HealthLawProf Blog

Continued Skepticism re "Wellness Programs"

A big part of the job of being a Health Law Prof is to help students understand the intersection of the many legal specialties that comprise the big tent of "Health Law."  Wellness Programs are a good way of doing that because one of the key features of the Affordable Care Act is the flexibility it provides employers to link the cost their employees pay for health insurance with the individual employee's participation in a company sponsored "welleness program."  Here's an article I wrote explaining how PPACA went about doing that.  Here's a link to the Department of Labor's summary of the current rules and a good overview by the law firm Nixon-Peabody.  This report from Rand is an overview of what these programs are and how companies have increasingly fallen in love with them.   At this point just about every insurance company is offering to create one--here's some information from Aetna.  

The problem is, there's very little evidence that these programs do anything to demonstrably improve health (whatever that may mean).  And quite a bit that they may promote many different kinds of social injustice.

 This article in the Harvard Business Review does a great job describing the kinds of programs that are now descending on employees and how they are creating disatsifaction without any scientifically supportable improvement in "health."

There is also a growing literature suggesting that these programs may disproportionately discourage workers who employers aren't that unhappy to see go--but might not legally be able to actually fire.  Here is some very interesting testimony by Jennifer Mathis Director of Programs, Bazelon Center for Mental Health Law
On Behalf of the Consortium of Citizens with Disabilities.

Michelle Mello at Harvard has coined the term "life-style discrimination" to describe the ways Wellness Programs may target individuals employers may perceive as undesirable because they are obese, smoke or have other non-job related characteristics.

Studying Wellness Programs--and the issues they raise--can be an accessible entry point for students who can easily be intimated by the regulatory complexity of health law and can also be a bridge to understanding how fundamentally the Affordable Care Act has affected the way health care will be paid for and delivered as our students begin their careers in advising those struggling to implement these new regulations.

 

 

 

 

Is Big Data Overhyped?

For some in Silicon Valley, the rise of new data and communication networks creates unprecedented opportunities to solve problems like obesity, traffic, and flu pandemics. For example, an app like FitBit or LoseIt can keep track of calories and buzz a dieter once he goes over his daily limit. Futuristic early warning systems can warn drivers away from bottlenecks, and detect emerging influenza outbreaks.

Evgeny Morozov’s illuminating book To Save Everything, Click Here challenges both “internet centrism” and “solutionism.” The internet may, for instance, make traffic worse. Moreover, solutionism tends to “reach for the answer before the questions have been fully asked.” Is the problem really traffic, or something deeper in the way cities and opportunities are arranged? Solutionism tends to prioritize issues that widely accessible tech can address: small, algorithmically decomposable bits of wicked problems.

While a solutionist might think of gamified calorie counting as a wonderful new way to fight obesity, a more sober analysis of the problem will lead us to doubt the smartphone will make us svelte. Similarly, calorie counts may be a great disclosure tactic, but disclosure is only the first step on the road to changing behavior. And our food problem, like our traffic problem, may entail reconsideration of privilege, taste, and inequality as far deeper problems than individual struggles for self-control.

Big data has been linchpin of solutionist narratives about the future of tech in health care. However, there are still major challenges in data quality. Even if the data were perfect, causal inference still may be a challenge, as Hoffman & Podgurski explain:

EHR [electronic health record] vendors are making slow progress towards achieving interoperability, the ability of two or more systems to exchange information and to operate in a coordinated fashion. In 2010 only 19% of hospitals exchanged patient data with providers outside their own system. Vendors may have little incentive to produce interoperable systems because interoperability might make it harder to market products as distinctive and easier for clinicians to switch to different EHR products if they are dissatisfied with the ones they purchased. . . .

Even if the EHR data themselves are flawless, analysts seeking to answer causal questions, such as whether particular public health interventions have had a positive impact, will face significant challenges relating to causal inference. These include selection bias, confounding bias, and measurement bias.

Paul Ohm adds to the data skepticism in a recent essay:

[A]s medical research follows the lead of Google Flu Trends and begins to slip outside these traditional institutions and their concomitant safeguards, we should be concerned about the relative lack of controls. Particularly as more medical research is conducted by profit-driven companies—–whether large corporations or small startups—–we should worry about forcing the public to accept new risks to privacy with little countervailing benefit and none of the controls. The worst of all worlds would occur if medical researchers at non-profit institutions began to clamor for relaxed human subjects review in a race to the bottom to compete with their forprofit counterparts.

Ohm’s point about maintaining a baseline of standards is prescient: I have heard at least one behavioral scientist argue that research will migrate out of universities and into private companies if the universities don’t relax IRB standards. Ohm also questions whether something as celebrated as Google Flu Trends has led to actionable data:

Who has created an app, therapy, or epidemiological study based on the colors on [Google's flu maps]? Has a traveler ever avoided boarding a plane to a city on a distant coast because of the relative difference in the shading of the oranges between home and destination? The answer, I suspect, is that none of these positive results has occurred. Instead, the project’s primary mission is to market Google: we are reminded by a colorful map that Google is not evil.

As I’m sure the Washington Post will be soon be reminding us of cloud services generally.

[FP]

X-Posted at Concurring Opinions. 

Lessons About Medical Error Learned Watching I Love Lucy.

It's no secret that the night staff of a hospital are both over-worked and over-tired.   Nor is it any secret that many medical errors occur at night.  But until we look at the totality of the human factors making up medical error, we are unlikely to make significant headway in addressing it.  A review of the literature suggests that the reason isn't a lack of understanding about the factors which cause human errors, it's concern about the cost of addressing them.

The authors of a recent study in the Journal of the American Medical Association titled, Relationship Between Occurrence of Surgical Complications and Hospital Finances conclude that not only aren’t hospitals doing all they can to reduce medical errors, they actually have no financial incentives to do so.  

I'd suggest that financial incentives are behind ineffective efforts to address the issues of staff over-work and the inherent dangers of intermittent shift work.

 It's no surprise that another widely reported recent study has found that reductions in the hours medical residents work has not resulted in increased patient safety.   The study authors conclude that this is because although residents worked less hours, they did not have a reduced work load.  So, like Lucille Ball in the chocolate factory, the trying to cram more work in the same amount of time increased resident error.  

The findings of that study need to be seen in combination with the vast amount of scientific research on the increase in errors caused during night shifts.   A recent study of nurses working night shifts showed that “on average, the error rate increase 6% after the second night shift in a row, 17% after the third successive night shift and an astounding 35% higher on the fourth night shift.”  See also this and this article by the Joint Commission.  Although no one disputes the reality that human beings perform best in the day time, every hospital must be fully staffed 24 hours a day.  The information is both anecdotal and research based.   But no one seems to be listening.

 An article in Nursing World  does an excellent job of using available research to describe the scope of the problem, but implies that it can be effectively addressed by nurses proactively paying more attention to their sleep patterns.  It advises nurses working the night shift to “take control of sleep.”  In fact the NSF “recommends that nurses wear wrap around sunglasses when driving home so the body is less aware that it is daylight.”    This advice ignores the scientific reality that humans are not as effective or alert at night as they are in the day time.  Nor does it consider the human reality that medical shift workers do not have the luxury of using their days to sleep.  Like everyone else living in a diurnal world, they must cope with the tasks of family and daily living.

 Techniques like wearing dark glasses may work in making a shift to a new rhythm--like travelling to another time zone.   But given the unlikeliness of medical staff to convert to a  permanent change in their circadian rhthyms, as if they were working in a submarine (and that doesn’t work very well either)  the answer is to address the reality that humans are less effective at recognizing problems and completing complex tasks at night.   But that’s not where the problem solving is going. 

Continue reading

Evidenced Based Practice: When will Law Catch up with Medicine?

 Two widely reported studies this week about bed rest for women at risk of preterm delivery and reduction of salt consumption in order to promote heart health highlight two things we don’t think about enough—that a lot of standard medical practices are without any foundation in science and a lot of legal ones probably are too.    However, medicine has more and more taken the public health approach of examining the practices of individual doctors to see how effective they actually are in the general population.    For example, it is old news that prescribing bed rest to pregnant women at risk of preterm delivery is not effective.  But what this Obstetrics & Gynecology study found that “activity restriction”, such as quitting work, is still prescribed to one at three women at risk for preterm delivery.  The accompanying “Bed Rest in Pregnancy: Time to Put the Issue to Rest” makes an ethical argument that continuing to prescribe bed rest in the absence of evidence of its effectiveness violates the principles of autonomy and beneficence.

The Institute of Medicine just issued this report Sodium Intake in Populations: Assessment of Evidence “found no consistent evidence to support an association between sodium intake and either a beneficial or adverse effect on most direct health outcomes other than some CVD outcomes (including stroke and CVD mortality) and all-cause mortality.”

We have similar research in law- a lot of it coming from the Empirical Legal Studies movement, including work done at the Center for Empirical Legal Research at Washington University Berkeley Emperical Legal Research , the Centre for Emprical Legal Studies at UCL (formerly known as University College London) among many others, but it is not as well funded or coming from as well established sources as the studies which attempt to find an evidence basis for medical practices.  The salt reduction report was commissioned by the Institute of Medicine   In contrast, the ACLU supports its empirical argument that the death penalty does not deter crime on an opinion survey of police chiefs.  Translating information from research scientists to practicing physicians is still a slow process,—but no one questions the underlying principle that medical practice should be based on scientific evidence.

Part of the issue is funding.   Medicine as a whole is in a constant quest to contain costs and stopping ineffective practices is an important component of that effort.    But beyond a small number of progressive funders like the Robert Wood Johnson Foundation, there isn’t a lot of demonstrable interest, the kind supported by funding studies, in law making bodies in finding out what legal practices work and what do not.   

 This isn’t a new observation.  Bryant Garth outlined the problem in 1997 when he explained the importance of more social science research into the foundational principles of practices civil procedure.   But the steady flow of studies questioning conventional wisdom coming from the medical field has, as yet, no real counterpart in the world of law making.

Of course there will always be the problem of knowing the unknowable.  But it would be interesting for law makers to consider taking a lesson from public health in challenging assumptions about the human body and mind or even more generally the physical world that underlie both common law and statutes.