Unbiased Analysis of Today's Healthcare Issues

How much are you willing to pay to live an extra year?

Written By: Jason Shafrin - Aug• 18•14

Health Economists often use the cost per quality-adjusted life year (QALY) metric to answer this question.  QALYs are used to measure not only the additional years of life from a treatment, but also the quality of life.  For instance, you may prefer to live 1 year in perfect health to two years in a coma.  A QALY of 0.5 can indicate that the patient lived for 6 months in perfect health or for 1 year at a 50% health level.

Two popular methods to evaluate the value of a statistical life are stated preference and the value of a statistical life methods.

A first and direct approach is to ask respondents about their WTP for small health increases/QALYs using stated preference (SP) techniques such as discrete choice experiments or contingent valuation. The WTP estimates can subsequently be used to estimate the WTP for a gain in a full QALY. A second approach is to use the monetary value of preventing fatalities (the value of a statistical life), on which there is a substantial empirical literature, in order to implicitly derive the WTP-Q assuming a certain life expectancy (LE) and discount rate for the sample on which the value of life is derived.

Payers often used the cost per additional QALY to determine if a product is cost effective.  Countries often only approve reimbursement for a therapy if the cost per QALY falls below a certain threshold.  Ryen and Svensson (2014) write:

Threshold values often referred to in the literature and policy debates include the US value of US$50,000 to US$100,000 (approximately €37,500 to €75,000), which dates back to 1982 (Kaplan and Bush, 1982), and a UK threshold value around £20,000 to £30,000 (approximately €24,000 to €36,000) (NICE, 2004). In Sweden, relevant government authorities have suggested a threshold of 500,000 SEK (approximately €57,000) (Socialstyrelsen, 2007).1

The authors look at the literature on the value of a QALY and find significant variation across studies.


Overall, the average willingness to pay for a QUALY is 118,839 EUR 2010, which is equivalent to $179,000 USD in today’s dollars. The median WTP however, is only 24,226 EUR (or $36,000 in 2014 USD). Additionally, there is variation across method for valuing a life year. WTP measures using the stated preference measure are likely to be much smaller than those using the value of a statistical life (VSL) measure. Disregarding the 2.5% highest and lowest estimates, respectively, the resulting trimmed mean amounts to €74,159, or ($114,545 in 2014 USD)
WTP QALY Summary

Some additional conclusions from the authors:

We find that individuals have a higher WTP if the QALY is based on length of life improvements compared with QoL improvements. Further, the evidence indicates that there is a problem with scale bias, that is, WTP is not linearly proportional to the QALY change respondents are asked to value, which implies that WTP-Q is lower if respondents are asked to value higher changes in QALY.


Does poor mental health decrease your job prospects?

Written By: Jason Shafrin - Aug• 17•14

Conventional wisdom holds that individuals with serious mental illenesses will have more difficulty acquiring and retaining a job.  Measuring the magnitude of the effect of any mental illness on employment empirically is difficult because of a dual-causality problem.  People with mental illnesses may have difficulty gaining employment, but losing employment also has an adverse effect on mental health.  How can we solve this problem?

A paper by Frijters, Johnston and Shields (2014) uses data from 10 waves (2002 2011) of data from the Household, Income and Labour Dynamics in Australia (HILDA) survey.  Mental health is measured using nine questions from the Short-Form General Health Survey (SF-36).  The authors use an IV-FE model where death of a friend in the past three years is the instrument for mental health.  This instrument is valid as long as the death of a friend affects employment opportunities only through a decrease in mental health.  The authors also control for  age, education, marital status, children, windfall income, friendships and the deaths of relative.

The authors conclude the following:

 We find robust evidence that a worsening of mental health leads to substantially reduced employment. Moreover, the size of this effect is substantial, with a one-standard-deviation worsening of mental health leading to a 30-percentage-point reduction in the probability of being employed. This effect is large for both men and women…Further investigations suggest that this employment effect is larger for older than younger workers…

In this case, conventional wisdom is proven right: poor mental health has an adverse effect on employment.


Friday Links

Written By: Jason Shafrin - Aug• 15•14


HWR is Wright this week

Written By: Jason Shafrin - Aug• 14•14

Brad Wright has posted Health Wonk Review: August Recess Edition at Wright on Health.

Too much or too little regulation

Written By: Jason Shafrin - Aug• 14•14

Getting Obamacare subsidies may be too easy or too hard depending on your perspective. From MSN:

In May 970,000 people had citizenship data errors in their Obamacare applications. As of August, 450,000 of those cases have been resolved, 210,000 are in progress and 60,000 new documents arrive every day. The 310,000 remaining applicants will receive two more phone calls and one more email…

Critics of the health care law have noted that the government doesn’t have a system in place to verify information it receives from consumers. Last month the Government Accountability Office was able to gain subsidized health insurance for 11 out of 18 fake accounts.

Some people may say that government regulation is cumbersome and people are not getting the funds to purchase the insurance they need. Others may cite the GAO statistics saying that it’s easy to scam the system. Your personal values for providing subsidies to individuals in need vs. avoiding fraud likely will determine how you interpret this story.

Will P4P work?

Written By: Jason Shafrin - Aug• 12•14

In pay-for-performance (P4P) or value-based purchasing (VBP) schemes, health care provider reimbursement rates depend on performance. Physicians can receive bonuses for following best practices, and hospitals can increase reimbursement rates from Medicare if they improve clinical processes and patient satisfaction. As an economist, rewarding good performance with financial payments makes perfect sense. Or does it?

Dan Ariely’s findings cast a some doubt on whether P4P will work in practice. In his 2011 study, he found the following:

…as long as the task involved only mechanical skill, bonuses worked as would be expected: the higher the pay, the better the performance. But when we included a task that required even rudimentary cognitive skill, the outcome was the same as in the India study: the offer of a higher bonus led to poorer performance.

If this empirical finding holds true, then P4P would seem to make sense for rewarding a few basic, high-value health care processes. For instance, a P4P scheme to reward physicians who provide the proper vaccinations makes sense. A P4P program that tries to identify every best practice possible and reward each one is doomed to fail because: (i) the informational burden of not only measuring best practices but updating them over time is immense, and (ii) P4P will focus providers attention only on the activities they are rewarded for and will distract their attention from the difficult cases that require more creative thinking. Doctors and hospitals have long grumbled to policymakers and payers about P4P. According to Ariely’s research, they may be right after all.

How do states plan to control Obamacare premiums?

Written By: Jason Shafrin - Aug• 11•14

Obamacare mandates that individuals need to buy health insurance or else they will face a financial penalty. This threat, however, is not credible unless there are affordable health insurance options for most Americans. What are states doing to hold down health insurance rates in the ACA’s health insurance exchanges? A RWJF working paper provides some options which I describe below:

  • Supplemental or Alternative Reinsurance Program. The ACA provides for a temporary reinsurance program to operate from 2014 through 2016 in all states.   The federal approach sets an attachment point at $60,000, the level of individual incurred medical expenses above which reinsurance funds will be made available, a coinsurance rate (80%), the share of medical expenses for which the insurer will be reimbursed above the attachment point, and a cap ($250,000), above which no reinsurance payments will be made.  States have the option of using state funds to increase premium protection provided by reinsurance or to create their own alternative reinsurance program.
  • Supplemental Risk Corridor. The federal temporary risk corridor program redistributes funds from exchange-based qualified health plans (QHP) with lower than expected costs to those with higher than expected costs in an attempt to  increase market stability. The program compares actual QHP medical costs to the plan’s projected medical costs. If the actual costs are less than 97 percent of the expected, a share of the savings goes to HHS; if the actual costs are more than 103 percent of the expected, a percentage of the excess costs is paid to the QHP by HHS.   States can supplement this program, although none have yet chosen to do so.
  • Geographic Rating Areas. Rating areas define the geographic regions within which a plan’s enrollees with the same characteristics—in the case of the ACA, these are age and smoking status—will be charged the same premium.  States have flexibility to determine rating areas to align with available cost and utilization patterns and reduce premium spikes for certain geographic areas, or states can default to federally determined areas. For instance, MN, NY, OR and RI use a determination based on their own state definition but AL, NM and VA use the federal definition.  The federal definition defines the rating areas as one rating area per metropolitan statistical area (MSA) and one additional rating area, which will include all non-metropolitan statistical areas in the state.  This approach is very similar to the geographic rating areas Medicare uses for its hospital wage index.  On the other hand, Oregon has seven county-based areas, and Rhode Island itself is a single rating area. Maryland allows insurers to set their own rating areas; New Mexico uses the federal definition, however, it has made the additional risk-sharing move of capping the maximum differential between the highest and lowest rated areas at 40 percent.
  • High-Risk Pool Transition. Before the ACA was enacted, 35 states had created high-risk pools to provide a coverage option for people with pre-existing conditions These are policies to transition individuals out of the current state high-risk pool (HRP) programs into HIE plans. Since HIE plans cannot alter premiums based on pre-existing conditions, the HRP are no longer needed.
  • Early Renewal Regulation. Prevent or constrain insurers from renewing plans early, delaying compliance with ACA market rules
  • Age Rating. The federal rules currently have 3 age bands, 0-20, 21-63, and 64 and older. States have flexibility to establish their own age curves, which determine the distribution of rates across age bands. The more age bands available, the closer plan prices are to actuarial value but the further they are from full community rating.  New York relies on pure community rating without age bands and Minnesota increased the relative premiums that could be charged to children in order to prevent insurers from being discouraged to sell to children.
  • Restricting the sale of catastrophic plans to limit selection effects and attract catastrophic plan enrollees to exchange plans.  Currently, the ACA restricts the sale of catastrophic plans to two groups: those under 30 years of age at the start of the plan year and those without other affordable offers of health insurance coverage.  The goal of state policies to further limit the sale of catastrophic plans is  to avoid adverse selection which could occur if all healthy individuals decided to buy catastrophic plans leaving standard HIE with a sicker patient population, thus leading to high insurance premiums.
  • Additional Oversight and Regulation of Non-Traditional Products. Certain insurance products, such as association health plans (health plans sold through professional associations), discount medical plans, short-term policies, and coverage through health sharing ministries have often been treated differently, for regulatory purposes, than standard small group or individual health insurance. While some of these plans are independent and might be self-insured, others have been set up by insurance companies in an effort to offer insurance products not subject to more restrictive state laws.  Thus, some States have included additional regulation of these plans, often treating them as small group plans within the HIEs.
  • Broker Compensation. Standardizing broker compensation inside and outside of the exchange markets to prevent brokers from steering customers away from one market and towards the other.
  • Network adequacy. The ACA  requires the inclusion of a new category of providers called “essential community providers,” which provide care to underserved populations. The ACA does not, however, impose a network adequacy standard on insurers selling policies outside the exchanges, but many states have their own standards, particularly for Medicaid plans and commercial health maintenance organizations (HMOs).  Narrow network plans have low up-front costs and fewer providers, which can attract healthy individuals who have fewer provider needs. States can set similar network adequacy standards inside and outside of the exchange.
  • Service Area Alignment. Regulating insurers’ service areas to ensure they are not cherry-picking healthier service areas.
  • Plan standardization. Mitigating the potential for variations in plan benefit design within coverage levels, as well as plans outside and inside the exchange, reducing opportunity for benefit designs that may disproportionately attract healthy individuals.
  • Requirements to Offer at Specified Metal Levels. Preventing insurers from avoiding higher risk individuals by requiring them to offer plans at a range of coverage levels.


Dr. Wal-Mart

Written By: Jason Shafrin - Aug• 10•14

CVS’s Minute Clinic isn’t the only game in town for quick primary care visits anymore.  Wal-Mart is getting into the primary care game with $40 office visits with nurse practitioners.  MSN Money reports:

Wal-Mart is making its long-awaited move into delivering primary care: The retailer has quietly opened half a dozen primary care clinics across South Carolina and Texas and plans to launch six more before January.

The clinics will be staffed by nurse practitioners in a partnership with QuadMed.

The clinics will be open 12 hours a day on weekdays and 8 hours per day on weekends.

Why did Wal-Mart choose Texas and South Carolina?

“Both Texas and South Carolina have primary care access problems, [but] interestingly, the access problem is specifically related to cost,” she [Alicia Daugherty] says. “And neither state is expanding Medicaid, so both will continue to have a group of uninsured who will prioritize cost when seeking care. Obviously, both also have high rates of obesity, smoking, chronic conditions, and poverty.”

Friday Links

Written By: Jason Shafrin - Aug• 08•14

Competition Works…even in Medicare Part D

Written By: Jason Shafrin - Aug• 06•14

This is the finding from a CBO working paper by Stocking et al. (2014). They use measure how plan bids change as the number of plans in an area change controlling for year, region, plan sponsor fixed effects, whether the plan was a Medicare Advantage Part D Plan (MA-PD), and whether the plan has a high share of low-income subsidy (LIS) beneficiaries. The authors find the following:

Consistent with economic theory, we find that increases in the number of plan sponsors within a market were associated with lower bids and lower overhead and profits of plans in that market. [A]mong stand-alone plans…each additional plan sponsor entering [a] market was associated with a reduction in bids…of 0.4 percent…which corresponds to an elasticity of -0.071….an additional plan sponsor nationwide was associated with a reduction in government spending of $7 million to $17 million each year.

However, these are only the average results. The authors also find that the size of the incumbant and the new entrants matter.

The bids of a larger “incumbent” plan that enrolls 5 percent of the regional beneficiary pool are less responsive (elasticity = -0.01) to changes in the number of plan sponsors than the bids of a smaller “fringe” plan that enrolls less than 0.25 percent (elasticity = -0.12).

Background on Medicare Part D