Unbiased Analysis of Today's Healthcare Issues

Health Wonk Review: Super Bowl Edition

Written By: Jason Shafrin - Jan• 29•15

You have been studying the the teams, getting the snacks, and reading up on “Deflate-gate.”  You’re ready to grab a beverage and watch some commercials football.  The Super Bowl is almost upon us.

SuperBowlXLIXLogo

Before you turn on the TV for the game, however, an even more exciting event is upon us: the Health Wonk Review!  So get ready for this weeks the best health policy posts on the wonk-o-sphere.

Healthcare cost

Of course, as an economist, I have to start off talking about money and cost.

Health Policy Initiatives

Spending money in and of itself is not bad.  It the money spent on health care leads to significant health improvement, you are getting good value.  Below are two innovative programs that have the potential to both reduce cost and improve quality. 

Safety

How do we reduce medical errors?  How do we reduce on-the-job fatalities.  Two wonkers tackle these issues. 

Health IT

Information technology can provide a number of benefits to patients, physicians, and payers.  But what are the risks?  Our HWR panel weighs in.

Kindness

Just because I am economist, doesn’t mean that I am cold-hearted.  I end this edition of the HWR on a post describing how training physicians to be kind can help improve patient care.

 

Does your FitBit need to be FDA approved?

Written By: Jason Shafrin - Jan• 27•15

Right now, the answer is no, but in the near future, this may no longer be the case. The FDA has released a draft guidance on how it will regulate the new generation of wearable technology.  This guidance  says it will not regulate “general wellness” products like the FitBit.

However, if the wearable cites health benefits for a specific disease, then the wearable would be subject to FDA regulation. For instance, if the wearable states it can improve specific disease symptoms or improve functional status due to a specific deformity, those claims would require FDA approval.

On the one hand, having commercial firms make false advertisements is problematic.  On the other hand, the FDA approval process is expensive and time-consuming for innovators.  Since many firms entering the wearable space are start-ups, they may not have the funds to go through FDA approvals.  Further, if wearables undergo revisions due to user feedback or beta testing, would the improved version of the product also have to go through FDA approval?  Requiring innovation

Pharmafile notes that “The FDA guidelines are not yet legally binding it is important to note, and the US regulator is requesting opinions from the public on the move.”

Individuals who see government as getting in the way of innovators likely will think the FDA has overstepped its role; individuals who see government as protecting the general public may think that the FDA has not gone far enough.

Another question is even if the FDA decides to regulate wearables, does it even have the capacity to do so effectively?  Given the large number of health-related wearables entering the market, the FDA’s good intentions could risk significantly stifling innovation.

In Memoriam: Willard G. Manning, 1946-2014

Written By: Jason Shafrin - Jan• 25•15

In November, Willard Manning passed away.  I met Dr. Manning as he was a lecturer at the European Science Days summer school in Steyr, Austria.  iHEA has put together a nice in memoriam article and I have an sample of that below.  I will echo that although Dr. Manning was best know for his work on the RAND Health Insurance Experiment, his most lasting contributions to the health economics field are likely in his work as a leading health econometrician.

 

Will was probably best and most widely known for his work on the RAND Health Insurance Experiment (HIE). Not only has this work on the RAND HIE been hugely influential in academic and policy thinking about insurance design and its implications (e.g. Manning et al., 1987; Newhouse et al., 1981), it also generated a series of important methodological contributions that have had lasting impact on the empirical practice of health economics and health services research (e.g. Duan et al., 1983, 1984). While not his best known work from the RAND HIE project, my all-time favorite Will Manning paper – and, I’ve learned recently, others’ favorite as well – is Manning et al., 1982. Its lessons about health status measurement and prediction vs. postdiction are still essential considerations in much empirical research in our field.

Beyond and largely after the RAND HIE work, Will made important substantive contributions to an extraordinary number of areas in health economics including, but not limited to: mental health (Keeler, Manning, and Wells, 1988); tobacco and alcohol use, and poor health habits (e.g. Farrell, Manning, and Finch, 2003; Manning, Keeler, et al., 1989, 1991; Manning, Blumberg, and Moulton, 1995; Wasserman, Manning, et al., 1991); rural healthcare (e.g. Moscovice et al., 1995); health insurance theory and design (e.g. Ellis and Manning, 2007; Manning and Marquis, 1996; Zweifel and Manning, 2002); hospital-based healthcare delivery (e.g. Meltzer, Manning, et al. 2002); and healthcare disparities (e.g. Cook and Manning, 2009). Will’s research also provided major advances in the conceptual and statistical underpinnings of cost-effectiveness analysis (e.g. DeLeire and Manning, 2004; Luce, Manning, et al., 1996; Weinstein and Manning, 1997). There is no question that Will’s applied work has had significant influence on the way policymakers think about the costs of illness, taxation of unhealthy commodities, design of health insurance, healthcare access, and many other important policy domains.

In addition to his applied work, Will also made prominent contributions to the everyday empirical toolkit of health economists and health services researchers. Indeed, in some circles Will was best known and properly regarded as the field’s top “health econometrician”. His applied work itself generated significant methodological advances, including the RAND HIE work mentioned above and quantile and count data regression applications tailored to health economics applications (e.g. Manning, Blumberg, and Moulton, 1995; Manning, Keeler, et al., 1991). Beyond these, Will was responsible for developing many of the methods still commonly used to analyze health care cost or spending outcomes (e.g. Basu and Manning, 2009; Basu, Polsky, and Manning, 2011; Manning, 1998; Manning and Mullahy, 2001; Veazie, Manning, and Kane, 2002).

Friday Links

Written By: Jason Shafrin - Jan• 23•15

State of the Union 2015: A Healthcare Review

Written By: Jason Shafrin - Jan• 21•15

The Healthcare Economist’s annual tradition is upon us. I review the President’s State of the Union address, identify all healthcare related comments, and provide commentary.  So without futher ado…

And in the past year alone, about ten million uninsured Americans finally gained the security of health coverage.

The President pats himself on the back for the Affordable Care Act (a.k.a. Obamacare)

At every step, we were told our goals were misguided or too ambitious; that we would crush jobs and explode deficits. Instead, we’ve seen the fastest economic growth in over a decade, our deficits cut by two-thirds, a stock market that has doubled, and health care inflation at its lowest rate in fifty years.

Everyone likes fewer uninsured. Critics of Obamacare claimed that expanding health insurance would increase deficits and hurt the economy. The President claims that the ACA caused neither of those things. However, a rebound from the Great Recession is likely the reason that the economy is growing; the bigger issue is whether the government–particularly state governments that expanded Medicaid–will be able to afford the additional costs in the long-run.

Today, we’re the only advanced country on Earth that doesn’t guarantee paid sick leave or paid maternity leave to our workers. Forty-three million workers have no paid sick leave. Forty-three million. Think about that. And that forces too many parents to make the gut-wrenching choice between a paycheck and a sick kid at home. So I’ll be taking new action to help states adopt paid leave laws of their own. And since paid sick leave won where it was on the ballot last November, let’s put it to a vote right here in Washington. Send me a bill that gives every worker in America the opportunity to earn seven days of paid sick leave. It’s the right thing to do.

Living in California, this is one of the few states that has paid maternity leave. This certainly drives up costs for employers–since California maternity leave is covered by short-term disability–but is an added benefit most families appreciate. Will paid maternity leave increase the fertility rate and increase the number of kids born in the US? Likely not significantly, but there could be a small impact. Regarding paid sick leave, it is unclear whether this provision would apply to part-time workers or not and how much sick leave would be guaranteed. Again, this provision would drive up labor cost, but is a nice benefit for workers.

21st century businesses will rely on American science, technology, research and development. I want the country that eliminated polio and mapped the human genome to lead a new era of medicine – one that delivers the right treatment at the right time. In some patients with cystic fibrosis, this approach has reversed a disease once thought unstoppable. Tonight, I’m launching a new Precision Medicine Initiative to bring us closer to curing diseases like cancer and diabetes – and to give all of us access to the personalized information we need to keep ourselves and our families healthier.

Vox has a nice summary of this initiative, saying “Precision medicine describes a growing movement in medicine to build treatments specifically targeted to an individual’s genetic make-up. While the White House hasn’t specified how big this initiative will be, the idea is to invest more in these more individualized types of medicine that many experts see as the future of health care.”

In West Africa, our troops, our scientists, our doctors, our nurses and healthcare workers are rolling back Ebola – saving countless lives and stopping the spread of disease. I couldn’t be prouder of them, and I thank this Congress for your bipartisan support of their efforts. But the job is not yet done – and the world needs to use this lesson to build a more effective global effort to prevent the spread of future pandemics, invest in smart development, and eradicate extreme poverty.

A very important point; fighting Ebola and other contagious diseases is one of the things (along with warfare) that could bring down societies. Continuing to fund research to fight contagious disease is essential, especially when the public may not be as concerned about these diseases.

Tuesday Links

Written By: Jason Shafrin - Jan• 20•15

Quality and Quality of Life

Written By: Jason Shafrin - Jan• 19•15

There have been numerous efforts to measure quality of health care, especially among the elderly.  For instance, Nursing Home Compare measures of quality of care for nursing homes.  However, these quality measures focus on health and safety.  They do not measure quality of life.  Atul Gawande’s book Being Mortal describes why nursing homes focus more on patient safety and less on quality of life.

Compounding matters, we have no good metrics for a [nursing home’s] success in assisting people to live.  By contrast, we have very precise ratings for health and safety.  So you can guess what gets the attention from the people who run places for the elderly: whether Dad loses weight, skills his medications, or has a fall, not whether he’s lonely…assisted living isn’t really built for the sake of older people so much as for the sake of their children.

Children of the elderly focus more on safety than their parents’ satisfaction; they will do anything to avoid a fall from their parents, whereas elderly parents often are willing to tradeoff more autonomy for a higher risk of a fall.

Friday Links

Written By: Jason Shafrin - Jan• 15•15

Winter HWR

Written By: Jason Shafrin - Jan• 15•15

Vince Kuraitis has posted a most excellent “Shake the Winter Blahs” Edition of Health Wonk Review at e-Care Management Blog

WTP to reduce mortality risk

Written By: Jason Shafrin - Jan• 14•15

How much would you pay to live longer?  Most people would say an infinite amount.  In practice, however, this is not the case.  For instance, you can drive slower to reduce your risk of a car crash.  In this case, you trade off your time with your probability of death.  Or, to continue the care safety theme, one could buy the most expensive car seat with the highest safety track record.  However, not everyone buys the most expensive car seat.

Economist measure preferences using a utility function and one can readily adapt a utility function to measure the value of a statistical life.  Let one’s expected utility be:

  • EU=(1-p)ua(w)+p ud(w)

where p is the probability of death in the current period, ua(w) and ud(w)are the utlity of weath conditional on suriving and not suriving. If we differentiate with respect to both w and p, we get:

VSL=dw/dp= ua(w)-ud(w)
(1-p)ua‘(w)+(p)ud‘(w)

How do we interpret this result? A paper by Hamitt et al. (2012) provides the answer:

…in the standard model expectancy conditional on surviving the current period increase the utility of survival ua(w) and may increase the marginal utility of wealth conditional on survival ua‘(w). Reductions in life expectancy and health clearly limit the opportunities for gaining utility from wealth…and there is some empirical evidence that impaired health reduces the marginal utility of wealth…Depending on the magnitudes of the effects on the total and the marginal utilities of wealth given survival, better health and increased longevity may increase, decrease, or not affect VSL.

Clearly, the value of wealth at dealth depends on the value individuals place on bequests. In individuals do not value bequests, then:

VSL= ua(w)
(1-p)ua‘(w)