented by the parameter n, while the benefits of the treatment are represented by the function G(m). The doctor receives a capitation payment of R and a marginal revenue amount given by p-c. B represents the technology constraint.

It seems obvious, but Selder shows that an increase in monetary medical costs (c) or non-medical costs (n) are welfare destroying. Technological innovations, represented as an increase in B are welfare improving if the technological constraint is binding or have no impact on welfare is the technological constraint is not binding. This results is intuitive: higher costs are bad, technological innovation is good.

This result, however, only holds when there is perfect information. With asymmetrical information, technological innovations may be welfare enhancing or welfare destroying. The welfare enhancing argument is similar to above: better technology leads to better medical care. If there is a moral hazard problem, however, using more basic technologies may actually help to counteract the tendency to over-consume medical care in the presence of insurance. Also, in the presence of moral hazard, technological innovations will cause insurance companies to charge higher premiums in order to cover the additional cost of this care.

How does the technological constraint, B, affect welfare in different physician compensation schemes?

• “If B is a binding constraint and increases in B are welfare enhancing then a fee-for-service system should be used. Increases in B and reductions in [monetary medical costs] c are induced all of which are welfare improvements. Incentives with respect to [non-monetary costs] n cannot be improved upon.
• If B is a binding constraint and increases in B are welfare reducing then a system of cost sharing [e.g.: capitation] should be implemented which induces reductions in B and c and gives no clearcut incentives with respect to n. Incentives with respect to B and c are thus optimal, and incentives with respect to n cannot be improved upon.
• If B is not binding the optimal reimbursement system depends on the demand elasticities with respect to costs.”

In words:

“It has turned out that the state should classify diseases or treatments into subgroups which are reimbursed differently in order to achieve the desired welfare effects in each subgroup. Especially for the case of extremely severe illness shocks the introduction of a fee-for-service system may be socially desirable. It is these very severe diseases where the capitation system seems to induce negative welfare effects with respect to the technologically feasible boundary of treatment. Cost sharing/capitation systems are most suitable for treatments where a reduction of the amount of health care consumed is desirable.”

While the solution Selder proposes is logical, it does not take into account the cost to the state to collect information regarding these disease classes. Lobbying will likely influence whether a given treatment falls into the fee-for-service or cost-sharing grouping. Nevertheless, Selder’s general findings seems reasonable and applicable to the medical care finance design in the real world.

• Selder, Astrid. 2005. “Physician Reimbursement and Technology Adoption” Journal of Health Economics Volume 24, Issue 5, Pages 907-930

“On the biggest shopping weekend of the year, you’ll know the price of the big-screen TV and the Wii you’re about to buy – but you’ll likely be in the dark about the cost of any health care you need.”

Two Wisconsin state senators are trying to change this.  The Milwaukee Journal Sentinel (“…Health cost disclosure“) reports that “Sen. Jim Sullivan (D-Wauwatosa) and Rep. Steve Wieckert (R-Appleton) this week introduced a bill requiring health care providers and insurance companies to make available information about the cost of procedures or services to patients who ask for it.”

Here is one type of government intervention I support: the government is helping to reduce asymmetric information in the medical care market without fixing prices.  The bill would compel providers to state the cost of the 50 most common medical procedures.  These costs would be divided into 3 groups: the usual rate for the service (whatever that means); the rate paid by government programs; and the average rate for health plans.

Milwaukee pediatrician Carl Eisenberg, does note that the cost of a procedure can vary from patient to patient.  Nevertheless, the provider could charge a fee in which for some patients they lost money, but for some “easy” patients they made above average profits. 

There are other problems with the pricing structure.

Larry Rambo, chief executive officer for Humana’s Great Lakes region, said cost information might best come from an insurance company because it can encompass the “episode of care,” meaning all the costs that go into treatment.

“If you’re going in for knee surgery, you’re going to get a bill from the hospital, you’re going to get a bill from the surgeon, you’re going to get a bill from the anesthesiologist and you’re going to get a bill from the radiologist,” Rambo said.

Nevertheless, I am always in favor of more information.  As a supreme court jurist once wrote: “sunlight is the best disinfectant.”

I recently read a Health Affairs article analyzing a pay-for-performance (P4P) demonstration. The Local Initiative Rewarding Results (LIRR) demonstration in California involved seven Medicaid-focused health plans in California between 2003 and 2005. Here are some of my most recent thoughts on P4P:

• The article seemed to show that P4P worked best when there was much consensus over how doctors should treat patients. The irony of P4P is the following: P4P programs with high levels of physician consensus work, but if everyone physician is already acting appropriately P4P does not make a major change in behavior; larger behavioral changes can occur when physicians are greatly deviating from the optimal practice, but in this case it is very difficult to implement P4P.
• P4P plans are often implemented so those that do well gain income and those that preform poorly maintain their status quo income. When no one loses any money, P4P is supposed to gain more acceptance among physicians. In equilibrium, however, an economist would predict that those with low P4P scores will receive lower wages in the future (or wage increases below inflation) due to P4P.
• Unsurprisingly, the authors of the Health Affairs paper found that meager financial incentives do not significantly change physician behavior, while larger financial incentives have a greater impact. Also, good communication with physicians helps to increase physician compliance with P4P mandates.
• If P4P evaluates doctors on care levels which depend on patient compliance, health plans can help physicians to increase the quality of care. For instance in the above study, “many providers used the plan lists of members turning fifteen months old as the basis for outreach…”
• When P4P financial incentives vary across plans, it is difficult for physicians to focus on specific quality indicators due to complex reimbursement schemes in each plan.
• When HEDIS scores improve, some of this improvement is due to better quality while much of it may be attributed to better documentation in a patient’s medical records.

Suzanne Felt-Lisk, Gilbert Gimm and Stephanie Peterson (2007) “Making Pay-For-Performance Work In Medicaid” Health Affairs, v26(4) pp. w516-w527.

Arnold Kling of the EconLog site has some commentary on P4P when discussing Tim Hartford’s latest book (“The Logic of Life“).

I have a very different approach to compensation. I think that the key is to change compensation schemes frequently. The reason is that any scheme can be gamed, and the longer you wait to change any given scheme, the more effectively the participants will have gamed it. That is one reason I think that “Pay for Performance,” the newest miracle cure for health care costs, will fail miserably. The doctors will be able to run circles around the bureaucrats. In the U.K., they already have–all of a sudden, 91 percent of doctors were receiving bonuses for being above average.

I can’t verify this ‘91%’ figure.  Using pre-P4P measure as the measuring stick will lead to many physicians reaching the ‘above average’ mark in the post P4P mark.  Much of this increase is due to better record keeping; some of it is due to better care.

Looks like the convenience clinic trend is coming to my neck of the woods in Southern California.  According to the San Diego Union-Tribune (“Are retail clinics a healthy choice?“) six Minute Clinics are opening in San Diego county with ten more on the way before year’s end.

These clinics likely will lower the cost of obtaining a flu shot.  Not only will providing the flu shot be less expensive for the provider, the patient will have fewer time costs waiting for a doctor or driving to an inconvenient physician location.  These clinics are likely just as safe as a physician’s office if the patient is healthy.  However, if a patient has multiple diseases and needs a more in depth check-up, these convenience clinics will be poor substitutes in terms of quality.  There is always a tradeoff.

Here are some tips from Dr. Marissa Weiss on building a good doctor-patient relationship from the patient side. Thanks to Dr. Rich’s Covert Rationing blog for the link.

• Greet the doctor–or introduce yourself if this is a new physician–with a professional handshake.
• Let your doctor know what is on your mind and how the doctor can be most helpful.
• Before you get to the doctor’s office, write down your symptoms and the questions you have for the doctor.
• Record the doctors answers to your questions. This can either be done by taking notes, using a tape recorder (ask the doctor’s permission first) or bring a friend or family member to take notes for you.
• Sit close enough to the doctor to feel like you are having a personal conversation, but not too close to make the situation uncomfortable for either of you.
• Feel free to ask the doctor to repeat him/herself if you did not understand what he/she said.
• Make sure that when you receive a test result, that your other doctors are informed of these results.
• Ask yourself what do you value in a doctor. Be sure that your doctors satisfy your needs.
• Go to a doctor who likes being a doctor. These physicians will make the extra effort to provide you with the best care.

According to the Telegraph (‘Record numbers go abroad for health‘), “More than 70,000 Britons will have treatment abroad this year – a figure that is forecast to rise to almost 200,000 by the end of the decade.”  Many of these individuals are seeking treatment in countries such as India, Hungary, Turkey, Germany, Malaysia, Poland and Spain.  Why are these individuals going abroad?  Long wait lists and shortages of qualified clinicians (such as dentists – see May 9, 2006 post).

Ezra Klein notes that 100,000 Americans travel abroad for plastic surgery.  Why do they do it?  Here, wait lists and physicians availability are not the major motivators (living in Southern California, I can tell you that there is no shortage of plastic surgeons).   In the U.S., monetary cost is the major consideration for most patients who become medical tourists.

Thus, in both countries, people are trying to find better deals abroad.  Health care is expensive in the UK; not in monetary terms, but due to a high time cost from long waiting lists. Health care is expensive in the U.S.; not due to time costs from waiting lists, but from high monetary cost.

Megan McArdle of Asymetrical Information notes that Baumol’s Cost Disease is one explanation as to why health care is so much cheaper outside the OECD.

Health care systems suffer from Baumol’s cost disease: it’s a labor-intensive service that doesn’t offer huge scope for gains in labor productivity. The number of hours it takes to manufacture a car is consistently falling, but the number of hours it takes to perform doctor’s visits is roughly the same as it has always been. As a society gets richer, in order to attract workers, the labor intensive service has to pay competitive wages with the sectors where productivity is rising rapidly; that means that costs for labor-intensive services rise faster than the general price level.

Bangkok’s doctors are so cheap because a doctor making a modest wage by British standards can have an enormous house and a flock of servants to take care of him, putting him in the very top echelon of Thai earners. Nurses too, can make an American pittance and still live very well. As Bangkok gets richer, the servants and the gigantic house will not be so affordable–and neither will the health care.

This is how a very interesting article (“P4P is changing me“) in Medical Economics begins. The essay won an award in the 2006 Doctors’ Writing Contest.

The author of the story is a physician who has been under much financial pressure of late; a divorce, med school loans, a mortgage, alimony and child support were all eating away at the author’s income. One day an 84-year old WWII vet walks into his office. He had a left renal mass, but did not want any further medical treatment for this problem. The author must contemplate how–or if–he should treat the patient.

“There’s very little I could do to improve [the patient's] life. I asked him once what I could do to help, and he requested merely that I talk with him. That’s what I’ve done, every three months, but I won’t get any extra pay for that. I could check his A1C, though—after all, he does have diabetes, and it has been more than a year since it’s been checked.“

The patient had been very diligent in maintaining the correct levels of blood pressures, heart rates, and blood sugars. The author believed that an A1C test was clinically unnecessary. But…

We talked for 30 minutes (10 minutes over the scheduled 20-minute appointment); I was then behind. How would I wrap this up? Should I make one last plea that he open himself up to counseling and antidepressants, and not suicide? Or should I tell him that I need him to go to the lab and have his blood work checked? Well, I doubted I could do much to improve his life, but I did need the $50 . . .

Should I start statins on the drooling demented to lower their LDL? Should I preach to paranoid schizophrenics that they must quit smoking? Doing so might help ease my burdens—will it ease theirs? Without a financial incentive, I treated practice guidelines as guidelines, and I treated patients as patients. With financial incentives, will the guidelines become my goal? Will I lose patience for patients who are just a means to my means?

• Mansfield, Richard J. (2007) “P4P is changing me,” Medical Economics, May 4, 2007.

On the news yesterday that Microsoft purchased a 1.5% stake in Facebook for $240 million, social networking appears to  highly valued commodity.

“…[T]he strength of social networks among Mexican-Americans is positively related to access to care.”

Is this true? That is hypothesis that a recent NBER working paper by Roan Gresenz, Escarce and Rogowski attempt to test. The authors uses data from 1996-2002 MEPS, along with data from the 2000 Census, Area Resource File, the CPS and the Bureau of Primary Health Care Uniform Data System.

Methods

The econometric specification is relatively simple. A probit regression is used where the dependent variables are either (1) whether the person has a “usual source of care,â€? (2) whether or not the person has an office-based physician or non-physician visit during a year; (3) whether the individual has any prescription drug expenditures during the year; (4) whether the individual has any medical expenditures during the year.

Social networks are measured three ways. The first is the percentage of Hispanics in an individuals ZIP code of residence, the second is the percentage of the population that is foreign born and Spanish speaking, and third is the percentage of Spanish speakers in a ZIP code. Each social network measure is interacted “…with an individual-level variable indicating whether the individual was born in the U.S., is foreign-born but has lived in the U.S. for more than five years, or is foreign-born and a recent immigrant.”

Results

The authors find that Mexican-Americans who only speak Spanish have less access to care than bilingual Mexican-Americans. Insured Mexican-Americans who live in areas of dense Hispanic populations have more access to care than insured Mexican-Americans living in areas with a weaker Hispanic presence. The results for uninsured Mexican-Americans are mixed. It seems that uninsured individuals living in an area with more Hispanics or more Spanish speakers leads to more medical expenditures and office visits, but seems to decrease the percentage of the population who spend money on pharmaceuticals or have a usual source of care.

Healthcare Economist commentary

One worry is that areas with larger Hispanic populations are areas with higher economic growth or are somehow different than areas with fewer Hispanics or Spanish speakers. Since the authors use data on a ZIP code level, this may be less of a problem. Further the authors state the following:

“We find no effects of these characteristics of the local population on access to care for U.S. born Mexican-Americans, suggesting that similarities in race and language may contribute more to the formation of social ties among individuals who are less acculturated to the U.S. “

While the data seem to prove that Mexican-Americans–especially the insured– have more access to care in areas with high levels of Spanish-speakers, the mechanism of how this manifests itself is unclear. The authors claim that social networks is the cause. Social networks provide information concerning which doctors are of high quality and are Spanish-speaking. On the other hand, a supply-side story could explain this phenomenon as well. In areas with many Hispanics, there will be more Spanish-speaking doctors and Mexican-Americans will gain more utility from a physician office visit. This is likely true regardless of whether a single individual has a large or small social network.

Even though this paper uses a large data set and has an intuitive result, since their is no measure of an individual’s social network the results can not prove that social networks–rather than other features of heavily Hispanic areas–are causing changes in access to care.

• Roan Gresenz, Carole; Escarce, Jose J.; Rogowski, Jeannette (2007) “Social Networks and Access to Health Care Among Mexican-Americans” NBER Working Paper #13460.

Revascularization (bypass surgery or angioplasty) have been frequently used procedures to treat patients who have experienced a myocardial infarction (MI). These procedure are expensive, but are supposed to enhance longevity. Do they?

This is the question analyzed by David Cutler in his NBER working paper titled “The Lifetime Benefits of Medical Technology.” The problem with many MI studies is that they are short term. Cutler uses data on Medicare beneficiaries who had a heart attack between 1986 and 1988. This means that Cutler can utilize 17 years of follow-up mortality data.

Another issue with non-randomized trials is that of patient selection. Very sick MI patients likely will not receive revascularization surgeries because they not be well enough to survive the surgery. Relatively healthy MI patients may not need revascularization. Thus, even the direction of the selection bias is unknown in this case. In order to account for this selection problem, the paper uses an instrumental variables approach.

The instrument is “the distance to the nearest revascularization hospital [defined as a hospital capable of preforming a revascularization] minus the distance to the nearby hospital of any type.” This instrument was used in a paper by McClellan, McNeil and Newhouse (JAMA 1994). In order for the instrument to be valid, “patients who are more likely to benefit from invasive treatments do not select their residential location based on distance to high-tech medical care.” Cutler argues that this likely true since most covariates are balance above and below the median differential distance. It is possible, however, that richer, healthier people live in more affluent areas and revascularization hospitals locate their facilities to attract these types of patients. I do not know whether or not this is the case. Also, “…if hospitals that provide revascularization are also better at providing aspirin at admission, at managing post-acute follow-up, or at treating subsequent illnesses years later, the instrumental variables estimates will overstate the importance of revascularization.”

Cutler does show that his instrument is relevant as “people who live closer to a revascularization hospital are 3 percentage points more likely to receive a revascularization procedure than those who live farther away.”

Results

The affect of revascularization on mortality is not clear.

“The marginal person receiving a revascularization is about 4 percentage points more likely to survive the first day after the MI than if the person did not receive a revascularization (although not statistically significantly). This gap narrows over time and even reverses by 1 year. At that time interval, people who received revascularization are 6 percentage points more likely to have died than people not receiving revascularization.”

After 17 years, people with MI have a mortality benefit of 5% but this result is not statistically significant. Cutler also examines the cost-effectiveness of revascularization procedures:

“…The greater survival for the marginal patients receiving revascularization translates into 1.1 years of additional life expectancy. The cost of this gain is about $38,000. Thus, the cost per year of life is $33,246.”

A year of life is generally valued at around $100,000, which might lead one to conclude that this is a worthwhile procedure. Since the mortality differential is not measured very precisely, however, one should be somewhat skeptical of this conclusions. Further, Cutler wisely notes that he is not sure whether or not the actual revascularization caused the decreased mortality. Being admitted to a revascularization hospital may simply be a proxy for the receipt of other hospital services, or it could be the case that revascularization hospitals provide superior patient management and patient care than non-revascularization hospitals. Also, due to data constraints, this paper only examines mortality effects. The impact of heart surgery on quality of life is not considered.

• Culter, David M. (2007) “The Lifetime Costs and Benefits of Medical Technology” NBER Working Paper # 13478.

Many health care policy researchers believe that non-physician clinicians, such as physician assistants, nurse practitioners and midwives can help to reduce cost while maintaining quality. Midwifery has gained in popularity over recent years. Groups such as the American Public Health Association, Public Citizen and the National Organization for Women all support increased access to midwifery care.

The question remains whether or not midwife care during pregnancy is inferior, equivalent, or superior to physician care. Amalia R. Miller attempts to answer this question in her 2006 B.E. Press paper.

Differences between midwives and physicians

• Skills: Physicians receive an MD while midwife training is comparable to a nursing background. Only physicians can preform surgery such as a cesarean delivery.
• Financial Incentives: Physicians have a financial incentive to recommend cesareans since they will reap the financial rewards of preforming the surgery. Since midwives do not receive any compensation from surgery, they may be more likely to look out for the best interest of the patient.
• Attitude toward childbirth: The midwifery model of care views birth as a natural process and gives the mother more input towards shaping the birth experience. The physician’s medial approach “…highlights the risks of childbirth, viewing the event as inherently medical, even pathological, requiring hospital admission and technological intervention.”

Quality

One problem with measuring the quality of care received by those who use midwives is that of selection bias. For instance, healthy women may be more likely to use a midwife. Pregnant women with serious complications will be more likely to use physicians. Thus, a researcher may erroneously conclude that pregnant women treated by physicians are more likely to have cesareans, when a more appropriate conclusion would be that physicians treat a less healthy patient base and thus preform more cesareans.

The best study preformed to date is a Chambliss et al. (1992) paper. The authors conducted “[a] randomized blinded clinical trial was conducted in which 492 low-risk patients were assigned to either physician or midwifery management.” Unlike most non-randomized trials, the authors found a small positive relationship between midwifery and cesarean rates.

Methods

The Miller (2006) paper looks at how midwifery affects cesarean rates. They use 1989-1999 Natality Detail Files as well as the 1989-1999 March Current Population Surveys (CPS) as her data source. The author considers a simple OLS regression using cesarean rates as the dependent variable and the use of midwifery–along with other covariates–as the independent variables. The problem of selection bias remains.

Thus, the authors use the enactment of Any Willing Provider laws as a proxy for state-wide midwifery usage. These laws “prohibit discrimination against a class of providers.” While Any Willing Provider laws are not directly related to midwives, the authors also use specific state midwifery reimbursement laws to proxy for midwifery usage. The claim made by Ms. Miller is that these laws are exogenously enacted; this creates a natural experiment and allows a difference-in-difference regression.

Results

Ms. Miller finds that midwifery reimbursement laws, unsurprisingly, do increase midwifery usage by pregnant women but more general Any Willing Provider laws do not alter midwifery usage rates. The authors continues to state that “…The main finding of the Chambliss et al. (1992) study is confirmed: there is no evidence that the expansion of midwifery led to a reduction in cesarean section rates. Hence, the results from the small randomized trial appear to generalize to the population at large, while the non-random trials likely suffered from selection bias due to inadequate controls for patient health and preferences. ”

• Miller, Amalia R. (2006) “The Impact of Midwifery-Promoting Public Policies on Medical Interventions and Health Outcomes,” Advances in Economic Analysis & Policy: Vol. 6 : Iss. 1, Article 6.
• Chambliss LR, Daly C, Mederaris AL, Ames M, Kayne M, Paul R (1992) “The role of selection bias in comparing cesarean birth rates between physician and midwifery management” Obstetrics and gynecology, v80(2) pp. 161-165.

What has happened to physician assistant (PA) education in recent years? An article by P. Eugene Jones (Academic Medicine 2007) enlightens readers with the latest information.

The states with the most PA programs are: New York (19), Pennsylvania (15) California (10), Texas (8) and Florida (6). Alaska, Delaware, Hawaii, Mississippi, Vermont and Wyoming all have zero PA programs. Unsurprisingly, PA concentrations are highest in the states with the highest population.

For the 2002-2003 academic year, one year of PA education costs $36,000 for residents and $44,000 for non-residents. These figures include tuition costs and student fees plus expenses for books and equipment.

The most surprising finding of the article is that there is a trend for PAs to choose jobs outside the primary care fields. I once thought that PAs could be a replacement for primary care doctors when: 1) a patient was healthy or had a disease which was relatively simple to diagnose and treat, and/or 2) when patients wished to spend more time with their medical provider. In fact, Dr. Jones cites an article which claims that PA productivity is 84% of that of a FTE family medicine physician.

Nevertheless, Dr. Jones finds “…the distribution of PAs in the primary care settings of family medicine, general internal medicine, and general pediatrics was 50.8% in 1996. By 2006, only 36.1% were reportedly practicing in theses settings.”

• Jones, PE (2007) “Physician Assistant Education in the United States” Academic Medicine, 82(9) pp. 882-887.

A new study by Tai-Seale, McGuire, and Zhang (HSR 2007) analyzes how primary care physicians allocate their time in a typical office visit. The authors use data from 392 videotaped office visits conducted in three settings: 1) a salaried group practice in an academic medical center (AMC), 2) a managed care group (MCG), and a fee-for-service inner city solo (ICS) practitioners with an Independent Practice Association contract. The authors found that the average length of a visit was 17.4 minutes but the median visit length was only 15.7 minutes.

The data above show that only about 5 minutes was spent on discussing the major issue facing the patient. For minor issues, the doctor and patient only spent one minute discussing the issue. We see that physicians at the AMC spent the most time with their patient while the physicians at the ICS spent the least. The authors find that “…while time spent by the patient and physician on a topic responds to many factors, time of the visit overall is much less malleable.”

The paper also notes that “[i]ncentives in prevailing physician payments favor procedure-based patient care over time-intensive evaluation and management care.” One could easily imagine a system with a flexible physician schedule. The patient could schedule a standard 15 minute appointment for the usual co-pay, or could pay the physician extra if they wanted a 20 minute, 30 minute or 1 hour appointment. This way, the physician would be reimbursed for their time. If the insurance company paid for these extra minutes, the physicians would have an incentive to exaggerate the number of minutes spent on each patient. Thus, a likely solution is for the insurance company to pay for the base appointment length (15 minutes) and anything over this the patient will have to pay for.

• Tai-Seale M, McGuire TG, Zhang, W (2007) “Time Allocation in Primary Care Office Visits” HSR vol 42(5), pp. 1871-1894.

Much has been written on this site about the growth of convenience clinics (see posts on July 25, April 26, and April 17).  The Economist’s Free exchange blog adds to the discussion (“A spoonful of monopoly…“).  It warns how the AMAs monopoly powers may be a threat to convenience clinics such as Medical Marts.

“The fact that there is a shortage of family physicians in many areas did not stop the AMA from trying to stem the growth of these clinics by passing a resolution in June that asked government authorities to investigate the possibility of a conflict of interest in clinic-housing drug store chains that, in effect, both write and fill prescriptions.”

Free exchange agrees with the opinions stated previously on Healthcare Economist.  Convenience clinics should expand choice, offer a low cost alternative, reduce waiting times, make available expanded hours of operation, and should maintain high quality standards for basic ailments.  The Free exchange blog concludes:

“However, it seems the AMA would like to make sure its members profit no matter what choice you make. As it happens, nurse practitioners are required by law to practise under the supervision of a physician in 28 states — including in Illinois. I’ll swallow a stethoscope if the AMA didn’t have more than a little to do with the existence of those laws. “

Many papers have attempted to calculate hospital efficiency before and after a policy change. Most research, however, does not take into account quality levels when analyzing these changes in efficiency. For instance, a doctor may increase the number of patients per hour that they visit by 50%, but if this is accomplished simply by lowering the quality of each visit, there may not necessarily be a quality improvement.

Pablo Aroncena and Ariadna García-Prado (2007) look at efficiency measures in Costa Rica after the implementation of management contracts with the local public hospital administrators. Unlike most papers, however, they attempt to take into account how quality plays a role in efficiency metrics.

Costa Rican Health Care System

In Costa Rica, health care is primarily provided by the government. In 2001, 83% of providers worked in the public sector. Approximately 77% of health care expenditures are public compared to only 23% private. The Ministry of Health provides regulatory oversight of the health care system and the Caja Costarricense de Seguro Social (CCSS)–Costa Rican Social Security Institute is in charge of public health care service delivery and financing. Most all physicians in public health care system are salaried and receive civil service status. Physicians and hospital managers receive little or no merit-based pay and thus have little incentive to improve performance.

The 1990s brought much restructuring of the Costa Rican health care system. For example:

• 1994: a population-based model of primary care was created. Basic health care teams–Equipo Básico de Atención Integrada a la Salud (EBAIS) were established to decentralize health care services and offer primary care and preventative services to the entire population.
• 1998: Decentralization Law. This law gave managerial autonomy for public hospitals.
• 2000: Management agreements fully implemented. “These contracts specified targets that managers pledged to achieve in a given time frame and were mainly deemed to get quality improvements and a better utilization of hospital resources.” Spain introduced similar management contracts in the 1990s and while hospital efficiency did increase, the measures were ineffective in primary care centers.

Data and Methods

The authors use Costa Rican public hospital data between 1997 and 2001. The authors define a productive process as follows:

• P(x)={(y,b) : x can produce (x,b)}

In the paper, x are inputs, y are good outputs, and b are bad outputs. The vector x consists of measures of MD and RN labor hours, the number of beds as a proxy for capital, and real monetary expenditures on goods and services. The good outcomes y are the number of discharges and number of outpatient hospital services used, while the bad outcome, b, is given by hospital readmissions.

The authors claim that hospital readmissions is a good proxy for quality. This may not be true. A sicker patient base may have more hospital readmissions. The authors do try to control for health status using DRGs and also their study examines changes in readmission rates so the baseline case mix of a hospital is not as important. Similarly, if a hospital has poorer patients, they may be less likely to comply with the doctors directives (either due to financial issues or misunderstanding the physician). If the case mix remains unchanged, however, this will not bias the results. A final issue noted by Arocena and García-Prado is that managers may have misreported re-admission rates in order to receive favorable reviews on their performance contracts. This problem is mitigated somewhat by the fact that the CCSS conducted audits of each hospital facility.

The distance function employs a nonparametric data envelopment analysis approach. The function used by the authors is:

• D^t(x^t,y^t,b^t,α)=min {λ: (λ^1-αb, λ^-αy) ∈ P^t(x)}

Results

The authors find that hospital efficiency increased significantly after the management contracts only in small hospitals. In large hospitals, there was neither an increase or decrease in efficiency. The paper believes that increased physician compliance with clinical protocols and better record keeping drove the improved performance for small hospitals. Peer pressure mechanisms are less effective in large hospitals, and the finding that absenteeism rates increased in large hospitals after the management agreements may show one reason why efficiency improvements did not increase in large hospitals.

Further, the authors actually find an efficiency decrease when quality is not taken into account. While the management contracts may not have strictly increased throughput, they do seem to have increased quality in small hospitals and the quality gains outweigh the quantity losses, at least in the case of small hospitals.

• Aroncena P, García-Prado A (2007). “Accounting for quality in the measurement of hospital performance: Evidence from Costa Rica,” Health Economics. Volume 16, Issue 7, Pages 667 – 685.

Should hospitals with long waiting times have higher or lower budget transfers? Offering hospitals who have low wait times more money will increase a hospital’s incentives to decrease wait times. On the other hand, thus policy may hurt the busier hospitals and may not alleviate the wait times of those who are waiting the longest. In the case of public school transfers, if the best schools are rewarded, this encourages achievement, but may punish the worst off kids (i.e.: those at poorer schools). Transfers to low-performing school may mute incentives to increase achievement.

The issue of hospital payment structure is analyzed by Luigi Siciliani in his article on optimal contracts B.E. Journal of Economic Analysis & Policy. As with any thesis which claims to give an optimum solution, this optimum is based on some assumptions. This paper uses four major assumptions.

1. Demand for treatment can be controlled by dumping some patients. Doctors can tell patients who wish to have medical treatment that they either a) don’t really need it or b) that they will not provide it
2. The purchaser (i.e.: NHS, an insurance company, Medicare, etc.) can not observe the number of people dumped.
3. Dumping is costly for the specialist. By dumping patients, the specialist receives more complaints about their service level. Thus, either the physician’s reputation is tarnished (a cost) or the physician must spent more time (another cost) convincing the patient that they do not need treatment.
4. Hospitals differ in potential demand for treatment, either due to the catchment area of the hospital or from having a better or worse reputation.

Another key assumption is that no co-payment charges can be issued. This assumption is plausible, because it basically represents the British NHS system. Thus, the optimal solution must be seen not as the ideal optimal, but as the optimal with a centralized payer and no co-payments.

The Model

Hospitals have parameter θ which describes the public hospital type. This parameter θ indicates potential demand in the absence of a rationing system.

For each treatment, patients differ in the value they would receive from treatment. For instance, healthy patients would not benefit from heart surgery, but individuals with coronary artery blockages likely would benefit from surgery. Thus the author assumes that individuals’ value from treatment is uniformly distributed between v₀ and v₁.

Patients have three options:

1. They can be treated at a public sector hospital after a wait of time w, [u^p(v,p)]={∫^T₀ v dt} -p=vT-p]
2. They can be treated in a private sector hospital with no wait, but pay a price of p, [u^NHS(v,w)]={∫^T_w v*g(w) dt} =vg(w)(T-w)]
3. or they can receive no treatment[u^none=0]

There are two costs to going to the public hospital. First, the individual has to wait w weeks longer, so they do not get to enjoy the benefit of the treatment for as extended a period of time. Secondly, since 0<g(w)<1, the treatment becomes less effective or less valued the longer the patient waits.

Thus, from the math above, we can see that a person will choose a public hospital if and only if:

• v<V(w)=p/{T-g(w)*(T-w)

The comparative statics show that longer wait times decrease the probability of using a public hospital, higher prices, p, decrease the probability of using a private hospital, and higher valuations, v, increase the probability of using a private hospital.

Demand for public hospital services is written as:

• D(θ,w,x)=θV(w)-x
• x is the number of patients who are dumped (i.e.: not added to the waiting list)

The number of treatment supplied by hospital θ is y(θ) and since supply must equal demand, we have:

• θV(w)-x=y(θ)

The authors claim that providers receive disutility from dumping patients. Also, hospitals receive more disutility when they dump patients who value the treatment more (i.e.: high v, this is more likely to be the sicker patients). Thus, we are lead to our first major conclusion.

• Conclusion 1: The patients who are dumped are the ones with the lower benefits from treatment. This means that hospitals dump the patients who don’t really need the treatment.

After some more math, the Dr. Siciliani states a second conclusion:

• Conclusion 2: A mix of explicit rationing (through dumping) and implicit rationing (through waiting) is therefore optimal. Siciliani explains that: “Rationing by waiting alone induces excessive disutility for patients. Rationing by dumping alone generates excessive disutility for the specialists.”

The author continues to conclude that a separating or pooling equilibrium may occur.

“Under symmetric information, the optimal contract is for the purchaser simply to over a transfer in exchange for the provision of the desired level of activity and waiting time, without leaving any rent to the provider…Under asymmetric information, we found that a separating equilibrium exists when it is optimal for the purchaser of health services to contract more activity and higher waiting times to hospitals with higher demand. In this case providers with low potential demand have an incentive to mimic hospitals with high potential demand. To induce hospitals to self-select, the purchaser needs to pay a rent to hospitals with lower potential demand. [But] if it is not optimal for the purchaser to contract more activity and higher waiting time to hospitals with higher demand, then a separating equilibrium may not exist.”

Problems

One main problem with the paper is that it assumes that patients with a high value, v, cost the same to treat as low value patients. If v is a proxy for sickness, this is likely not to be the case; sicker patients with a high v are more expensive to treat. If this were the case, then conclusion 1 would not hold. Public hospitals would instead treat patients with the lowest benefit and dump patients with intermediate benefits–the high benefit patients would still go to the private sector hospital.

Also, the paper does not take into account any strategic interaction between hospitals. “If hospitals with higher potential demand are contracted higher waiting times, then patients will switch from the hospitals with high potential demand to hospitals with low potential demand, increasing excessively the amount of dumping and consequent disutility for hospitals with low potential demand.”

• Luigi Siciliani (2007) “Optimal Contracts for Health Services in the Presence of Waiting Times and Asymmetric Information,” The B.E. Journal of Economic Analysis & Policy: Vol. 7 : Iss. 1 (Contributions), Article 40.

Physician scorecards have been a highly touted means to improve healthcare quality. One example is NY state’s coronary artery bypass graft (CABG) Surgery Reporting System. One side effect of scorecards is that surgeons may choose to operate on healthier patients in order to maximize their scorecard grade. In fact, over 60 percent of NY cardiothoracic surgeons reported refusing to operate on high risk patients on at least one occasion (Burack et al. 1999).

A paper by Glance et al. (HSR 2007) investigates whether or not high-quality cardiac surgeons are less likely to operate on high-risk patients. The paper uses a data set with over 57,000 patients treated by 189 surgeons. The authors first estimate a regression as follows:

• log[p_i/(1-p_i)] = α + Σβ_kx_kij + Σλ_jP_j

The equation above estimates the predicted probability of the ith patient treated by the jth surgeon with risk factors x_kij. The mortality of each patient if they are treated by the average surgeon is

• log[p_n/(1-p_n)] = α + Σβ_kx_ki

To determine the surgeon’s quality the authors used the observed to expected mortality rate.

Results

The paper finds that high quality surgeons actually treat higher risk patients. This finding is reassuring for those who favor medical scorecards. The authors due note some issues with the paper. For instance, one must be sure that the risk adjustment calculation is correct, and high-quality surgeons may be miscoding patients more frequently as high-risk. Another explanation could be that high quality surgeons have more experience and are closer to the end of their careers so they care less about scorecards and more about informal reputations. However, as young surgeons age and have been conditioned to believe that scorecards matter, this finding that high quality surgeons treat high risk patients may not hold in the long run. Nevertheless, the study is straightforward, clear and assuages some fear of patient selection by doctors operating under a scorecard system.

• Glance LG, Dick A, Mukame DB, Li Y, Osler TM. (2007) “Are High-Quality Cardiac Surgeons Less Likely to Operate on High-Risk Patients Compared to Low-Quality Surgeons? Evidence from New York State.” Health Services Research (OnlineEarly Articles). doi:10.1111/j.1475-6773.2007.00753.x

“…purchasers typically reimburse health care providers on the basis of the volume and intensity of the services provided, rather than the quality or cost-effectiveness of those services. The result is a financing system akin to paying academics on the basis of the volume and intensity of footnotes.”

This website has blogged extensively on pay-for-performance schemes (see these articles). But what do other people think of P4P.

Michael Cannon of the Cato Institute gives his take in a 2007 article. Mr. Cannon speaks out against P4P in the Medicare setting since there is little room for experimentation or learning due to Medicare’s sheer size. Mr. Cannon writes:

“The current system of private P4P programs allows insurers and employers to conduct experiments and learn from each other’s successes. Competition to improve the quality of care in a cost-effective manner encourages private purchasers to experiment with P4P, and private control gives purchasers flexibility in designing and altering those experiments. As important, private P4P experiments confine any harmful failures to smaller populations.”

The author constantly mentions that errors which occur in publicly run P4P will harm many people, but avoids mentioning the flip-side that installing a successful P4P program in Medicare can also help the most people. Mr. Cannon’s point of using competition between insurers to allow each to experiment is wise assuming that insurers want the best care for their patients. As Dr. Fogoros notes in his GUTHealtcare website, patients generally do not pay for their health insurance, employers do. And for employers “As long as we don’t hear more than the average number of complaints from our employees, the health coverage we provide is, by definition, good enough.”

Still, one should take Mr. Cannon’s point seriously that at least there is some competition in the private sector health insurance while there is no competition in government run insurance plans. Competition leads to experimentation and experimentation leads to progress a la the Learning Economy model. Further, Medicare already has complex reimbursement rules and adding P4P schemes to the mix may only further increase physicians’ cost to serve Medicare patients. Finally, since Medicare is a political entity, it is inevitable that there will be significant lobbying and rent seeking in order to have Medicare’s P4P serve certain interest groups.

Another novel point the article makes is for insurance companies to focus on patient based P4P. “…Patients who receive recommended care (or who use providers known for delivering recommended care) would face lower out-of-pocket costs, while those who do not would face higher out-of-pocket costs. Patients would know sooner whether a provider was not adhering to the plan’s quality guidelines because that deviation would affect their pocketbooks.”

P4P Tradeoffs

The article also notes some tradeoffs provided by different types of P4P programs:

Problems with P4P

Poorly constructed P4P measures may lead physicians to methods of patient selection (i.e.: treating only healthy patients in order to increase outcome scores) as well as data manipulation. Physicians would never manipulate data…right? According to an article by Bogardus, Geist and Bradley (2004), as many as 50% of physicians admit they have manipulated third-party reimbursement rules to secure coverage of a particular treatment for a patient.

Another problem with P4P that Cannon wisely points out is that “A treatment’s overall beneficial effects may hide different effects on subgroups, including no effect or even harmful effects. For example, patients may respond differently to a given intervention as a result of multiple illnesses or interactions with treatment regimens for such co-morbidities. Financial incentives that encourage providers to treat such outliers according to what benefits the majority of patients may inadvertently encourage low-quality or even harmful care.”

• Cannon, Michael (2007) “Pay-for-Performance: Is Medicare a Good Candidate?,” Yale J. Health P. Law & Ethics, Vol. 7, issue 1: 1-38.

Why do nonprofit hospitals exist? If they act exactly as for-profit hospitals, then they should be under private ownership. If they act according to some other maximization strategy, what is it?

These are the questions that Jill Horwitz and Austin Nichol look to answer in their 2007 NBER working paper. First, let us examine the composition of hospital ownership between 1988 and 2005.

We see that there is a slow change towards more for-profit (FP) ownership, and less government ownership. We can also look at the hospital figures weighted by admissions.

Here, we see a similar increase in FP ownership and a decrease in government ownership. Nevertheless, non-profit (NP) hospitals, still serve the bulk of patients in the United States.

Theories of Non-Profit ownership

1. Output Maximization. This theory was developed by Newhouse (AER 1970) and claims that non-profit hospitals offer more health care until profits are driven to zero. But the non-profit’s choice of how to maximize output is affected by neighboring hospitals. “If their neighbors are driven more by profit motives, then the nonprofit will tend to treat less profitable patients who seek less profitable types of care. In this case, the nonprofit’s behavior will be affected through the binding constraint on profits—in the absence of the profit-seeking competitors ‘cream-skimming’ patients, they would have offered a mix of services (and served a mix of patients), call it X, that generated zero profit, but in the presence of the profit-seekers, the mix X will lose money, so they must alter their behavior to generate additional profits. Thus a nonprofit will be induced to look more like a profit-seeker in an environment where there are more profit-seekers, by both being less likely to offer unprofitable services and more likely to offer profitable ones.”
2. Market Output Maximization. This theory was developed by Weisbrod (1988) and claims that non-profits seek to maximize the total medical service output for the entire community.
3. For-profits in disguise. “Pauly and Redisch ([AER] 1973) develop a formal model in which physician employees capture nonprofit hospitals, operating them to benefit physician cartels by maximizing doctors’ incomes.”
4. Mixed Objective.

Results

Horwitz and Nichol use AHA Annual Survey of Hospitals data between 1988 and 2005. The authors conclude that the output maximization theory–the Newhouse model–is supported by the data. The evidence includes the following:

• Non-profit hospitals in markets with a high concentration of for-profit hospitals are more likely to offer profitable services (e.g.: MRI) than those in low for-profit concentration markets.
• Non-profit hospitals are less likely to provide unprofitable services (e.g.: HIV/AIDS treatment) in high for-profit penetration markets than in other markets.
• “Perhaps the most convincing evidence for the effect of market mix is the results for home health and skilled nursing, post-acute services that were first ambiguously profitable, then profitable, then less profitable again. During the most profitable period, nonprofits were more likely to offer them in high, compared to low for-profit markets. During less profitable periods, depending on the specification, there was either no discernable difference or more dramatic exit among nonprofits in for-profit markets.”

References

• Horwitz, J.R.; Nichols A.; (2007) “What Do Nonprofits Maximize? Nonprofit Hospital Service Provision and Market Ownership Mix” NBER Working Paper 13246.
• Newhouse, J. (1970) “Toward a Theory of Nonprofit Institutions: An Economic Model of a Hospital,” The American Economic Review, Vol. 60, No. 1., pp. 64-74.
• Pauly, M.; Redisch M.; (1973) “The Not-For-Profit Hospital as a Physicians’ Cooperative,” The American Economic Review, Vol. 63, No. 1., pp. 87-99.

Many times on this blog, I have commented about pay-for-performance (P4P) programs. A healthcare economist, physician, or health services researcher may wonder where they can get data regarding P4P. In truth, getting P4P data is difficult; this is reinforced by the fact that for most physicians, P4P incentives make up a small portion of their salary and thus it may be difficult to detect major behavioral changes empirically.

Nevertheless, the Alliance for Health Reform has written a 2006 issue brief on P4P and cites some of the major programs.

• Agency for Healthcare Research and Quality
• Ambulatory Care Quality Alliance
• Bridges to Excellence
• California Report Card
• Integrated Healthcare Association
• Leapfrog Group
• MedPAC
• National Committee for Quality Assurance
• National Quality Forum
• Premier Hospital Quality Incentive Demonstration
• Robert Wood Johnson Foundation.

What is a good metric to measure if a doctor is adequately vaccinating their patients? For instance, is the pediatrician Dr. Smith doing an adequate job of giving his patients flu shots?

One of the easiest, and most common metrics used is simply the vaccination rate.

• Vaccination rate = (nbr of patients vaccinated)/(total nbr of patients).

But does this truly capture whether or not Dr. Smith is doing a satisfactory job of immunizing his patients? Let us decompose the vaccination rate further.

• Vaccination rate = P(Doc Visit)P(Vacc|Doc Visit) + P(No Doc Visit)P(Vacc|No Doc Visit).

For the time being, let us assume that people who do not go to the doctor do not get vaccinated [i.e.: P(Vacc|No Doc Visit)=0, so Vacc rate = P(Doc Visit)P(Vacc|Doc Visit) ]. In reality this assumption does not hold–because many people are immunized at pharmacies, Costco, their employer, their school, etc.–but it will make the analysis here simpler and does not change how physicians themselves should be evaluated.

We see that there are two components which determine the vaccination rate. The first is whether or not the patient visits the doctor. This probability is influenced by demographic factors, distance from the provider, education of the parents and many other factors. Dr. Smith can not change the demographics of his patient base or make his patients move closer to his office. Of course, items such as reminder phone calls may help increase the probability the patient visits his office, but many determinants of whether or not the patient will eventually reach his office in a given year remain out of his control.

On the other hand, the probability a patient is vaccinated once they arrive at the office is certainly under the control of the doctor. A better metric would be to analyze a group of patients eligible for flu vaccination and to see whether or not Dr. Smith actually administered the flu shot. 

A chart audit of each physicians would be useful to see if Dr. Smith vaccinated the patients who came to the office.  If the patient was not vaccinated, the auditor should look to find out why the patient was not vaccinated and work to improve the vaccination process. 

Using a chart audit to study the P(Vacc|Doc Visit), is a metric more relevant to doctors and can result in more concrete, more immediate improvements.  The downside is that is does not emphasize the public health aspect of trying to incentivize physicians offices to increase the P(Doc Visit), for their patient base.

Earlier this month, VentureBeat reported that QuickHealth, a Burlingame, Calf. company that operates walk-in medical clinics, said it has raised an $8.5 million in a second round of financing.  The company’s report states the following:

Take Care Health Systems LLC, an operator of retail clinics predominantly in the Midwest, completed its sale to Walgreen Co. in May for undisclosed terms…CVS Corp. completed the acquisition of MinuteClinic in September 2006 for undisclosed terms….America Online Inc. founder Steve Case, through Revolution Health, has backed InterFit Health Inc.’s RediClinics chain. Wal-Mart Stores Inc. formed an agreement with SmartCare Family Medical Centers in 2006 to include its retail clinics in stores in Colorado, Nevada and Arizona. SmartCare is backed by the Colorado Fund I and individual investors.

It looks like investors see lots of potential for these convenience clinics.

The largest P4P program is run by California’s Integrated Healthcare Associates (IHA). A 2006 report (“Advancing quality through collaboration“) chronicles IHA’s progress in working with the California Association of Physician Groups as well as Dr. Stephen Shortell to establish a P4P measures. The report has two very interesting summary tables: one describes how the IHA P4P measures have evolved over time, the other how payment methodologies vary by participating health plan.

Total payments to California physician groups for P4P programs totaled $37.4m in 2003 and $54m in 2004. Of the $54m, $26m went towards P4P clinical measures, $22m went to P4P based on patient experience, and the remaining $6m went for improvements in information technology. “Payments to individual physician groups ranged from 0 to $4.50 pmpm (per member per month). On average, the incentive payment was only about 1.5% of physician group income.

Through these efforts, the report finds that measured quality dimensions are improving but “‘breakthrough improvement’ has not been achieved.” Further, the report believes that much of the quality improvement is likely due to better data collection and record keeping rather than actual changes in care.

Where will IHA move P4P in the future? Recommendations include:

• increasing incentive payments up to 10% of total physician compensation by 2010 (if P4P payments are trivial, then there will likely be no behavioral change)
• incorporating better measures of risk adjustment into capitation payments (this will discourage physicians from refusing care to sicker patients for fear of reducing quality score measures)
• addition of an efficiency domain, including appropriate resource use measures (quality does not mean quality at unlimited cost to the payers)
• avoiding incentivizing physicians to ‘teach to the test’ (physicians may decrease quality care in dimensions not measured by the IHA’s P4P program).

The popularity of specialty medical facilities (SMF) has increased over the years. The number of Medicare-certified ambulatory surgery centers (ASCs) has doubled to 3,371 during the past decade. A question remains: are these “Focused Factories” good for society?

In an article by Casalino, Devers and Brewster, (“Focused Factories…“) the authors try to answer this question.

What are SMFs?

At this point there are 2 types of SMFs: specialty hospitals and ambulatory surgical centers (ASCs).

• Specialty hospitals – According to the Community Tracking Study, most specialty hospitals are either “heart hospitals” or hospitals specializing in orthopedic surgery. They are generally joint ventures between physicians and national specialty firms or local hospitals, but a few are wholly owned by either physicians or by local hospitals.
• ASCs – Most ASCs are small and have four or fewer operating rooms. The most common services provided at ASCs are ophthalmology and gastroenterology.

Are they specialized medical facilities (SMFs) good for society?

Physicians who work at or own the SMFs claim that this type of care increases quality and reduces cost. Proponents of SMFs claim productivity increases due to specialization and the fact that there is less down time between procedures. Some hospitals say that these facilities engage in competition that is ‘unfair’, but if lowering cost and increasing quality is ‘unfair’ competition, mark me down as a fan of the unfair. The hospitals also argue that the SMFs are formed around the most profitable services and thus the hospital can not subsidize money-losing departments (e.g.: ERs, burn units, trauma centers). If the hospital is losing money on certain procedures, this does not mean that they should be making excess profits on other procedures, only that health plan compensation schedules should be altered.

The hospitals, however, are not all in the wrong. The SMFs have been accused of ‘cherry picking’ healthy patients. For instance, if physicians are reimbursed $5000 for a surgical procedure, the cost of preforming the surgery may be $2000 for a (relatively) healthier patient and $4000 for a relatively sicker patient due to increased likelihood of complications during surgery for the sicker patient. Thus, the hospital is shouldered with caring for the sicker patients and it may be more difficult for them to turn a profit. This solution to this is of course to make surgery payment in a risk-adjusted manner. In reality, risk adjustment is a delicate process which depends on many unobserved health variables so this solution may not be as easy to implement as it would seem in theory.

Another issue is whether SMFs create incentives for excess medical care. This is related to the problem of integrating the diagnostician of a problem and the treater of a problem (see 10 April 2007 post). If physicians own the SMFs, there may be an even larger incentive for them to recommend that their patients have invasive medical procedures since the physicians themselves often will profit not only from the labor compensation they will receive from preforming the procedure, but will receive additional income as return on capital from their investment in the SMF. Even physicians who do not treat patients and only diagnose them will have an incentive to recommend surgeries if they own a share of the SMF where the surgery would be preformed.

To counteract this problem, some politicians are considering bills which would “prohibit physicians from referring Medicare
and Medicaid patients to specialty hospitals in which the physicians have an investment.” While this is certainly a problem, the authors wise note that the negative aspect of these types of laws “…is that it would cause society to lose any advantages that might come from physician ownership and management of such facilities.”

So are SMFs good for society? At this stage it is difficult to say with certainty whether they are or not. Further investigation on this topic is certainly merited in the future. Any comments on your opinions regarding specialized medical facilities would be greatly appreciated.

• Casalino; Devers; Brewster (2003) “Focused Factories? Physician-Owned Specialty Facilities” Health Affairs, 22, no. 6, pp. 56-67.

Dr. Richard N. Fogoros has a very interesting website named, the Grand Unification Theory of Healthcare, which relates his views about health care.   His analysis is systematic.  One is able to understand the health care system from the point of view of physicians, patients, health plans, the government, and employers. His “Pathway # 2 to Enlightenment” is very long, but merits a read.  While the author’s website certainly won’t win him any awards for modesty, it does offer some very insightful commentary.  Below I give a brief summary of some of the points which I find particularly, well, enlightening.

Rationing is unavoidable

When a resource is scarce, such as health care, it must be rationed in some way.  In a typical market, goods are rationed by a pricing mechanism.  Only those with a willingness to pay above $3/gallon can buy a gallon of gas.  Other rationing mechanisms include queuing and refusing to give individuals products or services based on some guidelines.  Dr. Fogoros’ comment that rationing is unavoidable is best understood in his mind as that third party rationing is inevitable.

Wonkonians vs. Gekkonians

Dr. Fogoros divides the world into two halves: the Wonkonian School and the Gekkonian school.  The Wonkonians consist of liberals, government regulators, politicians, and public health officials who want government to strictly regulate the health care industry.  Gekkonians, modeled after Gordon Gekko, include healthcare executives, many physicians, and most political conservatives.  This group believes in a free market system.  Where the Wonkonian School wants health care run by large government, the Gekkonians would prefer it to be run by large corporations.

Benefits of both world views

• Wonkonians: These wonks have pushed through legislation to help reduce physician fraud.
• Gekkonians: The large managed care companies have increased efficiency and standardized care (when possible).  The concept of critical pathways was introduced by the Gekkonian school.

 Drawbacks of both world views

• Wonkonians: The wonks attempt to regulate the healthcare market has created a morass of legislation.  Physicians have less freedom to use their professional judgment since if they do not abide by the standard of care and decide to bill Medicare, they may be prosecuted for fraud.  The government can turn an earnest billing mistake into a large fraud case.  For instance, the University of Pennsylvania had to pay a $30m fine in 1995 after a PATH (Physicians at Teaching Hospitals) investigation found that the university was billing Medicare for services where the attending physician was not present.  Yet having an attending physician present at every service provided is an inefficient use of physician time and also reduces the learning experience of the trainee.  Also, compliance with government regulation costs the health care industry millions (if not billions) of dollars per year.
• Gekkonians: Insurance companies make money by signing up more people for their plan.  They lose money, whenever they have to pay out money for medical costs.  Early on, the health plans realized to retain healthy patients and compel ill patients to drop their plan, they needed to “let the system bog down in red tape for the ill, while, at the same time, to work hard to keep the system squeaky clean for healthy subscribers.”  For example, “providers can strategically locate and number specific services to make them easy (e.g., primary care) or difficult (e.g., specialists) to utilize.”  Also, some health plans began to pay physicians on a capitation basis, which encourages them to withhold care, especially from the sickest patients.

Other interesting Points

Finally, I will mention a few other interesting points that Dr. Fogoros brings up.

• The Erosion of the fiduciary relationship between physicians and patients. Doctors now must abide by standards of care in order to now run afoul of the law, even if a non-standard form of care would be beneficial for the patient.  They must abide by the cost rationing of their managed care bosses in order to reduce cost.  Thus, the physician is longer the person who will advocate for the patient to get adequate care, but instead is constrained by government and corporate rules.  In Dr. Fogoros opinion: “the traditional doctor-patient relationship is vital to the professional survival of the physician, and to the physical survival of the patient.  If we lose this relationship, we lose everything.”
• Non-profit hospitals.  The article also discusses how non-profit community hospitals were bought up by private health care corporations in the late 1990s.
• Health plan customers.  Who are a health plan’s customers?  Most people would say that it is the patients.  However, most patients do not actually choose their health plan directly; a human resources employee or benefit manager from their company generally chooses the health plans which are offered to the patients.  Thus, health plans must try to market their services to these HR managers.  But don’t the HR managers want high quality medical care for their employees at a reasonable price?

“My own eyes were opened on this issue several years ago when I attended a retreat, sponsored by my hospital, that featured a panel discussion by a group of prominent local employers.  When asked how they go about assuring themselves that the health coverage they buy for their employees provides high-quality care, the captains of industry responded thusly: ‘We make widgets, we don’t assess healthcare quality.  We don’t know how, and we don’t want to know how. So we’ve got to be practical about it.  To us, quality means quiet.  As long as we don’t hear more than the average number of complaints from our employees, the health coverage we provide is, by definition, good enough.’”

As my colleague Mike Ewens wrote to me: “Monopolists hate competitors and have to use the government to keep them away.”

An example that takes center stage can be found in a recent Chicago Tribune article (“AMA takes on Retail Clinics“) . Some doctors have asked the AMA to ban on in-store clinics currently being opened by companies such as Wal-Mart and Walgreens.

Why would doctors want to do this? Likely this is to protect their ability to charge high prices to their patients. How can they justify their demands to the public? They claim in-store clinics put patient’s health at risk.

The article concludes:

“We would be disappointed if the AMA adopted a policy that is counter to what patients are demanding, which is more accessible and affordable health care that reduces overall costs,” Walgreens spokesman Michael Polzin said in a statement. “It would be hard to argue against those principles. The bottom line is, retail clinics are improving health-care access and health outcomes while keeping the patient’s doctor informed as the patient desires.”

I see no reason to outlaw in-store clinics. Giving consumers more choice is always a good thing.

The concept of pay-for-performance has been discussed repeatedly in this blog. But what about the other P4P: pay-for-participation?

In the pay for participation model, payers compensate physicians to add infrastructure or partake in data collection. For instance, a health plan may pay providers to implement an electronic medical records system. Providers may also compensate physicians to set up data collection systems where performance can be measured. One difference between pay for performance and pay for participation is that P4Performance measures are generally distributed to the public whereas P4Participation metrics are kept confidential between the payers and providers. While the lack of openness reduces the information the public has about quality, it also diminishes a hospital’s or physician’s incentive to game the system.

As an example of pay for participation, an article by Birkmeyer and Birkmeyer (NEJM 2006), looks at the case of Blue Cross -Blue Shield of Michigan (BCBSM). The BCBSM program targets cardiac surgery, bariatric surgery and other general and vascular surgery. “[H]ospitals are compensated for data collection and participation in improvement activities in the form of supplements to reimbursements according to the diagnosis-related group for surgical care.” Since the data collected are not publicly report, physicians have less of an incentive to ‘juke the stats.’ For instance, when P4P performance measures are publicly available, surgeons may decide to forgo surgery on the sickest patients in order to decrease their surgery mortality rate, even though it is just these types of patients who likely could benefit most from surgery. With their flaws not open to public scrutiny, physicians may be more open to admit errors or work with the payer to improve the quality of care.

The authors do note that pay for participation is difficult to implement and requires large amounts of organization and coordination. While the payers do cover the cost of implementing the data collection, neither hospitals nor surgeons “[profit] financially from the pay-for-participation program,” which may limit provider enthusiasm for P4Participation efforts.

• Birkmeyer, Nancy; Birkmeyer, John; 2006. “Strategies for improving surgical quality – Should payers reward excellence or effort?” NEJM, 354:8, pp. 864-870.

Externalities are a basic concept in the economics of health care. Yet actual ACIP policies do not pay significant attention to externality issues. The rationale for vaccination recommendations often doesn’t consider strategies to target sub-populations, such as school children, that are most likely to generate negative externalities by spreading the disease.

A paper by Boulier, Datta and Goldfarb (“Vaccination Externalities”) uses epidemiological modeling to estimate the marginal social benefit of each vaccine. The model is based on the Susceptible-Infective-Removed (SIR) model. A population is divided into 3 groups: (S)usceptibles can catch the diseases, (I)nfected individuals can transmit it, and (R)emoved individuals are those who have recovered from a disease. Individuals who are vaccinated are placed in the R group with probability m, where is the efficacy of the vaccine.

The model is fairly complex and will not be fully discussed here, but it is important to note the three determinants of a disease’s infectiousness.

• The rate of contact among population members: When individuals have more contact with each other (e.g.: at school, sporting events), the probability of coming in contact with more infected individuals is higher.
• The transmissibility of the disease given contact
• Period of infection: With a longer infection period, it is more likely that you will come in contact with an infected individual.

The paper’s conclusions are as follows:

“Five positive and negative findings are of particular interest. The most striking positive finding is that the actual size of the vaccination externality can be large at some levels of vaccination. In particular, for some of our influenza simulations, the marginal externality can exceed one case of disease prevented among the nonvaccinated for each additional vaccination. A second striking positive finding is that the marginal externality of vaccination may rise and then fall with increases in the fraction of the population vaccinated. The exact pattern depends on the infectiousness of the disease, and the effectiveness of the vaccine. Third, the patterns of externalities we find are quite different from, and more complex than, the diagrammatic presentations found in standard microeconomics or health economics textbooks. Fourth, the marginal social benefit of vaccination need not be monotonically related to the infectiousness of a disease. Fifth, externalities need not vary monotonically with vaccine efficacy, or the infectiousness of the disease.”

Intuitively, we see that the marginal private benefit to vaccination decreases as the number of individuals vaccinated in the population increases. The marginal social benefit of vaccination, however, increases initially from zero as more people are vaccinated since increasing the number vaccinated not only prevents the individual from being infected, but also reduces the infection rate in the general population. Eventually, however, the marginal social benefit reaches a peak and the marginal social benefit declines. This occurs because after a certain point, there are very few people left who can transmit the disease (most have been vaccinated). For instance, if there are 1000 people in the population and 997 have been vaccinated, only these 3 people are transmitter, so vaccination will provide a small marginal social benefit.

• Boulier, B., Datta, T., Goldfarb, R. 2007. “Vaccination Externalities” The B.E. Journal of Economic Analysis & Policy, 7(1).

Pay-for-performance (P4P) is one of the latest hot topics in the health policy world. Yet it has not been conclusively answered whether or not P4P incentives affect the quality of care given. Meredith Rosenthal and Richard Frank review some of the more compelling empirical studies in their April 2006 paper in Medical Care Research & Review.

Hillman et al. (Am J Pub Health 1998). In this study, 52 capitated, non-exclusive primary care practices were randomly assigned to either a control group or treatment groups in order for the authors to determine the affect of financial incentives on cancer screening. The treatment group received a bonus equal to 20% of capitation payments if it was one of the top three performers and a payment of 10% if it was in the fourth, fifth or sixth best performer range. The study detected increased screening in both the control and treatment groups, but difference in screening rates between the control and treatment was negligible.

Hillman et al. (Pediatrics 1999). This was also a randomizd trial, but the focus was on childhood influenza immunization rates. The control group was compared against 2 treatment groups: one which received feedback on their performance and another which received feedback and a bonus payment if sufficient number of children were immunized. This study also found financial incentives had no effect on immunization rates.

• Rosenthal and Frank give a few explanations why Hillman and co-authors found financial incentives to be ineffectual in either of their studies. First, the authors had a small sample size and short time horizon (18 months). Secondly, the financial incentives only pertained to Medicaid capitation patients. If a physician contracted with many non-Medicaid health plans (e.g.: private HMOs, PPOs, etc.), the magnitude of the bonuses would have been small. Finally, the physicians may not have been aware of the program or were unaware of approximately what level of cancer screening/influenza immunization would be needed to receive a bonus.

Kouides et al. (1998). This study had a treatment and control group where the treatment group received between $0.80 to $1.60 per person immunized against influenza. The authors found a statistically significant 7% increase in immunization rates between the treatment and control. Since the two groups were not randomized, it is likely that those physicians who more aggressively immunize patients choose to be in the treatment group.  This selection effect likely biases the results. Further, the authors note that the treatment and control groups differed significantly in terms of practice size and specialty mix.

Fairbrother et al. (1999). This study also looked at the impact of financial incentives and performance feedback on childhood immunization rates. The framework of the study had one control group and three treatment groups. The first treatment group received feedback every 4 months for one year, the second group received feedback and a bonus for receiving a target immunization rate, and the third group received feedback and a bonus for timely immunization. “The rather sizable bonus did improve immunization rates, but this was primarily achieved through better documentation of immunizations children had received outside of the practice, suggesting no real gain in quality of care.”

One problems with the study is that each of the 4 groups (i.e.: control and the 3 treatment groups) only had a sample size of 15 physicians. Further, the 8-month time horizon may not have been sufficient to detect a significant change.

Roski et al. (2003).  This study examined how financial incentives affected smoking cessation care.  Forty clinics were randomized into three groups: 1) a control, 2) a financial incentive-only group, 3) a financial incentive group with a computerized patient registry linked with counseling over the phone.  The authors found that documentation of smoking status and documentation of advice to quit smoking increased significantly compared to the control group.  “Despite improved adherence to guidelines, however, there was no significant impact on smoking cessation rates. In addition, in a somewhat puzzling result, the clinics that were offered both the financial incentive and access to the patient registry and telephonic counseling system showed no improvement relative to the control group.”

Amundson et al. (2003).  This study looks at a study in the HealthPartners system in Minnesota in which physicians received a bonus of over 80% of patients were asked if they smoked and were subsequently counseled to quit smoking (i.e.: ask and advise rates).  The ask and advice rates increased significantly but since there was no control group, one can not determine if the increase is due to the financial incentives or a time trend.

Overall it seems that the studies cited by Rosenthal and Frank do not show that P4P caused large changes in care.  One issue is that most of the financial incentives were small relative to overall physicians pay.  Also, P4P may increase documentation of care–in order that the physicians can receive the financial bonus–but may not actually alter care levels.  It is also possible that the changes in care practices occur over a longer period of time (i.e.: more than 1 or two years), which would not be captured in these shorter term studies.  While I do not doubt that large financial incentives will cause physicians to perform more care on the dimensions measured, P4P may also cause physicians to substitute their effort levels away from un-measured care dimensions which may be equally important to patient health.

One can only conclude that significantly more research is needed to clarify the effects of P4P.

• Rosenthal, Meredith; Frank, Richard; 2006.  What Is the Empirical Basis for Paying for Quality in Health Care? Medical Care Research and Review, Vol. 63, No. 2, 135-157 (2006)
• Hillman, A. L., K. Ripley, N. Goldfarb, I. Nuamah, J. Weiner, and E. Lusk. 1998. Physician financial incentives and feedback: Failure to increase cancer screening in Medicaid managed care. American Journal of Public Health 88 (11): 1699-1701.[Abstract/Free Full Text]
• Hillman, A. L., K. Ripley, N. Goldfarb, J. Weiner, I. Nuamah, and E Lusk. 1999. The use of physician financial incentives and feedback to improve pediatric preventive care in Medicaid managed care. Pediatrics 104 (4): 931-935.[Abstract/Free Full Text]
• Kouides, R. W., N. M. Bennett, B. Lewis, and J. D. Cappuccio. 1998. Performance-based physician reimbursement and influenza immunization rates in the elderly. The primary-care physicians of Monroe County. American Journal of Preventive Medicine14 (2): 89-95.[Medline]
• Fairbrother, G., K. L. Hanson, S. Friedman, and G. C. Butts. 1999. The impact of physician bonuses, enhanced fees, and feedback on childhood immunization coverage rates. American Journal of Public Health 89 (2): 171-175.[Abstract/Free Full Text]
• Roski, J., R. Jeddeloh, L. An, H. Lando, P. Hannan, C. Hall, and S. H. Zhu. 2003. The impact of financial incentives and a patient registry on preventive care quality: Increasing provider adherence to evidence-based smoking cessation practice guidelines. Preventive Medicine 36 (3): 291-299.[Medline]
• Amundson, G., L. I. Solberg, M. Reed, E. M. Martini, and R. Carlson. 2003. Paying for quality improvement: Compliance with tobacco cessation guidelines. Joint Commission Journal on Quality and Safety 29 (2): 59-65.[Medline]

What issues are facing primary care physicians in the near future?  A nice article by Eugene Rich and Anna Maio discusses just this topic in their paper “Late to the Feast: Primary Care and US Health Policy.”

Some issues discussed are:

• How FFS payment systems compare to prepaid-group practice with regards to the type of care provided to patients.
• The increase in HMO popularity in the early 90s lead to an increase in the popularity of generalist career choice among medical students, but the subsequent HMO backlash has reduced the number of graduating medical students choosing primary care specialties.
• Medicare and most private payers do not reimburse telephone or email conversations, and thus valuable, low-cost primary care services are not preformed.
• The paper broaches the possibility of the primary care physician as ‘a medical home’ or a facilitator of care coordination.  “The United States faces rapidly growing numbers of older individuals with multiple chronic illnesses. The benefits of increased access to specialized physicians may be subverted by failures in care coordination among multiple independent specialist offices.”
• Some hypothesize that American cultural norms favoring high-tech treatment explain the paucity of primary care expenditures.  Rich and Maio claim that this argument is false.  Germany and Switzerland both have experienced a rapid increase in the amount of medical technological advances, yet “…primary care physicians in these countries are more prevalent and better compensated when compared with specialized physicians.”

Although there have been quality improvements in nursing home care over time, most elderly (including my own grandmother) dread the thought of entering a nursing home. According to a Mattimore et al. (J Am Geriatrics Soc 1997) study only 7% of patients surveyed were “very willing” to live permanently in a nursing home, while 26% were “very unwilling” and 30% would “rather die.”

A New York Times (“Rethinking Old Age“) gives an illustrative anecdote

“Nursing home priorities are matters like avoiding bedsores and maintaining weight — important goals, but they are means, not ends. [One patient] left an airy apartment she furnished herself for a small beige hospital-like room with a stranger for a roommate. Her belongings were stripped down to what she could fit into the one cupboard and shelf they gave her. Basic matters, like when she goes to bed, wakes up, dresses, and eats were put under the rigid schedule of institutional life. Her main activities have become bingo, movies, and other forms of group entertainment. Is it any wonder most people dread nursing homes?”

The Green House Project is trying to change these attitudes through an innovative way of structuring elderly care. The program was developed by Dr. William Thomas and based on the Eden Alternative model. The Green House methodology does not only focus on medical quality measures, but quality of life measures as well such as reducing boredom and loneliness. The NYT article continues to explain that the Green House Project utilizes

“…houses for no more than 10 residents, equipped with a kitchen and living room at its center, not a nurse’s station, and personal furnishings. The bedrooms are private. Residents help one another with cooking and other work as they are able. Staff members provide not just nursing care but also mentoring for engaging in daily life, even for Alzheimer’s patients. And the homes meet all federal safety guidelines and work within state-reimbursement levels”

Kane, Lum, Cutler, Degenholtz and Yu (J Am Geriatrics Soc June 2007) find that controlling for baseline characteristics, Green House residents reported significantly higher quality of life ratings than those in a traditional nursing home owned by the same parent company.

I have two concerns regarding the Green House. The first is cost. While the Green Hou