- Do voters now like Obamacare?
- The deadliest drug.
- Evidence for digital medicine.
- X-ray goggles.
- CDC Ebola guidance.
Austin Frakt says although Medicare Advantage plans used to be considered high cost, low-quality options, in recent years, these Medicare Advantage plans have vastly increased quality of care and have become less focused on cream-skimming healthier patients.
Medicare Advantage plans — private plans that serve as alternatives to the traditional, public program for those that qualify for it — underperform traditional Medicare in one respect: They cost 6 percent more.
But they outperform traditional Medicare in another way: They offer higher quality. That’s according to research summarized recently by the Harvard health economists Joseph Newhouse and Thomas McGuire, and it raises a difficult question: Is the extra quality worth the extra cost?
It used to be easier to assess the value of Medicare Advantage. In the early 2000s,Medicare Advantage plans also cost taxpayers more than traditional Medicare. It also seemed that they provided poorer quality, making the case against Medicare Advantage easy. It was a bad deal…
…in contrast to studies in the 1990s, more recent work finds that Medicare Advantage is superior to traditional Medicare on a variety of quality measures. For example, according to a paper in Health Affairs by John Ayanian and colleagues, women enrolled in a Medicare Advantage H.M.O. are more likely to receive mammography screenings; those with diabetes are more likely to receive blood sugar testing and retinal exams; and those with diabetes or cardiovascular disease are more likely to receive cholesterol testing.
This may be why almost 1 in 3 Medicare beneficiaries choose a Medicare Advantage plan over traditional Medicare fee-for-service.
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)
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.
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.
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.
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?
…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.
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: