May 2009

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Letter to Obama: We’re gonna save $2 trillion

May 11, 2009 in Public Policy, Supply of Medical Services | 3 comments

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

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

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

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

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

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Unintended Consequences: Brazil’s Bolsa Família Welfare Program

May 11, 2009 in Public Policy | 1 comment

Brazil’s Bolsa Família program has been help up as one of the great social welfare programs.  It has been a model for Mexico’s own Oportunidades social welfare program.  

The Wilson Quarterly reports that the 44 million poor Brazilians who participate in this program receive payments of up to $104 a month for sending their children to school, getting them vaccinated, and sending them to health clinics.  These are large amounts since these families on average earn less than $73 month.  It has been shown that the program has increased vaccination rates and school attendance. 

However, the Bolsa Família program may not be as inocuous as it seems.  Anothony Hall (2008) documents that these grants have been used in some areas to buy votes.  Further, spending on Bolsa Família has crowded out other social spending programs.  For instance, federal spending on basic sanitation and housing fell in real terms by 46% between 2002 and 2004.  Finally, the Bolsa Família may draw people towards working in the informal sector.  Formal sector employment may make a family ineligible for the Bolsa Família grants.  São Paulo’s informal sector doubled in size (to 51%) between 1991 and 2004.  

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“Chained to Jobs they hate by health coverage they can’t afford to lose”

May 9, 2009 in Uncategorized | 1 comment

A humorous take the serious problem of job lock.

Rushing to produce a Swine Flu Vaccine: A Cautionary Tale

May 8, 2009 in Uncategorized | No comments

The Washington Post recounts a cautionary tale concerning a hasty roll-out of the flu vaccine this fall.

“As U.S. health officials consider rolling out a plan to inoculate the nation against swine flu in the next several months, they are haunted by the events that unfolded the last time the government stepped in to head off a surprise flu outbreak.

In the fall of 1976, dozens of Americans died within 48 hours of receiving a swine flu vaccine. To allay the public fears that threatened to unravel the mass inoculation program, President Gerald Ford rolled up his shirtsleeve and received his shot in front of the television cameras.

More than 40 million others followed his lead. But two months later, the campaign was abruptly stopped: More deaths had followed and hundreds were reporting serious side effects, including paralysis. “

How did the national debt get so big?

May 8, 2009 in Public Policy, Taxes | 3 comments

The book Cadillac Desert discusses the development of dams, aquaducts, and irrigation canals to slake the thirst of cities and farmers in the Western U.S..  While these projects did eventually deliver the water they promised, they did so at huge costs to taxpayers.  In the words of former congressmen Robert W. Edgar:

“The old-boy network comes to you,” says Edgar, who was elected to the House of Representatives in 1974, at the age of thirty-one.  ”They say, ‘You’ve got a water project in your district?  You want one? Let us take care of it for you.’  Then they come around a few months later and get their pound of flesh.  You actually risk very little by going along.  You get a lot of money thrown into your district for a project that few of your constituents oppose.  In return, you vote for a lot of projects your constituents don’t know or care about.  Not many of my constituents are going to base their vote for or against me on whether or not I supported Stonewall Jackson Dam in West Virginia.  Then everyone wonders why we’re running such big federal deficits, and they cut the social programs, which must be the culprit.”

  • Robert W. Edgar, U.S. Congressman from 1975 to 1987.

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Why is the Jamaica Tourism Board Advertising?

May 7, 2009 in Economics - General | 3 comments

Recently, I have seen a number of commercials promoting tourism to Jamaica.  Why are these commercials running?

Let us assume that these commercials convince 2% of vacationers to go to Jamaica.  If this is the case, it would make more sense to advertise during boom times; 2% of a large number of vacationers is a bigger number than 2% of the current small stock of vacationers.  On the other hand, it is possible that advertising is more effective now since the advertising budgets from other countries have been cut.  

A final possibility is that the Jamaica Tourism Board is not profit maximizing.  It may have a target tourism level.  Achieving the status quo tourism level may be more valuable to Jamaica in order to maintain a more stable level of tourism-related employment. Does this mean that the Jamaica Tourism Board is not a fiscally sound organization or that–like many government organizations–it is simply acting to smooth the booms and busts that results from normal swings in the world economy?

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Regression Discontinuity

May 7, 2009 in Econometrics | No comments

Regression Discontinuity is an econometric method that has become popular in recent years.  Let me give you an example where regression discontinuity would be valid.  

Let us say that all students who score 1000 or more on their SATs matriculate at Ivy U and all students who score below 1000 attend college at State U.  The research question is what impact going to Ivy U has on wages.

If we simply compare the average salaries of those at Ivy U and those at State U, this will likely not reveal the true effect that Ivy U had on its graduates.  Those at Ivy U were likely smarter and more motivated than those at State U.  Thus, the impact of Ivy U’s education is confounded with the individual’s own talent and motivation.  

Regression discontinuity, however, can solve this problem.  If we compare individuals who scored just above and just below 1000, these individuals are likely very similar in terms of intelligence and motivation.  The only difference would the impact of Ivy U’s education and networking possibilities against State U’s.  We could compare average scores just above and below the 1000 mark.  However, we could also fit a polynomial function of test scores on wages with a discrete jump term at 1000.  Mathematically, this means the following:

  • Effect = limx↓c E[Yi|Xi=x]  -  limx↑c E[Yi|Xi=x]
  • In this example, Yi is the wages, Xi is the test scores, and the the cutoff value, c, is 1000.

Can we use Regression Discontinuity to estimate the impact of school districts on schooling?  We could compare houses on each side of the school district boundaries and then see if these similar houses have different test scores.  However, this will likely not produce reliable results if parents choose their house based on the school district.  Thus, even if two identical houses are right next to each other, if high achieving parents always choose the better school district, then there will be perfect sorting between school districts.

David S. Lee and Thomas Lemieux (2009)  have a great “user guide” about how to use Regression Discontinuity in practice.  Some of their top tips are the following:

RD designs can be invalid if individuals can precisely manipulate the “forcing variable”. 

  • In the school district choose example, where parents can precisely choose their school district RD may be invalid.

If individuals – even while having some influence – are unable to precisely manipulate the forcing variable, a consequence of this is that the variation in treatment near the threshold is randomized as though from a randomized experiment. 

  • Intuitively, when individuals have imprecise control over the forcing variable, even if some are especially likely to have values of X near the cutoff, every individual will have approximately the same probability of having an X that is just above (receiving the treatment) or just below (being denied the treatment) the cutoff – similar to a coin-flip experiment.  This is the case of people who score around 1000 on the SAT and thus have an approximately equal probability of getting into Ivy U or State U.

RD designs can be analyzed – and tested – like randomized experiments.

  • If variation in the treatment near the threshold is approximately randomized, then it follows that all “baseline characteristics” – all those variables determined prior to the realization of the forcing variable – should have the same distribution just above and just below the cutoff.

Non-parametric estimation does not represent a “solution” to functional form issues raised by RD designs. It is therefore helpful to view it as a complement to – rather than a substitute for – parametric estimation.

  • Parametric functions are what are traditionally used.  These are generally polynomial that regress the dependent variable of interest onto the X variable.  In my example, this would be a polynomial regression with future wages as the dependent variable and test scores as the independent X variable.  Non-parametric estimation techniques include local linear regression.

Goodness-of-fit and other statistical tests can help rule out overly restrictive specifications.

  • Although there is no simple formula that works in all situations and contexts for weeding out inappropriate specifications, it seems reasonable, at a minimum, not to rely on an estimate resulting from a specification that can be rejected by the data when tested against a strictly more flexible specification. For example, it seems wise to place less confidence in results from a low-order polynomial model, when it is rejected in favor of a less restrictive model (e.g., separate means for each discrete value of X). Similarly, there seems little reason to prefer a specification that uses all the data, if using the same specification but restricting to observations closer to the threshold gives a substantially (and statistically) different answer. 

Citation

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Spend more time eating, Weigh Less

May 6, 2009 in Obesity | No comments

According to Economix, countries whose people spend more time eating have a lower obesity rates.

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Cavalcade of Risk – May 6 edition

May 6, 2009 in Carnivals | No comments

The Tax Update Blog literally puts out fires in the latest edition of the Cavalcade of Risk.  My favorite posts include:

Any my favorite, Arnold’s Kling’s quotation on Medicare reform:

Saying, “We don’t need to have any restraint on the use of medical services. Look at Medicare” is like saying, “We don’t have to worry about the fish population. Look at all the fish we just caught.”

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Are health insurance markets competitive?

May 6, 2009 in Health Insurance | 2 comments

The answer: sometimes.  A study by Dafny (2009) finds that in markets with ten or more insurers, markets do seem to be competitive.  However, with six or less insurers, health insurers do have some market power due to switching costs.

“Using data on ‘fully insured’ health plans offered to employees of 184 publicly-held firms in over 100 geographic markets in the United States for the years 1998 to 2005, she finds that increases in company profits are associated with increases in health insurance premiums, but only in geographic markets served by fewer than ten major insurance carriers. In the most concentrated markets — those with six or fewer carriers – a 10 percent increase in company profits is associated with a 1.2 percent increase in health insurance premiums..

Further analysis suggests that in order to get lower rates, employers must be willing to change health plans. A plan switch is a ‘tough sell’ in good times because employees must identify in-network providers, transfer medical records, and figure out the claims reimbursement system. The data reveal that employers are ‘especially reluctant to drop health plans when profitable, a finding that supports the hypothesis that profits act to raise employers’ switching costs.’“ 

I would predict that integrated health IT and more regulation of minimum benefit levels could reduce switching costs.  However, increased minimum benefit levels will also drive up premiums.  I predict that switching out of integrated health delivery systems such as Kaiser Permanente would involve much higher switching costs for employees, since most Kaiser doctors are employed directly by the insurance company.  Thus, the patients would have to switch primary care providers (PCP) if their employer changed coverage.  On the other hand, switching between PPOs or less integrated HMOs might involve less switching costs since a patient’s PCP likely would accept insurance from a variety of health plans. 

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