Unbiased Analysis of Today's Healthcare Issues

“Adjustments” drive variation in Medicare hospital reimbursement rates

Written By: Jason Shafrin - May• 08•16

In my previous work, I have examined regional variation in Medicare and Medicaid costs through reports to the Institute of Medicine and publications in peer-reviewed journals.  We found significant variation in health care costs across regions, that high-cost regions tended to remain high cost over time, but that a region that is high-cost for treating one medical condition may not be high cost for another medical condition.

A new paper in Health Services Research by Krinsky et al. (2016) examines the causes of regional variation in Medicare inpatient cost between 1987 and 2013.  In the current Medicare inpatient reimbursement system–the Inpatient Prospective Payment System (IPPS)–hospitals are paid:

…based on patients diagnosis related groups (DRGs), and it also compensates hospitals for exceptionally costly patients through outlier payments. While each DRG is assigned a base price that applies to all U.S. hospitals, hospitals receive payment adjustments designed to account for differences in area wages, care for low-income patients under the disproportionate share hospitals (DSHs) program, and the indirect costs associated with graduate medical education (IGME), among other adjustments.

The size of these adjustments have varied over time.  For instance, the the Affordable Care Act (ACA) “reduced DSH payments by 75 percent and introduced a new uncompensated care adjustment, beginning federal fiscal year (FY) 2014.”

Using Medicare hospital cost reports, Krinsky et al. (2016) decomposed Part A payments into seven components: operating, capital, outlier, DSH, IGME, DGME, and an “other” category. The authors measure the share of these adjustment payments relative to the base DRG payment.  

The studies find that a growing share of Medicare payments for Part A inpatient care are for payment adjustments rather than the base DRG payments (see figure below).  As the adjustments are more likely to vary across regions, we see that over time, variability in Medicare hospital reimbursement rates has increased over time as well.

Figure 3

The authors summarize the results as follows:

Over the 27 years of the IPPS covered in our study, adjustments represented a large and increasing share of Medicare expenditures for acute inpatient care. The highest rates were paid to hospitals that received large payments both for DSH and medical education. Community hospitalsreceived the lowest rates.

The authors also measure variation in reimbursement within hospital referral regions (HRRs).  However, use of HRRs is not the best approach.  The Medicare Hospital Wage Index–used to adjust hospital payments for regional differences in labor costs–is defined by metropolitan statistical area (MSA) and rest of state areas.  Whereas HRRs are agglomerations of ZIP codes, MSAs are agglomerations of counties.  Thus, there may be heterogeneity in reimbursement rates within HRR by design due to CMS policy.  Nevertheless, the finding that adjustments make up a larger share of IPPS reimbursement is certainly an interesting one.


Quotation of the Day

Written By: Jason Shafrin - May• 05•16

Doubt grows with knowledge.

J.W. von Goethe

The comprehension of truth calls for higher powers than the defence of error.

J.W. von Goethe

HWR is up

Written By: Jason Shafrin - May• 05•16

Brad Wright has posted Health Wonk Review: Pivoting Towards the General Edition at Wright on Health.  Check it out!

The problem with bundled payments

Written By: Jason Shafrin - May• 05•16

Bundled payments sound like a great idea for improving efficiency and in the short-run they are. Bundled payments involve paying a fixed fee for the treatment of a specific patient over a specific time period.  For instance, CMS have considered using a singled bundled payment to reimburse providers for both acute and post-acute care providers.  This approach gives providers the incentive to provide care in a more cost effective setting. On the other hand, bundled payment–like capitation payment–incentivizes providers to offer fewer services or lower cost services to patients.

Whatever the merits and and demerits of bundled payments are in the short run, the key issue is how to price the bundle in the long run. Over time, the price of services will change and could become more or less expensive.  Thus, payers using bundled payments must have an accurate source for tracking costs over time.

More importantly the services provided in the bundle may change over time.  NPC gives one example:

For example, a payment bundle for Hepatitis C treatment in 2014 would have needed to evolve as new oral therapies such as Sovaldi and Harvoni became available. Although these drugs have been shown to be cost effective in the long term, their use would likely have been discouraged by an outdated Hepatitis C bundle.

Although Medicare updates its Outpatient Prospective Payment System (OPPS) annually, providers may have little incentive to use innovative treatments unless bundle payments are sufficient to reimburse providers for this cost.

Does Medicare or large commercial insurers have sufficient clinical and market expertise to update thousands of treatments to ensure patients receive high quality care?  Will the bundles be sufficiently risk adjusted or stratified so that providers are not incentivized to avoid the sickest patients?  On both accounts, the answer is likely no.  Thus, bundled payments can be successful in the short-run, but the long-run issues of updating the services and prices included in the bundle make this approach extremely problematic.

VBID in practice

Written By: Jason Shafrin - May• 03•16

In a typical insurance plan, patients have a fixed copayment, insurance and deductible regardless of whether the treatment they receive is considered high or low value.  However, an alternative insurance structure–known as value-based insurance design (VBID)–uses a different approach.  Under VBID, patient cost sharing is higher for low-value treatments and lower or eliminated for high-value treatments.

One such VBID program was Connecticut’s Health Enhancement Program for its state employees. Enacted on October 1, 2011, the program:

…introduced incentives to align patient costs with the value of care, including the elimination of office visit copayments for chronic conditions (a savings of $15 per visit) and the reduction or elimination of copays for medications associated with the management of the five following chronic conditions targeted by the program: asthma or chronic obstructive pulmonary disease (COPD), diabetes, heart disease, hypertension, and hyperlipidemia….Additionally, the program assessed a new $35 copay for emergency department (ED) visits when there is a reasonable medical alternative and the member is not admitted to the hospital…A novel feature of the program is its attempt to engage patients in preventive care by holding them accountable for receiving it. Members who desire to maintain Health Enhancement Program benefits must satisfy a number of requirements, including obtaining health risk assessments, screenings, and physical examinations that are appropriate for people of their age and sex.

Although the program was voluntary, Connecticut state employees that enrolled in the Health Enhancement Program were exempt from a monthly $100 health insurance premium surcharge and and also were exempt from any deductibles.

Using data for enrollees aged 18-64 between July 1, 2010 and June 30, 2013, a study by Hirth et al. (2016) compared changes in health care cost and utilization between Connecticut state employees and state employees from other states. The authors found that:

During the program’s first two years, the use of targeted services and adherence to medications for chronic conditions increased, while emergency department use decreased, relative to the situation in the comparison states. The program’s impact on costs was inconclusive and requires a longer follow-up period.


Health Care in Malaysia

Written By: Jason Shafrin - May• 02•16

Malaysia is a middle income country (GDP per capita $26,600, about half of U.S. income levels) of 30.5 million people (about the population of New York and Ohio combined).  Life expectancy is 74.75 years, just 5 years below the U.S.  Health spending in Mayalsia is only 4% of GDP (compared to 17% of GDP in the U.S.).

A recent paper by Rannan-Eliya et al. (2016) describes their health care system.  All Maylasians are entitled to free or near-free health care provided by the government. The government provides not only primary care services, but also heart surgery and some expensive cancer treatments (e.g., Herceptin for breast cancer). The supply of high-cost treatments, however, may be limited and care rationed.  “In 2011 the public sector treated 49 percent of outpatients and 74 percent of inpatients.”

Some patients choose private insurance.

Private financing goes almost solely to private providers. Outof-pocket spending accounts for 79 percent of private financing. Third-party financing, by private insurance and employers that reimburse employees for using private providers or directly pay such providers, accounts for the remainder of private financing and mostly covers middle- or upper-income workers in the formal sector of the economy…Most health insurance is group insurance that substitutes for direct employer spending on health care.

The authors find that Malaysia’s out-of-pocket health care spending as a share of GDP (1.7%) is similar to high income countries such as Austria (1.8%) and Sweden (1.6%).  Although the authors do not examine the quality of care received, the Malaysia healthcare system appears to do an adequate job of protecting patients against the financial risk of health shocks.

Improving DCE Response Rates

Written By: Jason Shafrin - May• 01•16

Non-response bias is a key problem when conducting any type of survey, including surveys that use a discrete choice experiment (DCE) methodology.  Non-response bias occurs when sampled individuals who respond to the survey differ from those who do not respond in ways that would affect the survey response.  For instance, assume that in the real-world, half of patients prefer treatment A and half prefer treatment B.  However, if a large share of patients that prefer treatment A decide not to respond to the survey, the resulting research may suggest that treatment B is strongly preferred, when in reality this is not the case.

A paper by Watson, Becker, and Bekker-Grob (2016) attempt to identify factors that affect DCE response rates using a meta-regression approach.  Using social exchange theory, they hypothesized that response rates are a function of perceived survey benefits and costs.  The identified survey benefits based on the severity of the disease and whether the survey respondents were limited to patients who had that disease (or physicians treating that disease).  They hypothesize that the benefits (and thus response rates) would be higher for more severe diseases (e.g., cancer) or when the sample population was limited to patients with the disease.  They collected data on eight factors that affected the survey’s cognitive burden to respondents.  These included:

  • Number of attributes,
  • Number of choice set alternatives,
  • Number of choice sets to be answered,
  • Includes an opt-out alternative,
  • Includes a cost attribute,
  • Includes a risk attribute,
  • Elicits time preferences
  • Same hypothetical alternative appears in all choice sets

Average response rates across all 64 studies conducted by mail that were included in the meta-regression was 50.4%.  The average number of attributes was 5.3 and the average number alternatives was 2.6 with 63% of DCEs presenting respondents with exactly 2 options. The average number of choice sets the respondents answered was 12.7.  About half (51.6%) of DCEs surveyed patients or caregivers, 21.5% health care professionals, and 20.4% the general public.  Out of the 132 unqiues studies, 64 were conducted by mail, 24 were self-completed, 16 were interviews, 8 were conducted over the internet, and 20 were placed in an “other” category.

Using this sample, the authors find the following:

Increasing the number of attributes from between two and four attributes to five attributes, six attributes or seven or more attributes decreases response rates. Including an opt-out increases response rates. We find a mixed effect of the number of choice sets: compared with eight choice sets, response rates are higher for DCEs with fewer (3 7) and more (> 8) choice sets. Contrary to expectations, studies with risk attributes have higher response rates. The inclusion of a cost attribute, time preferences or using a constant comparator design does not significantly affect survey response rates.

The perceived benefit of response increases response rates. Surveys of patients or healthcare professionals rather than the general public have higher response rates…reminders increase responses rates…

In summary (my emphasis):

Our findings suggest that researchers who want to minimise the cognitive burden should focus on the number of attributes included in the DCE choice sets.




Written By: Jason Shafrin - Apr• 28•16

Impact of Medicare Advantage on Hospital Admissions

Written By: Jason Shafrin - Apr• 27•16

Do patients who enroll in Medicare Advantage go to the hospital less frequently? The answer is yes. However, this fact may not be causal. Patients who enroll in Medicare Advantage are generally younger and healthier than patients who enroll in Medicare’s fee-for-service (FFS) program.

A paper by Duggan, Gruber and Vabson (2016) uses a novel approach to identify the causal effect. According to the NBER Digest, the authors:

examine the change in health care utilization by MA beneficiaries after they switch to traditional Medicare because their private insurer has exited the market. By focusing on cases where there are no other MA providers in the county, the authors ensure that the change in MA status is unrelated to the individual’s health or other characteristics.

Using this approach for hospitals in New York State, the authors find that…

MA enrollees who are forced to switch to traditional Medicare due to MA exit experience an increase of 0.11 hospital admissions per capita, which represents a 60 percent increase relative to the mean of 0.18 admissions. This increase in hospitalizations is accompanied by a 48 percent increase in total days spent in the hospital, a 33 percent increase in the number of procedures, and a 53 percent increase in hospital charges.

What other explanations are there for this result? Is this increase in hospitalizations a result of pent-up demand that was constrained by MA utilization restrictions? If so, there should have been only a short-term increase in hospital admissions, when in fact the increase persisted over time.

The authors do not find that MA enrollees face higher cost-sharing than traditional Medicare beneficiaries. This makes sense as MA plans that bid below the benchmark are able to reduce patient cost sharing.

The authors hypothesize that MA plans may restrict patients to hospitals that involve considerably longer travel or that MA plans more tightly restrict elective and non-urgent hospitalizations. However, quality of care and patient mortality are similar when patients are in MA or FFS plans.


Books to read

Written By: Jason Shafrin - Apr• 27•16

Andrew Soloman has an outstanding article the Guardian discussing the intersection of literature and medicine.  He his article about literature on medicine saying saying:

Medicine can contribute to literature; narrative practice can strengthen medicine. It behoves writers and doctors to learn each other’s fluencies, because their disparate approaches can add up to singular truths.

Of particular interest, the article highlights some of the best books in this genre.  Soloman’s own book Far From the Tree, although not included in the article, is another book well worth reading.