August 2007

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Are High-Quality Cardiac Surgeons Less Likely to Operate on High-Risk Patients?

August 23, 2007 in Academic Articles, Specialists | Permalink

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[pi/(1-pi)] = α + Σβkxkij + ΣλjPj

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

  • log[pn/(1-pn)] = α + Σβkxki

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.

Corrupted Blood: A model for influenza pandemics

August 22, 2007 in Medical Studies | Permalink

Can video games be used to learn how to best plan for infectious disease pandemics? Time reports on how a World of Warcraft pandemic can be used by epidemiologists:

[The] papers document the path of an unexpectedly virulent virtual disease called ‘Corrupted Blood,’ which swept through World of Warcraft’s online characters starting in September 2005. (The game’s administrators introduced the disease as a challenge for some high-level players; they didn’t expect it to break out of the caves and into the virtual world’s cities and towns.) The disease then ravaged the player population — despite administrators’ efforts to quarantine the infected — and gave World of Warcraft its first virtual-world pandemic.

In real life, epidemiologists have long used complex mathematical models to predict how an outbreak of, say, pandemic flu might spread around the world. The problem is that testing those models isn’t very easy, which makes it hard to judge whether the models are accurate. Scientists can’t just release pathogens into cities and see how many people die. So, instead, they base their models on past outbreaks, where information collection was imperfect, or on people’s stated (but hypothetical) beliefs about what they would do during a future outbreak. The resulting models can be remarkably sophisticated, but they “lack the variability and unexpected outcomes that arise … not by the nature of the disease, but by the nature of the hosts it infects,” according to Eric Lofgren and Nina Fefferman, authors of the Lancet Infectious Diseases paper. For example, they say, the failure of the World of Warcraft quarantine “could not have been accurately predicted by numerical methods alone, since it was driven by human decisions and behavioral choices.” In other words, no model will know whether or not people ignore infection-control rules in the real world.

Those interested in how diseases are spread may also find my 27 Jan 06 post interesting. It describes how flow of money may provide a good model of how diseases spread in modern society.

Cannon on P4P

August 22, 2007 in Physician Compensation | 1 comment

“…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:

Quality Measure Upside Downside
Processes Captures provider actions that promote health Can encourage inappropriate care for outliers; Providers can game process measures through patient selection, data
Structural Captures whether providers use human/ physical capital known to improve health/convenience Does not measure whether capital is used optimally; Can require large investments by providers
Patient satisfaction Measures whether providers meet patient expectations; Captures intangible/subjective aspects of quality Poor performers may score well if patients are ignorant of higher quality options
Incorporating multiple types of quality measures Captures benefits of each measure used Adds complexity and cost; Can discourage physician compliance

   

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.”

Increased pain medicine sales (not due to Brett Favre purchases)

August 21, 2007 in Pharmaceuticals, Public Policy | Permalink

The International Herald Tribune reports that U.S. pain medicine use has increased 88%. Is that a good thing?

Many people will rush to claim that these figures show how pain medication is being abused in the United States (see Brett Favre or Rush Limbaugh). Others will claim that big Pharma’s advertising is leading people to purchase medication they don’t really need. “Spending on drug marketing has gone from $11 billion (€8.2 billion) in 1997 to nearly $30 billion (€22.4 billion) in 2005.”

On the other hand, increasing use of pain medication may be due to treatment philosophy changes. “Doctors who once advised patients that pain is part of the healing process began reversing course in the early 1980s; most now see pain management as an important ingredient in overcoming illness.”

Also, as the population ages, more and more people will need pain medication. According to the U.S. Census Bureau, the number of people over age 65 is projected to increase by 19 million people between 2000 and 2020.

The Healthcare Economist’s Recommendation

So what should be done? Do we need a crackdown on physicians who prescribe painkillers? I don’t think so. Doctors should abandon pain medicine prescription to their chronically ill patients for fear of jail time or government prosecution. The NY Times ran a story two months ago which chronicled how Dr. Ronald McIver was put in jail for over-prescribing pain medication to his chronically ill patients.

Loosening regulations will likely increase the amount of pain killers used for recreational purposes. Nevertheless, would increasing the difficulty for your grandmother to get some relief from her chronic illness be worth the tradeoff of marginally decreasing recreational pain killer usage of people who choose to do so out of their own volition? I’ll side with increasing my grandmother’s freedom to choose painkillers over restricting the freedom of recreational drug users every time.

Why doesn’t my doctor prescribe generics?

August 20, 2007 in Pharmaceuticals | Permalink

A letter in the L.A. Times today from a man in Oceanside, California stated the following:

“I read with great interest ["Under the Influence"] in the Aug. 6 Health section because I, at one time, would only use brand-name medications.  Even though I belong to a Medicare HMO, the co-pays sometimes were quite substantial.  I was forced to buy some of my medications from Canada, the United Kingdom and even Israel.

I started to ask my primary physician for generics, and to my surprise he was able to find generics that served the same purpose as the nationally advertised drug.  Today I use only generics — except in one instance, because there is no generic yet on the market.

It is entirely up to patients to insist that their physician prescribe generics whenever possible. It is amazing how much money they could save.”

Patients almost always assume that physicians have only their best interest at heart.  This is not always the case.  Physicians must comply with managed care directives, are often influenced by the free lunches and dinners handed out by drug companies and may prescribe conservatively to avoid malpractice issues.  Even your doctor acts 100% in your medical interest, it is unlikely that they will act in your financial interest.  Since the doctor is not paying for the pharmaceutical–the doctor likely does not know if you or your insurance company is paying for the drug–they do not have any incentive to prescribe based on cost.  As the gentleman from Oceanside stated, “It is entirely up to patients to insist that their physician prescribe generics…”

Best Economics Blogs

August 20, 2007 in Economics - General | Permalink

The Aaron Schiff’s 26Econ website has a ranking of the top economics blogs based on Technorati data. The Healthcare Economist comes in at number 38.

Maps on acid

August 20, 2007 in Economics - General | Permalink

The Undergraduate Economist has three interesting maps to consider. The first draws each country with its size proportional to its PPP-adjusted public sector health spending; the second shows territory size proportional to the number of people 15-49 with HIV. The final map shows each country with its territory size proportional to the percent of worldwide private spending on health services spent there.  Sadly, health care spending is lowest in the countries with the highest incidence of HIV infection.

What do Nonprofit hospitals maximize

August 20, 2007 in Hospitals, Supply of Medical Services | Permalink

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.

  Urban Rural
  Gov NP FP Gov NP FP
1988 17.91 64.46 17.63 43.17 47.63 9.20
1990 17.67 65.22 17.10 43.13 48.02 8.85
1995 17.61 64.60 17.79 43.00 48.84 8.16
2000 15.72 66.01 18.27 39.76 51.83 8.41
2005 15.60 65.18 19.22 38.24 51.95 9.81
             

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.

  Urban (weighted) Rural (weighted)
  Gov NP FP Gov NP FP
1988 17.39 73.12 9.49 32.00 58.37 9.63
1990 16.80 73.74 9.46 31.63 58.53 9.84
1995 16.21 72.87 10.92 30.22 59.85 9.93
2000 13.25 74.43 12.32 26.83 61.98 11.19
2005 13.45 73.97 12.58 25.12 62.19 12.69
             

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

CoR #32

August 17, 2007 in Carnivals | Permalink

The latest edition of the Cavalcade of Risk is up at Insurance Help Hub.  The posts by Joe Paduda and Michael Cannon are particularly interesting.

Japan: A culture of savers?

August 17, 2007 in Economics - General | Permalink

Many economists claim that Americans are spendthrifts and for good reason. The average American has over $9000 of credit card debt. Why don’t we act more like the Japanese and save?

A NBER working paper by Charles Yuji Horioka, Wataru Suzuki, Tatsuo Hatta claim that Japan’s high saving rates in the 70s and 80s were mainly due to demographics and not to the fact that the Japanese are inherently a culture of savers.

The Facts

In the 70s, 80s, and even 90s, Japan has ranked as one of the top OECD countries in terms of savings rates. In 1975 Japan ranked #1 in the OECD in terms of net household savings; in 1980 and 1985, Japan ranked #2, just behind Italy. Today, their saving rate has declined from 23% in 1975 to 4% in 2005.

Claim

The authors claim that the reason why the national savings rate was so high was due to demographics. In the 1970s and 1980s, a large share of Japan’s population was made up of working adults. The dependency ratio was exceeding low. Since working adults are savers, having a low dependency ratio will lead to high national savings rates.

In the near-term and intermediate-term future, Japan will age rapidly. Currently, 20.6% of Japan’s population is over 65, but this figure will rise to 35.7% by 2050. Since working adults are savers, while the elderly and young spend more than they earn, the authors predict the savings rate to fall precipitously in the near future. In 1975, the net household savings rate was about 23%. The net savings rate stayed above 15% until the late 1980s. By 2005, as the population has aged, the savings rate has fallen below 5%.

Conclusion

It seems that the Japanese are not such a frugal culture as Americans once though. It also turns out that most Americans (55%) have $0 credit card debt and that the median person with credit card debt only owes $2200 (according to the Bean Counter Blog). As usual, those who we hold up as idols are never really as good as we first think; those we demonize are typically not as bad as we first think.

Note

The authors wisely note that “Japan’s saving rate can be expected to decline sharply as its population ages. However, aging will also raise the saving rate of individuals due to the existence of a pay-as-you-go public pension system.”

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