February 2009

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Injured Veterans

February 19, 2009 in Current Events, Public Policy | No comments

One health risk factor often overlooked in this blog is going to war.  Veterans from the wars in Iraq and Afghanistan frequently return home with traumatic brain injury from roadside bombs, post-traumatic stress disorder (PTSD),  and other injuries.  

Marketplace chronicles the problems veterans experience trying to collect military benefits after returning to civilian life.  The article reports that it can be difficult for Veterans to claim indemnity benefits.  

Soldiers given a military disability rating below 30 percent get a one-time severance payment instead of life-long medical benefits for the whole family. Kerry Baker — with the Disabled American Veterans — says the army cherry-picks lesser injuries when applying its disability standards. In military-speak, disabilities are referred to as “unfitting conditions.” That’s any injury that prevents soldiers from performing their duties.

Further, getting medical care at the VA is difficult during wartime.  The VA has a “backlog for disability claims is in the hundreds of thousands.”

The human and financial cost from war does not end at the close of combat.  These issues will linger on for years to come.

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Does “Just say no” work?

February 19, 2009 in Public Policy | 1 comment

Some of the biggest public health problems involve the use of drugs in alcohol.  Individuals use drugs and alcohol because they receive some psychic benefit.  However, this has a cost to their own health and often the health of others (e.g., drunk driving, increased homicide rates).  Whether or not the government should be involved in convincing people not to drink, smoke or take drugs is one question.  Another is whether it actually effective.

A paper by Hornik et al. (AJPH 2008) examines the effect of the National Youth Anti-Drug Media Campaign between 1999 and 2004.  The paper finds that ad campaigns like “Soccer: My Anti-Drug” generally had no effect on drug or alcohol use.  However, the campaign did seem to slightly increase marijuana use.  

Why does advertising not work?  Most people already know about the health costs of drugs, alcohol and smoking.  Thus, advertisements do not serve to change the public perception.  Any government who wants to start a advertising campaign against trans fat in order to reduce obesity must contend with the fact that most people already know which food are and are not good for them.  Thus, this type of advertisement likely has little impact.

Should public health officials just give up on stopping people from using drugs and alcohol?  Maybe not entirely.

The Economist cites the health benefits of Mikhail Gorbachev’s anti-booze campaign.  ”Mr Gorbachev’s anti-booze campaign—although hugely unpopular—raised life expectancy by fully three years between 1985 and 1987. After 1992 the state monopoly on alcohol (and health checks on its quality) collapsed. As anybody who lived in Russia at the time will recall, the effect was spectacular—and catastrophic. Death rates returned to their long-term trend.”

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Health Wonk Review is up

February 19, 2009 in Carnivals | No comments

The “Anti-spam” edition of the Health Wonk Review is up at Hank Stern’s InsureBlog.

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Unmeasured Outcomes in Quality Reports

February 18, 2009 in Quality | No comments

Pay-for-performance (P4P) has long been tauted as a means to improve quality.  However, since the Holmstrom and Milgrom (1991) paper on multitasking, it has been known that compensating individuals on one measured dimension can compel them to substitute effort away from unmeasured dimensions.  For instance, if a mortgage broker is compensated only for the number of new mortgages he secures and not the credit worthiness of the borrower, it is likely that they will bring in borrowers with bad credit.  In the healthcare setting, compensating doctors to do certain tests (e.g., test A1C levels) may increase the probability the doctor conducts the A1C test for diabetics, but may decrease the amount of time the physician dedicates towards counseling the patient to lose weight or stop smoking.

A paper by Glzer, McGuire and Normand (2008) tries to remedy this problem.  Take a look at the following Table.  We see that discharges one and two are observable and can be measured.  On the other hand, discharge 3 is unmeasurable.  For instance, discharges one and two could represent patient mortality with respect to different types of cardiac operations.  On the other hand “Discharge Three can be thought of as representing medical discharges associated with Skin, Subcutaneous Tissue, and Breast Disorders, for which in-hospital mortality is very low, that mortality would not be a feasible (or even valid) measure of quality.”

How should the hospital weight the overall quality score between outcomes one and two.  The authors of this paper claim that more weight should be placed out outcome one.  Why?  

Discharge one and three have the same inputs.  Thus, putting more weight on discharge one, will compel the hospital to increase inputs associated with a better outcomes associated with discharge one.  Since discharge one and three share inputs, this will lead to an increase in quality improvement for discharge 3.  For instance, an increase in nursing staff or computerized records may increase productivity for multiple observed an unobserved outcomes.  On the other hand, if discharge 2 depends on the purchase of a machine that test for only one condition, less weight should be placed on high levels of discharge 2 since there are less spillovers.

A necessary condition for this type of measurement to work is that all inputs must be used in at least one of the observable discharge types.  Further complications arise from the fact that, not all providers use the same inputs to treat patients with the same disease.  Also, “…the existing evidence supporting commonality is too general to be usable yet as a basis for modifying profile construction.”  

Nevertheless, thinking about how quality improvements can spillover to other treatments is an important framework to have whether policy-makers are creating P4P metrics.

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GM Healthcare Costs

February 17, 2009 in Current Events | No comments

Today, G.M. and Chrysler must submit a government-mandated recovery plan to Congress.  The N.Y. Times reports that G.M is trying get the United Auto Workers to agree to cutback in its employee and retiree health care benefits.  ”[G.M.] has to address how a company that lost more than $20 billion last year can afford $5 billion a year in medical bills.”  Five billion dollars in medical costs seems like a lot, but how much is it really?

According to the Kaiser Family Foundation, Medicare expenses in the following states were less than $5 billion in 2005:

  • Alaska, Arkansas, Colorado, Connecticut, Delaware, District of Columbia, Hawaii, Idaho, Iowa, Kansas, Kentucky, Maine, Minnesota, Mississippi, Montana, Nebraska, Nevada, New Hampshire, New Mexico, North Dakota, Oklahoma, Oregon, Rhode Island, South Carolina, South Dakota, Utah, Vermont, Washington, West Virginia, Wyoming.

Wow.  I couldn’t believe this either when I compared the numbers.  The N.Y. Times article continues stating “ [G.M.'s] future obligations for retiree health care are estimated at $47 billion, and by next year it is required by its contract to contribute more than $10 billion to the trust set up in 2007.”

This is certainly a tough situation.  G.M., Ford and Chrysler are on the hook for billions of current employee and retiree medical expenses.  On the other hand, retired Big 3 autoworkers who put in 30-40 years of service with the promise of life-time healthcare may now be left with limited or no medical coverage.

Like everyone in this economic recession, belt tightening is needed by all parties involved.

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New Job

February 16, 2009 in Miscellaneous | No comments

This past week, I have accepted a job offer to work as a Research Associate for Acumen, LLC.  Founded by Stanford Economist Thomas MaCurdy, Acumen is a contract research firm.  The firm specializes in program evaluation for Medicare and Medicaid. 

I am very excited about my new position and will begin full time work at the end of August.

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Partial and General Equilibrium in Toilet Flushing

February 15, 2009 in Economics - General | No comments

I have been traveling a lot lately doing flyouts for job interviews.  I was at an airport recently and forgot to flush the toilet.  Usually this is not a problem, since most urinals at airports are automatic flush toilets.  However, in this case the toilet was not an automatic flush toilet.  This got me thinking about the economics of automatic toilet flushers.

On average, individuals will flush the toilet with some probability, p.  If a toilet has an automatic flush mechanism, then the toilet will flush with probability 1.  Of course, not all toilets are automatic flush toilets.  Thus, if f percent of toilets are automatic flush, the increase in the probability of flushing a toilet is f*(1-p).

Chart

In a partial equilibrium setting, marginal effect of adding an automatic flush toilet increases flushing rates by 1-p. 

  • ∂[f+p(1-f)]/∂f = 1-p

So automatic flush toilets are a good thing right?  Probably, but maybe not as much as expected.  People may get used to having automatic flush toilets (as I did).  As the proportion of automatic flush toilets increases, this may decrease the probability that anyone flushes the toilet in the non-automatic setting since have become so  accustomed to having an toilet that flushes itself.

The probability of flushing a non-automatic toilet may depend on the proportion of toilets that are automatic flush.  In the general equilibrum, we can replace p, with p(f) where ∂p(f)/∂f<0). Now the impact of installing an automatic flush toilet is not as large. 

  • ∂[f+p(f)(1-f)]/∂f = (1-p)+(1-f)p’ 

What this equation says is that installing an automatic flush toilet increases the chance that a specific toilet flushes, but decreases the probability an individual flushes a toilet in a non-automatic setting.

Who would have thought that airport toilets could be so interesting!

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WEAI

February 13, 2009 in Economics - General, My Papers | No comments

My paper titled “Why Does Getting Married Make You Fat? Incentives and Appearance Maintenance” was just accepted for presenatation at the Western Economic Association International (WEAI) conference.  This paper is co-authored with Uri Gneezy.  The conference will take place June 29-July 3, 2009 in Vancouver, Canada.

Cost of Living II: Home Prices

February 13, 2009 in Economics - General | 3 comments

Be it rent or mortgage payments, paying for shelter is the largest after-tax expense for most people.  Differences in housing prices can greatly affect your purchasing power.  If you earn $50,000 in Wausau, Wisconsin, you will be able to afford a much larger house than if you lived in San Francisco.   Of course, living in San Francisco offers more job opportunities and amenitities than does Wausau.  

What is the price of a typical house in your metro area?  This chart reveals the median home price for 158 metro areas.  The prices are divided up between single family homes (SFH) and condominiums.  

Which cities have the most expensive median home prices?  Below are my rankings:

The most expensive metro areas to buy a home or condo are: San Francisco; Los Angeles; San Diego; New York; Washington, D.C.; Boston; Seattle; Boulder, CO; Miami.

The New York Times also has a nice graphic that better incorporates the recent downturn in housing prices, but is only available for select markets.  The data is derived from the Case-Shiller home price index.

Data Source:

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Cost of Living I: State Taxes

February 12, 2009 in Taxes | 11 comments

This June, I will finish my Ph.D. in Economics at the University of California, San Diego.  I am currently interviewing for a post-graduate employment and will likely move to another city.  Which city should I move to?  Of course, much of this has to do with personal preference.  Do you like warm weather or seasons?  City or rural?  Are there family considerations?  All these idiosyncratic issue certainly affect location choice.

However there is one issue that is important to all workers: taxes.  Most people prefer to live in a low tax state.  But what is a low tax state?  Texas has no income tax, but does has have a 6.25% sales tax.  Oregon has no sales tax, but does have an income tax of 8%-9%.  Although Maryland’s state income tax is low (around 4%), the local income taxes average about 3% of total income. Each state’s income tax rate depends on your tax bracket, plus there are state property taxes, estate taxes, etc.  This is getting complicated!

Fortunately, the Healthcare Economist has compiled a spreadsheet describing the tax rates of each state (see Table).  The data are from The Tax Foundation.  I have estimated the average tax rates in different states for individuals earning $60,000 and $100,000.  The aggregate tax rates include state and local income taxes as well as sales taxes.  The do not, however, include information on property taxes.

Which states have the highest tax burdens?  Take a look at my rankings:

I find that Alaska, South Dakota, Wyoming, New Hampshire, Delaware, and Montana have the lowest tax rates.  On the other hand, the states with the highest tax burdens are Maryland, California, Tennessee, Idaho, Minnesota, DC, and Kentucky.  

Different people are affected by different tax rates.  Retirees would prefer states with low sales tax and high income taxes.  Young workers saving in a for the future would prefer lowering income taxes rather than sales taxes.   Are taxes good or bad?  There is no shortage of opinion:

  • “There is no worse tyranny than to force a man to pay for what he does not want merely because you think it would be good for you.”  – Robert A. Heinlein
  • “Taxes, are the dues that we pay for the privileges of membership in an organized society.”  – Franklin D. Roosevelt 

Data Sources:

  • Sales Tax Data: http://www.taxfoundation.org/taxdata/show/245.html
  • State Income Taxes: http://www.taxfoundation.org/publications/show/228.html
  • Local Income Taxes: http://www.taxfoundation.org/files/localincometaxes-20080711.pdf

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