March 2008

Devon M. Herrick writes an article (”Why rent…“) creating a clever analogy comparing HSAs to equity in a house. He likens traditional health insurance to renting a home, while having a Health Savings Account (HSA) is more like owning the home. Making contributions to HSAs in essence gives you “equity” towards future health care expenses. On the other hand, if you do not use any medical care with traditional insurance, you lose all of your rent annual health insurance premium.

Mr. Herrick claims that he could cut his health insurance premiums by half if he had an HSA. There are 3 main reasons why health insurance premiums are lower. First, in a mechanical sense, health insurance plans are combined with HSAs which have higher deductibles. This means the insurance company will not pay for the first $1000 or so of medical care. Secondly, since there are high deductibles, utilization will decrease because of a reduction in the moral hazard problem. Finally, healthier people sort into HSAs and thus if everyone was compelled to have HSAs, health insurance prices would not decrease as much because there would be less advantageous selection.

As I have mentioned before in this blog, HSAs are highly unequal, since the rich 1) are the ones most likely to benefit from this legislation and 2) they have higher marginal tax rates and thus will receive a larger tax break for every dollar contributed.

Nevertheless, shifting more costs to the consumers and forcing consumers to face the true cost of medical procedures will help to reduce costs and to ensure than only necessary medical procedures are conducted.

• DM Herrick (2005) “Health Insurance: Why Rent When You Can Own?” Health Care News, The Heartland Institute, May 1, 2005.

Last Friday I was the keynote speaker for the Pinal County (Arizona) Health Care Delivery System - 2008 Conference. The conference had an interesting mix of speakers (see agenda).

Speakers included Lisa Garcia, the Assistant County Manager of Health and Human Services, two academics from the University of Arizona (Gary Hart and Keith Joiner), and the CEO of a local community college (Dennis Jenkins). Also, CEOs of three hospitals (Casa Grande, Banner Ironwood, Northwest Medical Center Oro Valley), representatives from Blue Cross Blue Shield Arizona and the Director of the Arizona Medicaid and SCHIP program (AHCCCS) also presented.

My talk was titled “Health Care Economics: An Introduction.” The power point presentation is available here. The other speakers presentations are available here.

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.

Most people do not understand what a health economist is. Where do they work? What do they do? How do they spend their time?  How are they trained?

A paper by Morrisey and Cawley (Health Econ 2008) attempts to answer this question. The authors conducted an online survey to achieve a better understanding of what health economists do.

Training

Ninety-three percent of health economists have a Ph.D. A few health economists have an MD (2.6%), an RN (1%) or a JD (<1%) in addition to their PhD. Of those with a Ph.D., 72% have a Ph.D. in Economics. Below are a list of the economics departments that have trained the most health economists in the sample:

Seventy-six percent of health economists wrote a health related dissertation, even though 2/3 of graduate programs lacked a formal health economics field. For instance, at UCSD I am writing my dissertation on health economics even though there is not established program.

Employment

Where do health economists work? Most work in academia (64%), but a large percentage also work for the government (12%), NGOs (15%) or the private sector (9%). Of those who are academically employed, below is a chart detailing where their principal appointment is located.

For those who work in public health or medical school about 50% of their salary is made up from funding from external grants and contracts.

Research Interest

Below is a chart detailing the subspecialty of the health economists in the survey.  Respondents could choose multiple options.

After reading this post, hopefully you now have some idea of who health economists are and what they do.

• Morrisey MA, Cawley J. 2008. “US Health Economists: Who we are and what we do” Health Economics, 17(4): 535-543.

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.

Many economists espouse utilitarianism as a superior ethical framework to proposed alternatives. A paper in Nature magazine finds that “Damage to the prefrontal cortex increases utilitarian moral judgements.”

Maybe there is some merit to the paper…economists have always been a strange breed.

The latest edition of the Cavalcade of Risk is up at Insurance Yak.

Some of my favorite articles include:

• InsureBlog finds a health insurance plan that costs $350 - $480 per year. Of course, there are $100 deductibles and 80%-90% coinsurnace, but this does seem like a good deal. This is pet insurance.
• The Fundmastery Blog cites a Financial Times article in which Alan Greenspan admits that “We will never have a perfect model of risk.”

Freakonomics by Steven Levitt and Stephen J. Dubner is an extremely popular book that has made economics a (somewhat) sexy topic of discussion. Levitt’s research makes economics exciting and his quirky, controversial studies make interesting reading.

John DiNardo, however, thinks that even Freakonomics is “interesting” and “entertaining,” it may not be revealing truths. Dr. DiNardo has written three critical reviews of the book. DiNardo’s criticisms call into doubt the meaning of some of the conclusions derived from Levitt’s research. For instance, DiNardo discusses the logical meaning the causal effect of obesity on health.

Nonetheless, I would argue that it is unlikely that anyone will devise a severe test of the proposition that obesity causes an increase in all-cause mortality. Simply put, the effect of obesity (or of ideal weight) is inextricably implementation specific. That is, it is not helpful to think about the “effect” of obesity for the same reason it is not helpful to debate the “causal effect of race on income”(Granger 1986). Many of us suspect, for example, that encouraging obese individuals to “starve themselves” for short periods of time might help one lose weight, but wouldn’t necessarily promote longevity (although it might, who knows? ).

Similarly, we might expect weight loss that results from increased physical activity to be more protective than
weight loss that results from increased life stress. The experience in the U.S. with the drugs fenfluramine and dexfenfluramine (Redux) is a case in point. Despite good evidence that the causal effect of taking Redux was weight loss, the drugs were pulled from the market because a “side effect” of the medication was an increase in potentially serious heart problems (Food and [Drug] Administration 1997) . Indeed, it would appear that the presumption that obesity is a cause of ill health made it virtually impossible to debate whether non–obesity was the cause of the increased heart problems. Rather, the consensus seems to be that the heart problems were not caused by non–obesity, but rather by Redux’s “side effects.”

My point is simple: when each way of “assigning” obesity that we can imagine would be expected to produce a different effect on all–cause mortality or other outcome, it is not at all clear that it is helpful to debate the “effect of obesity.” It seems more intelligible (and more policy relevant) to discuss the effect of Redux or exercise than it is to talk about the “effect” of obesity.

One study that DiNardo does hold up as an example of fine research is Cullen, Jacob and Levitt (Econometrica 2006). This paper was written by Levitt as well as my dissertation advisor Julie Cullen.

• John Dinardo (2007). “Interesting Questions in Freakonomics .” Journal of Economic Literature, Volume 45, Number 4, pp. 973-1000(28)
• Julie Berry Cullen, Brian A Jacob, Steven Levitt (2006) “The Effect of School Choice on Participants: Evidence from Randomized Lotteries.” Econometrica 74 (5) , 1191–1230 doi:10.1111/j.1468-0262.2006.00702.x

The American Economic Association (AEA) has some great resources for economists.  For instance,  it has links to:

• Rankings of the Top Economics Graduate programs
• Articles on Economists’ salaries and the Economist Job Market
• Articles on Economics Graduate Schools
• General information on Graduate study in Economics

The [Medicare Hospital Insurance Trust] fund also continues to fail our long-range test of close actuarial balance by a wide margin. The projected date of HI Trust Fund exhaustion is 2019, the same as in last year’s report, when dedicated revenues would be sufficient to pay only 78 percent of HI costs. Projected HI dedicated revenues fall short of outlays in this and all future years. ”

Who is this scare-mongering quotation from?  Rush Limbaugh?  Conservative think tanks?  Fox News?

Actually, this message is from the Social Security and Medicare Boards of Trustees 2008 Annual Report.  Currently, Medicare accounts for 3.2% of GDP.  The authors of the report project that by by 2028, Medicare expenditures will surpass Social Security expenditures.  By 2082, Medicare expenditures will account for 10.8% of GDP!

What is to be done?  We can increase taxes to levels that in the long run would cripple the economy.  We could cut the number of people receiving Medicare benefits.  For instance, we could increase the age at which people are eligible for Medicare or limit Medicare benefits to only certain groups (e.g.: the poor, those who are eligible for Social Security benefits, etc.).  The government could reduce the generosity of the plans by either shifting more costs to patients (i.e.: increasing co-pays and deductibles), or reduce the generosity of the benefit package (i.e.: rationing).  Or we could scrap Medicare all together and start over (e.g.: a voucher program, no elderly health insurance, mandatory savings for the purchase of health insurance later in life).

All of these ways to solve the Medicare crisis have pros and cons and those adversely affected by any change are likely to vehemently protest any reform.  Nevertheless, Medicare as it currently is structured is not a fiscally sustainable program.

What is the effect a country’s GDP on health? What about the country’s literacy rate on infant mortality rates? Often researchers try to answer these questions using time-series data. With time series data, we have observations of a few units (e.g.: countries or individuals) over many years.

Let the subscript i represent the the individual or country and the subscript t indicate the year. We can have a regression framework as follows:

• y_it = βx_it + ε_it

As long as cov(x_it,ε_it)=0, then ordinary least squares (OLS) will provide an unbiased estimate of β₁.

One frequent problem which occurs with time series data is that there will be serial correlation. Serial correlation (or autocorrelation) occurs when the error terms are correlated over time. For instance,

• ε_it=ρε_it-1+η_it

Serial correlation means that if your predicted y value is overestimated in period, it is likely to be overestimated in another period. This is likely due to some persistent variable omitted the regression. For instance, if we regressed test scores on a vector of explanatory variables, it is likely that student who scored higher than their predicted test score in one period would also score higher then their predicted test score in another period.

Fortunately, our coefficient vector (β) is still unbiased even in the presence of serial correlation. However, OLS is inefficient. In this case, the standard errors are too small.

One way to test for serially correlation is to use the Durbin-Watson test. Let u_it be the fitted values of the error terms after we conduct and OLS regression (u_it = y_it - β_ols x_it ).

The Durbin Watson statistic is:

• d= [Σ_{(t=2 to T)} (u_it - u_it-1)²] / [Σ_{(t=1 to T)} (u_it)²]

With panel data we have:

• d= [Σ_{(i=1 to N)}Σ_{(t=2 to T)} (u_it - u_it-1)²] / [Σ_{(i=1 to N)}Σ_{(t=1 to T)} (u_it)²]

This page will help you interpret the statistic as to whether or not you should accept or reject serial correlation. If there is serial correlation in your data, you may want to include a lagged dependent variable as one of your right hand side variables. This will result in an AR(1) specification.
Yuting Wang of Notre Dame has a good explanation of the problems that occur with serial correlation.

Are you friends members of the Marathon Runner’s of America club or the Bratwurst and Philly Cheesesteak club? If the answer is the later, you are much more likely to be obese than the former.

This is the finding of a 2007 NEJM paper by Christakis and Fowler. Obese individuals are more likely to be friends, relatives, or spouses with other obese people (and vice versa). The authors contend that there are 3 explanations for why this could be the case empirically.

1. Homophily. This means that individuals choose to associate with people who look like them. In this case, social networks would not cause obesity, it is just that obese individuals choose to hang out with other obese individuals.
2. Counfounding factors. Siblings have the same genes. Obesity social norms within a particular geographic area may affect friends and family in a similar manner. These unobserved, confounding variables may also be the true cause of why
3. Induction. Social influence and peer effects may effect the obesity level of each person in a group. The authors hypothesize that this explanation to be the major avenue by which social networks affect obesity.

The paper tracks a database of 12,067 individuals over 32 years. The regressions use a lagged dependent variable to eliminate problems of serial correlation.

Results

Let us define the ‘ego‘ the person as the person whose behavior is being analyze and the ‘alter’ as a person connected to the ego by a social network. When the ego’s alter is a friend and becomes obesity, there is a 57% chance that the ego will become obese. This impact is larger for same sex friendships (71% probability of become obese if the alter becomes obese) than opposite sex friendships (effect not different from zero).

How does the obesity of one’s spouse affect the ego’s obesity? According to the authors, “[a]mong married couples, when an alter became obese, the spouse was 37% more likely (95% CI, 7 to 73) to become obese. Husbands and wives appeared to affect each other similarly (44% and 37%, respectively).”

What explains this phenomenon that the alter’s obesity will affect the ego’s obesity. It is possible that the social network as a whole experiences similar life events which affect obesity. However, even when alter’s live geographically far from the ego–and thus likely have different life experience over time–this does not change the effect the alter’s obesity has on the ego. Christakis and Fowler claim that this supports their perception that social norms heavily influence obesity. Also, the spread of smoking behavior does not affect the spread of obesity. One would guess that social networks would have a similar effect on smoking and obesity. The authors claim that this finding, “…suggests that the psychosocial mechanisms of the spread of obesity may rely less on behavioral imitation than on a change in an ego’s general perception of the social norms regarding the acceptability of obesity.”

• Christakis NA, Fowler JH. 2007. “The spread of obesity in a large social network over 32 years.” New England Journal of Medicine. 357(4): 370-379.

With the stock market in decline, the credit crunch hovering over, and the fear of a recession growing, I think its time for some Friday humor.

I’ll let personal finance guru Michael Scott of the TV show The Office show us all how to declare bankruptcy.

According to Insurance and Technology, health insurer WellPoint has partnered with Zagat’s Survey to allow WellPoint’s members to rate their doctors.  Zagat’s will use its 30 point rating system to evaluate all doctors.  According to Spirit magazine, patients can grade doctors based on “including doctor availability, office environment, trustworthiness, and communication.”

Other websites, such as RateMDs.com, already offer patients the ability to rate doctors, but WellPoint is the first health insurer to offer this service to its members.

People who are sick are not able to shop around for medical care.  This statement may be true in some cases, but not for the majority of illnesses.  Those without insurance are especially sensitive to the price of medical care and are in fact very likely to shop for the combination of the lowest price, best quality care they can afford.

The RNCentral website gives some tips to the uninsured regarding how they can increase their access to care, improve the quality of care they are receiving, and reduce their out of pocket expenditures.  One interesting company is TelaDoc.  This firm provides a service which enables patients to phone a doctor 24 hours a day, 7 days a week to receive diagnosis and treatment information.  While TelaDoc won’t cure cancer, it will help patients to find the correct treatment for minor illnesses.

The latest edition of the Health Wonk Review is up at Joe Paduda’s Managed Care Matters website.

In Mexico there is a government program named Oportunidades which gives families cash payments if their children go to school, get vaccinated, and have regular health checkups.  The program has been a success and similar conditional cash transfers (CCTs) programs are being run in Nicaragua, Brazil and New York City.

New York City?  Should the NYC government pay for local children to go to school?  On the one hand, this will likely increase school attendance and decrease the number of drop outs.  On the other hand, the government is paying residents to do certain actions which seems to be a very paternalistic attitude.

The Economist  reports (”When bribery pays…“) that CCTs have been used in other settings as well:

Offering cash to change long-term bad habits, such as smoking or over-eating, has not worked. But disbursements tied to short-term transactions, such as getting drug addicts to take treatments for tuberculosis or depressed patients to see their psychiatrists, have already shown promise.

While paying children to go to school is not in and of itself a bad idea, I am concerned that the government will continue to pay people to do things that it thinks are in its best interest.  If we want to decrease inequality in society, it would be much better to increase cash transfers to the poor and allow them to decide for themselves what they should do with the money.

Vaccination is one of the most cost effective medical treatments we have.  It is important that providers vaccines in a timely manner.

In attempt to streamline vaccine distribution systems, the CDC created Vaccine Management Business Improvement Project (VMBIP).  Instead of having providers place orders with the grantee (i.e.: state health department), and then having the grantee ship them to a local distributor, VMBIP is an attempt to reduce warehouse costs by shipping vaccines from a centralized warehouse directly to the provider.  This may save money, if the vaccines are sent in a timely manner.

My presentation at the National Immunization Conference analyzed some data from southern California providers and found that the time from the vaccine order being place to delivery increased from 1.6 work days to 13.5 workdays after VMBIP was implemented.  I received other anecdotal evidence that these delays were affecting the vaccine supply of many California providers, but I did not know how efficiently the VMBIP program was operating in other states.

I found that California’s 13.5 day delay may not be so bad compared to the rest of the country.  One nurse from Texas said that vaccines delivery could take as long as 6 weeks.  There was significant variability so that the clinic would run out of vaccines occasionally so would have to place their orders early.  Sometime the vaccines would arrive within 2 days, but since the provider had anticipated a 2-4 week delay, there was no room in the refrigerator to store the vaccine.

Another conference attendee explained to me her experience in Minnesota.  Vaccines must be stored at a certain temperature to ensure they do not spoil.  Some winter days are so cold in Minnesota that the state public health department would advise distributors not to ship on those days to insure that they would not freeze.  Under the new, centralized VMBIP system, the national warehouse–which is run by McKesson–was not sensitive to these regional variations.  Minnesota providers have received frozen vaccines since McKesson did not know about how Minnesota winters effect vaccines.  These frozen vaccines are completely useless and must be discarded.

Overall, I doubt that centralized vaccine distribution is a good model.  Wal-mart can operate a centralized distribution system because all the stores are on the same computer network, they work under the centralized location, and receive extensive logisitcs training.  Further, Wal-mart is a hierarchical organization.  On the other hand, physicians are not integrated into a public health IT database–VACMAN not withstanding.  Further, providers are well trained on medical issues, but not logistics or filling out forms.  Since vaccine distribution is not a hierarchical system, a more flexible, less centralized, system would likely be optimal.

I would like to thank all the people who attended my presentation today at the National Immunization Conference and all the helpful feedback I have received.

I will be in Atlanta for most of this week attending the National Immunization Conference. If you are interested in seeing me present my work regarding the efficiency of the Vaccine Management Business Improvement Project’s new distribution system for the Vaccines for Children (VFC) program, my talk will be on Wednesday at 9am.

Blogging will resume later the week.

Merrill Goozer reports (”CMS okays heart scan…“) on how Center for Medicare and Medicaid Services (CMS) has reversed a policy to stop paying for heart scans.  There has been no clinical evidence to show that these expensive heart scans identify heart disease any better than less expensive procedures (i.e.: stress tests).

Physician revenue, however, would be hurt by this decision and after extensive lobbying, CMS has decided that paying for heart scans may be a good decision after all.  In the words of Merrill Goozer: “Pay first, evidence later. It’s the American way.”

Michael Cannon reports (”Pennsylvania Proposes to Defraud Non-Pennsylvanians“) that Pennsylvania is manipulating the Medicaid system.  Pennsylvania is increasing Medicaid payments to hospitals (thus increasing the amount of federal matching funds) with one hand, but with the other is creating a tax on “profits of general hospitals in two counties, Allegheny [Pittsburgh] and Philadelphia.”

Thus, the hospitals will be left with the same profit level–higher Medicaid payments will be eaten away by the special tax levy–however, Pennsylvania will have to pay a lower percentage of the cost because of the additional matching funds.  Who is hurt?  Only the taxpayers in those other 49 states.

Mr. Cannon analyzes the situation more acerbically: “…the federal Medicaid program allows Pennsylvania to siphon money away from other states.  That sound you hear is your pocket being picked.”

Darkness at Noon by Arthur Koestler is a unique novel which describes the imprisonment of Communist revolutionary Nicholas Rubashov. Rubashov was a loyal supporter of the Communist cause in Russia, but his subsequent imprisonment on bogus charges causes him to reflect on whether his fight to bring Communism to Russia was truly beneficial to Russian society. The book demonstrates how Communist idealist notions became perversions as Stalin took power and instituted a cruel dictatorship.

One of the main themes of the book is that philosophical generalizations and abstract ideals often lead to disastrous results when they are applied without regard to individual circumstance. As Ferdinand Lassalle once said:

‘Show us not the aim without the way./ For ends and means on earth are so entangled/ That changing one, you change the other too;/ Each different path brings other ends in view.’

One passage from the book may be particular applicable to economists whose solutions to mathematical problems may not prove to be fruitful in the ‘real-world’.

‘A mathematician once said that algebra was the science for lazy people–one does not work out x, but operates with it as if one knew it. In our case, x stands for the anonymous mases, the people. Politics mean operating with the x without worrying about its actual natures. Making history is to recognize x for what it stands for in the equation.’

Are you a bibiophile? Are you always on the lookout for a good book recommendation?

If this is the case you should try GoodReads. The website is a social networking site like Facebook or MySpace. Instead of using a social network to keep up with friends or the latest gossip, GoodReads allows users to list the books they have read and give them one to five stars. You can write a book review as well.

If you invite your friends to the site, you can see which books they rated highly. Perusing your friend’s 4 and 5 starred reviews, you will have long list of great books to read in the future.

Many reform advocates have claimed that the federal government should mandate a package of insurance benefits that all private and public health insurers would be legally compelled to provide. Switzerland is one country in which the government defines a what the insurance benefit will be for all standard health insurers. The National Coalition on Health Care also proposes “…requiring insurers to establish explicitly separate premiums for the core benefit package.” Is having the federal or state government mandate a minimum benefit package a good idea?

Cons

Most neo-classical economists would say that having the government mandate an insurance package is a bad idea. Regulation restricts choice. If consumers would prefer an insurance company to cover mental illness and another person would prefer their insurance company have more generous coverage for cancer treatment, then it would be welfare destroying to eliminate the individual’s choice. Even if regulators were able to determine an ‘optimal’ benefit package–even a benefit package deemed optimal for society is unlikely to be optimal for each individual–this optimality could only be achieved in a static setting. When new medical technologies and procedures became available would they be adopted? Adopting unproven medical technologies may not increase quality of care, but would increase the cost of premiums. Adopting technologies too late will harm the sick patients who could benefit from these advances.

Another issue is who would be deciding which procedures are included. Whether it is Congress or a medical “Federal Reserve,” these groups would be influenced by lobbying from the AMA, pharmaceutical companies, and patient interest groups. Further, Congressmen will have their own favorite diseases that they will include in the basic coverage plan, even when funding coverage for these diseases may not be as beneficial as for other diseases.

Pros

One benefit of the standardized medical package is that people would better be able to comparison shop. Currently, it is nearly impossible to determine what your insurance company covers unless you are an expert. With a mandated core benefit package, insurance companies would only be able to compete on the dimensions of price, service, and reputation. They would be no competition with regards to which procedures were covered. Also, this would help to attenuate the problem of adverse selection. Many insurers currently do not offer generous coverage since they know by doing so, they will attract the sickest individuals and likely decrease their profits.

Further with a standard benefit package there should be lower legal costs for both the insurance companies and patients. With a clear core benefit package, litigation would not be eliminated but it would certainly be curtailed since much of the payment ambiguity would be cleared up.

Supplemental Insurance

Regardless of whether or not you prefer a minimum insurance benefit, the government should allow supplementary insurance markets to exist. In this way, those who prefer more generous coverage could purchase additional insurance. Further, it is likely that supplemental insurance would be the first-adopters of new technology and could provide a testing group as to whether or not a new medical treatment should eventually be included into the core benefit package.

The very cleverly formatted March Madness edition of the Cavalcade of Risk has been posted at Regulating Health Insurance.

This website received both a #2 and a #6 seed. Henry Stern of Insure Blog deservingly received a #1 seed for his insightful piece on Alzheimer’s disease. Would you get a genetic test for a predisposition to Alzheimer’s knowing that there is no known cause of Alzheimers, and that there is no cure for Alzheimer’s?

My March Madness upset special is the fifth seeded Colorado Health Insider. This post discusses the pros and cons of Congress’ decision to compel insurance companies to put mental health coverage on equal footing with physical health coverage.

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.”

Megan McArdle has an interesting post (”Putting a price on health care“) about a U.S. single payer system.  If a smaller country like Switzerland decided to have a single payer system, this likely would not create too large a distortion regarding prices or innovation.  The U.S. would still have a (somewhat) private health care and the Swiss could learn the prices they should charge for different medical procedures.  Also, the Swiss don’t have to worry about testing out innovation.  The U.S. can advance new technologies.  If the new medical procedures are valuable, the Swiss will adopt them.  If not, the Swiss won’t.   Of course, basic research in universities can provide much medical innovation, but if there is price control in a single payer system, innovation from private firms would likely decrease.

McArdle notes:

“Europe’s governments operate their health care systems in the context of an existing US market that provides information about demand for new treatments (and of course I would argue, also the new treatments). They don’t use that price information to set what they pay for drugs, but it does filter through to their markets–for example, more widespread use of Herceptin for breast cancer in the US is putting pressure on the British government to provide it. I think an American shift to single-payer would be more problematic than the European example for a variety of reasons related to our government structure. But one important reason is that if we did, we’d have no where left to get prices from.”

TechCrunch reports on a Facebook application that alerts potential donors to donate blood in times of shortage.  Take all Types (TAT) is the name of the innovative non-profit which invented this application.  The TAT website wisely states:

“There are always shortages of blood throughout the nation, even though there are plenty of potential donors out there. After All, we all have blood we can share. The main issue is communication!“

If you were offered an actuarially fair lump-sum payment, would you give up half of your Social Security benefits? This is the question asked by Brown, Casey and Mitchell in their 2008 NBER working paper.

Overall, about 60% of respondents from the HRS data set preferred the lump-sum payment. The authors find the following individuals are more likely to prefer a lump-sum payment over the annuity:

• those with shorter expected longevity or who are in poor health,
• those with more education,
• those with less financial sophistication conditional on education,
• those who believe Social Security benefits will be cut.

Predictably, individuals who think they live longer will choose the annuity since they will get paid over a longer period of time. We also see that those who believe that there is significant political risk (i.e., Social Security benefits will be cut) are more likely to choose the lump-sum benefits.

Men aged between 63 and 67 have only 5% of their assets in private annuities. People have claimed that this was due to one of the following reasons:

• Adverse selection leads to high load factors on annuities, making them a poor value.
• Because they are made up of a fixed payment, Annuities are subject to inflation risk.
• Social Security may be a substitute for private insurance annuities.

The study finds evidence to contradict all three of these hypotheses. Social security benefits are actuarially fair, and inflation-adjusted. If people really benefited from Social Security annuities, than they should be hesitant to give up this stream of payments. Yet three of five people still would prefer a lump sum payment over the Social Security annuity, a type of annuity that offers significant advantages over those offered in the private market.

Maybe Social Security isn’t as valuable as once thought.

• Brown JR, Casey MD, Mitchell, OS. 2008. “Who Values the Social Security Annuity? New Evidence on the Annuity Puzzle,”NBER WP #13800.

Why do people want to lose weight? While this seems like an obvious question, it does merit answering. There are two major reasons: health concerns and appearance. Being obese increases the risk of suffering from many diseases (e.g.: diabetes). On the appearance side, individuals may experience social pressure to lose (or possibly gain) weight. Further, individuals may want to maintain a healthy body appearance to attract a mate.

Jeffery Sobal is an expert in obesity studies. According to his 2003 study, activities which directly affect weight are caloric intake, physical activity and smoking.

One of the more interesting questions is how an individual’s marriage status affects obesity. It is generally found that–even controlling for age and other covariates–married individuals are more likely to be overweight than non-married individuals. Why is this the case. Sobal cites some studies which attempt to explain this.

• Entering into marriage results in higher food intake. Craig & Truswell (1988).
• Marriage may change the physical activity level of the individuals. Some studies find that married individuals are more active (King, Kiernan, Ahn, & Wilcox 1998) other that they are less active (Myers, Weigel, & Holliday 1989, Verhoef, Love & Rose 1992), and still others find no relationship between marriage and physical activity (Hirvensalo, Lintunen & Rantanen 2000, Umberson 1992, Van den Hombergh, Schouten, Van Staveren, van Amelsvoort, & Kok 1995.).
• Smoking has been found to be correlated with lower body weights. Two studies (Venters et al. 1989, Waldron & Lye 1989) have found that married individuals are less likely to smoke than single, divorced, or widowed individuals. Two other sutides found that people who enter marriage are more likely to stop smoking (Waldron & Lye 1989, Wee, Rigotti, Davis & Phillips 2001).
• Umberson 1992 found that after 3 years, Americans who exited marriage had lower weights than those who remained married. In a six year study, Finnish individuals who got married gained weight and those who were widowed lost weight (Rissanen, Heliovaara, Knekt, Reunanen & Aromaa, 1991). Three studies by Kahn and Williamson use a 10 year panel of U.S. residents and find individuals gained weight upon entering marriage and lose weight upon exiting marriage (Kahn & Williamson 1990, Kahn & Williamson 1991, and Kahn, Williamson and Stevens 1991). These findings hold for both men and women in these two studies.
• While most studies do find that married individuals weight more than nonmarried, there are some subtleties to this statement. A paper by French et al. 1993 using 2-year data on US men and women found that women gained weight after they married, but men did not.

After citing all this evidence, Sobal and co-authors state 4 hyptotheses to test:

1. Marital trajectories that are stable are related to stable body weights,
2. marital trajectories entering marriage are related to weight gain,
3. marital trajectories dissolving marriage are related to weight loss,
4. marital trajectories involving the death of a spouse are related to weight loss.

Sobal uses data from from the National Health and Nutritional Examination Survey (NHANES I). A 10 year follow up survey of the participants is collected in the National Health and Nutrition Epidemiological Followup Survey (NHEFS). The authors use an OLS specification with a lagged dependent variable (i.e., lagged BMI) in order to estimate the impact of marital status on weight. Sobal, Rauschenbach and Frongillo conclude the following:

1. Stable marital trajectories were not associated with significant weight changes, except for weight loss among men who remained separated/divorced.
   
2. Marital trajectories involving entry into marriage were associated with weight gain among women, but not among men.
   
3. Marital trajectories involving dissolving marriages were associated with weight loss among men, but not women.
   
4. Marital trajectories involving death of a spouse were associated with weight loss among men, but not women.
   
5. Marital and other demographic characteristics were better predictors of weight loss than weight gain.

• Sobal J, Rauschenbach B, Frongillo EA., 2003. “Marital status changes and body weight changes: a US longitudinal analysis.” Social Science and Medicine, 56(7): 1543-55.

The latest edition of the Health Wonk Review is up at Workers Comp Insider.

VentureBeat (”…Health 2.0…“) profiles six innovative Health 2.0 firms which were at the 2008 Health 2.0 Conference in San Diego.  Each firm on the list aims to reinvent the doctor patient relationship.

Included on the list is Carol.com which allows patients to do medical shopping.  PharmaSurveyor allows users to enter the medications they are on and see if there are any harmful drug interactions.

There are lots of innovative ideas coming down the Health 2.0 pipeline.

William Easterly is a famous development economist at NYU. Yet in a 2007 paper in the American Economic Review, Easterly asks “Was Development Assistance a Mistake?”

Easterly first recounts how development economics conventional wisdom on how to end poverty has changed over time.

• 1950-1970s: Raising investment is the key to reducing poverty. “…[d]evelopment (i.e. economic growth) was a simple matter of raising the rate of investment to GDP, including public investments like roads, dams, irrigation canals, schools, electricity and private investment. However, private investment was usually not trusted to do enough or do the right things, and so there was a strong role for the state to facilitate and direct investment, guided in turn by the development experts.”
• 1980s: Washington Consensus. This policy “…called for removing price distortions, opening to trade, and correcting macroeconomic imbalances (mainly budget deficits). The slogan of the new wave was ‘adjustment with growth.’”
• 1990s: New Growth Literature. Here economists would would use hundreds of right hand side variables and regress them on growth in order to find the determinants of economic growth. “Durlauf, Johnson, and Temple (2005) pointed out that 145 different right hand side variables were significant as determinants of growth in various studies with around 100 degrees of freedom.”
• 2000s: We don’t know. In 2005, the World Bank states that “different policies can yield the same result, and the same policy can yield different results, depending on country institutional contexts and underlying growth strategies.” The Barcelona Development Agenda proclaimed that “there is no single set of policies that can be guaranteed to ignite sustained growth.”

So how does Easterly sum up the contribution of development economists to the world?

“In sum, we don’t know what actions achieve development, our advice and aid doesn’t make those actions happen even if we knew what they were, and we are not even sure who “we” are that is supposed to achieve development. I take away from this that development assistance was a mistake.”

In fact, Easterly likens development economists advice to that of a communist central planner.

“The 20th century’s first development economist may have been Lenin, who wrote a famous pamphlet in 1902 called ‘What is to be done?,’ and said that the revolutionary intelligentsia had the answer. A long line of such diverse thinkers as Edmund Burke, Karl Popper, Friedrich Hayek, Isaiah Berlin, and James C. Scott have criticized the idea that experts can re-design society, all the way back to the French Revolution, and the catastrophic outcomes of the more extreme attempts to do so supported these criticisms. Yet the unquenchable demand for experts who can call tell “us” the right answers shows no sign of ending soon.”

How much money do you need to save for retirement?  $100,000?  $500,000?  $1,000,000?   $5,000,000?

Well whatever your figure is, you need to tack on an extra quarter of a million dollars in order to cover your health care costs in retirement.  The Boston Globe (”Fidelity…“) reports that Fidelity now estimates that a couple will need to have saved $225,000 in order to pay for health care costs during retirement.  When Fidelity initially conducted this study in 2002, the figure was $160,000, which means necessary savings for health care in retirement has increased by almost 6% per year.
You may think that Fidelity’s numbers are biased upwards since Fidelity has an interest in making people save more money (they make a commission off their investments).  Boston College’s Center for Retirement Research also conducted a similar study, however, and found that  a couple will need to have saved at least $206,000.

These figures are extremely high, especially considering that they take into account the fact that all of these people will be covered by Medicare.  According to BC’s Center for Retirement Research currently 60% of older workers are “at risk” of being unable to maintain their standard of living in retirement.

[Hat tip to New Health Dialogue blog]

Are smart people risk averse? Are dumb people impatient?

This is what Thomas Dohmen, Armin Falk, David Huffman, Uwe Sunde explore in their 2007 Discussion paper. Using data from a choice experiment of 1000 German adults, the authors tested for risk aversion using a Holt & Laury framework, and for impatience by varying the annual rate of return for a €100 investment. It is necessary to test the risk aversion and impatience parameter separately because in expected utility theory (EUT), a more concave utility function will cause more impatient choices, holding constant the discount rate. Cognitive ability was measured using questions similar to those on the Wechsler Adult Intelligence Scale (WAIS).

The authors found that individuals with higher cognitive abilities are less likely to be risk averse. Further, those who scored higher on the WAIS are significantly less impatient. This finding is true even after controlling for income, education, and credit constraint co-variates.

According to the authors:

“The paper also points to a different interpretation of reduced form models that have been estimated in the literature on cognitive ability and labor market outcomes. These models have typically included a measure of cognitive abilities, but not risk aversion or impatience, as explanatory variables (e.g., Cawley et al., 2001). Outcomes such as educational attainment or wages may by affected by risk aversion and impatience, and thus part of the impact of cognitive ability may reflect the correlation with these traits. In other words, our findings point to a potentially important source of omitted variable bias in this type of estimation.

Given that cognitive ability is known to be transmitted from parents to children, our findings could also be relevant for the literature on intergenerational transmission of preferences and socio-economic status.”

• Thomas Dohmen, Armin Falk, David Huffman, Uwe Sunde, 2007. “Are Risk Aversion and Impatience Related to Cognitive Ability?” IZA Discussion Paper No. 2735.

The Regulating Health Insurance (RHI) blog today named Healthcare Economist as their Blog of the Week for my post on “Doctors, Patients, and the Racial Mortality Gap.” The RHI Health Blog of the Week is awarded to an exceptional health-related post appearing during the previous week.

Other RHI Blog of the Week winners can be found here.

Seat belts save lives. At least conventional wisdom says so. But is this really the case?

Seat belts are useful because the reduce the chance that–given that you are in an accident–you will die or sustain a serious injury. But wearing a seat belt may give drivers an incentive to drive more recklessly since the driver may believe that accidents are not as dangerous. Thus, seat belts may increase accidents but reduce injuries when people are in accidents. The net benefit may be ambiguous.

An Economist magazine article (”A hazardous comparison“) expands on this and other safety issues.

In one experiment, a British psychologist, Ian Walker of Bath University, simply got on his bicycle and monitored the behaviour of 2,300 vehicles that overtook him. When he wore a helmet, drivers were much more likely to zoom past him with little room to spare; when he was bare-headed (and indeed when he wore a female wig) the amount of space that motorists left would increase. An experiment in Munich found that the drivers of taxicabs fitted with anti-lock braking systems were involved in no fewer accidents than those without. That is because the former used those superior brakes not to practise prudence but to drive more aggressively.

Such unintended effects are not confined to Europe. John Adams, a transport expert at University College London, has compiled data from all over the world to show that laws making drivers wear seatbelts do not make roads safer; they move deaths from inside cars to outside them because they encourage bad driving. The number of young children killed on the roads has fallen in recent years, he notes—but mainly because they are rarely allowed out alone, so today’s teenagers have less skill at navigating hazardous roads; and as a result, the number of teenagers killed in car accidents has jumped. He lauds the Dutch experiment in “naked streets” where most road signs and markings were removed to force travellers to keep their wits about them.

Joe Paduda has a great post (”Wasted Dollars“) reviewing a study by Alex Swedlow. The study focuses on waste in the health care sector with a focus on Workers Compensation. Mr. Paduda concludes the following:

There’s a lesson here for the non-workers comp world, and policy wonks in particular. It is this - providers overtreat, to the detriment of the patient and the payer. Draconian measures such as flat limits on the amount of treatment do work.

With health reform on the horizon, here’s a great example of the waste in our health care ’system’, waste that benefits the provider.

Paduda claims that Draconian measure work.  They key is that policymakers/bureaucrats set these limits at an economically efficient amount.  If the medical care becomes too limited (e.g.: the number of doctors visits allowed is below the optimal level for many patients) then patient care could be hurt.  If the limits are too high, than there may be no cost savings.

In the California Workers Comp example, Paduda says regulators got it right.

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.

Electronic medical records (EMR) hold the promise of vastly improving the quality of medical care received in the U.S. today. One of the major issues with EMR is privacy however. Patients generally want their doctors to know as much about their health as possible in order to make the best possible medical diagnoses and treatment decisions.

Yet who should you trust with your EMR? Physician groups are generally too small to efficiently implement EMR. Further, if you switch doctors, most patients want their EMR to follow them. What if the health insurers are put in charge of the EMR? This may make the most sense, but some health insurers can use the EMR to learn more about the health of their enrollees. While this seems like a good thing, when a certain enrollee gets sicker, they may decide either to increase their premiums or to try to drop their coverage. A clear conflict of interest exists here.

What about a third party EMR vendor? Google and Microsoft both are offering EMR services. But do you really want one of these enormous corporations selling your most personal medical information to other companies?

One solution to this problem is Keyose.com. Created by Dr. Julio Bonis, Keyose is a completely anonymous EMR service. Here’s how it works:

1. Users sign up and enter their personal health information.
2. A username code is generated along with a public and private password. The public password is printed on an ID card that doctors can use to access medical information. The private password enables users to update their medical information. Further, Keyose allows patients to use their private password to enter confidential medical information that people with the public password (e.g.: physicians) will not be able to view. This allows patients to manage their own health care information.
3. You do not enter personal data (e.g.: not your name or an e-mail) when you sign up in Keyose. Thus, you will not receive any marketing materials. Even if a hacker breaks into the system, they will not be able to match your medical information to your name or email.
4. Finally, it is free to sign up.

As you know, there is nothing in life that is free. How does Keyose plan to fund this project? According to their “Help” section:

In the future we could include information about sponsors (including private health insurance companies, pharmaceutical or biomedical industries) mainly intended for doctors who access the personal health records. We could also charge for premium services (for instance translating the personal health record for international patients or providing contextual information about a patient’s diseases).

There are drawbacks to this patient-based EMR. Patients do not use the same jargon as physicians and, thus, much important information could be lost in translation between the physician and the patient. Also, the information is uploaded by the patient, and not physicians, nurses, or trained staff.

I tried out Keyose myself. It was pretty basic and could have used more pre-defined fields (currently there is only DOB, gender, blood type, allergies, and personal and family history). Specific fields detailing whether or not you have certain allergies, or whether you have received certain vaccines would be helpful. Also, I could view the confidential information section even when I logged in using the public password.

Nevertheless, Keyose does seem like an step in the right direction.