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It’s the Ventilator’s Fault

If you were from a foreign nation looking at the United States news right now, you would think that this was a nation that had declared war on death. Or perhaps we could state it better as a total denial of death. In California, Jahi McMath, a teenage girl who has been medically and legally dead for nearly a month (death certificate was issued December 12) has been moved to an unnamed facility and given surgical procedures to introduce air, water, and food more easily while her body continues to degrade and decay.

And in Texas, Marlise Munoz, a woman who may be brain dead or may be in a persistent vegetative state (the hospital isn’t saying and the experts are split), is being maintained because of the hospital’s interpretation of a state law, so that she can be used as an incubator to keep her 14-week old fetus growing despite the wishes of her parents and husband that she be disconnected from the ventilator and supportive measures.

In California, a mother is being criticized for exercising her autonomy beyond reason to define death on her own terms. While in Texas a family’s autonomy to make surrogate health care decisions is being denied. Both of these women have become objects and tools of various groups. In California, the girl is an object of unrealistic hope and political factions. In Texas, a woman is being made into an object and tool to gestate a fetus that may never be born and may not be viable after being deprived of oxygen. Not only has the family expressed their wishes but Marlise also had deliberate and specific conversations with her family about not wanting to be maintained by machines. And lest we forget, the human incubator is also being used as a tool of politics, for elected officials trying to further their career and standing with certain political/religious/social factions to further their agendas.

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Let’s Decriminalize Our Health Records

The governor of Vermont, Peter Shumlin, devoted all of his annual speech to the problem of drug addiction. On the national news, Shumlin points out the link between prescription painkillers and death, and he calls for treating opiate addiction as a medical problem no different than cancer. The White House praised the governor’s position.

Meanwhile in another part of Washington, I’m involved in the federal effort to link the law enforcement Prescription Drug Monitoring Program databases to the health records physicians use, and to link the databases across state lines.

The unintended consequences of criminalizing addiction and driving medical problems underground need to be considered here as well.

Physician-patient confidentiality is important to public health, and networked electronic health records have both individual privacy and public health consequences. Privacy is essential in infectious disease testing, domestic violence, mental health, adolescent, reproductive, and addiction medicine. Subjecting clinical encounters to law enforcement surveillance beyond the physician’s discretion is life-threatening.

Well-meaning people are now working to link PDMP databases to EHRs and across state lines. The evidence to justify the coerced crossing of the criminal – medical boundary is anecdotal findings in pilot studies that more physicians are in a position to uncover addiction and offer treatment.

The other goal is to reduce illegal diversion of prescription drugs by both physicians and patients. What could possibly go wrong?

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One Libertarian’s Dilemma: Genetic Testing or the FDA

An advantage astrologers have over genetic testing is that the prediction of astrologers are personally verifiable. An astrologer once emphatically stated that I had no chance of a career in international cricket or Bollywood. So far both claims have turned out to be remarkably accurate.

How does one personally verify a “12.5 %” increased chance of lung cancer, the sort of number the vendor for genetic testing 23andMe produces? If one develops lung cancer how would one know that the chances were indeed 12.5 %, not 6.25 % or 25 %?

We die only once. Whether one ends up with lung cancer or doesn’t, the veracity of the claim can be made only empirically. Meaning we need to see how many develop lung cancer out of 10, 000 people just like us.

Yet there is an element of scientific precision in the number, augmented by the decimal point. And it is precisely because genetic testing tends towards science not metaphysics that it falls within the dominion of the Food and Drug Administration (FDA). FDA does not regulate palm readers.

FDA has asked 23andMe to stop sales of its genomic testing.

As a libertarian seeped in the Austrian school of Economics, I am generally disposed against regulations. I also share the sentiments of the monetarist Milton Friedman that the true costs of the FDA must also include the treatment opportunities foregone in their lengthy review process.

So it hurts me to be somewhat sympathetic of FDA’s stance on 23andMe, even as I think an outright ban was a tad harsh.

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The Data Are Wrong. Our Patients Are Sicker!!!

People in health care don’t like it when numbers emerge that are uncomfortable.  Take these, issued today by the Massachusetts Health Policy Commission in its latest report on the drivers of the high cost of care in our state.

Variation, particularly when not correlated to quality of outcome, is particularly troublesome for some incumbents.  Academic medical centers often have their answer, but as the HPC explains, it doesn’t hold water:

One oft-cited theory for the cause of this variation is that certain types of hospitals, such as those that teach physician residents and fellows, must incur additional expenses to support their mission. However, the difference in median expenses per discharge between teaching hospitals and all hospitals ($1,030) was less than the difference between individual teaching hospitals ($3,107 between the 75th percentile and 25th percentile teaching hospitals). Moreover, there were a number of teaching hospitals that incurred fewer expenses per discharge than the statewide all-hospital median of approximately $9,000 per discharge.

So perhaps the high cost ones will now revert to the usual squawking: “This isn’t fair. The data are wrong.  Our patients are sicker.”

Except here, the data are the best that could be available–all the claims for all the hospitals and all the payers in the state–even adjusted for wages.  And the acuity of patients across the spectrum of academic medical centers does not vary widely–but, just in case, the numbers are case-mix adjusted.

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Gender Could Be as Big a Problem as Age for the Affordable Care Act

Concerns about whether insurance sold on  the individual Exchanges under the Affordable Care Act will succumb to an adverse selection death spiral have focused mainly on the shortage of younger enrollees into the system.

This shortage is potentially a problem because, due to section 1201 of the ACA, premiums for younger enrollees must be at least one third of that for older enrollees even though actuarial science tells us that younger enrollee expenses are perhaps just one fifth of those for older enrollees.

Younger enrollees are needed in large numbers to subsidize the premiums of the older enrollees. But at least premiums under the ACA respond at least somewhat to age.

The lesser studied potential source of  adverse selection problems, however, is the fact that medical expenses of women for many ages are essentially double those of men and yet the ACA forbids rating based on gender.

In a rational world, one would therefore expect women of most of the ages eligible for coverage in the individual Exchanges to enroll in plans on the Exchange at a higher rate than men. But, since the women have higher than average expenses than men, premiums based on the average expenses of men and women will prove too low, creating pressure on insurers to raise prices.

And, of course, there could also be some disproportionate enrollment by older men who have higher medical expenses than women of equal age. While I welcome contrary arguments in what I regard as a fairly new area of study involving the ACA, gender-based adverse selection would certainly appear to be  a real problem created by the structure of that law.

To me, it looks to be potentially as large a problem as age-based adverse selection. It is certainly one that needs continuing and careful evaluation.

Caveats
I see only three limited factors that reduce what would otherwise appear to be a significant additional source for significant adverse selection. As set forth below, however, I do not believe that any of these factors are likely to materially reduce the problem.

1. Ignorance
The first is ignorance. Adverse selection emerges only if individuals can accurately foretell their future medical expenses with some accuracy. To the extent, therefore, that men and women are ignorant of the effect of gender on their projected medical expenses, adverse selection is potentially diminished. I say “potentially,” however, because of a subtlety: people don’t have to know why their expenses are what they are in order for adverse selection to emerge; they only have to be somewhat accurate in their guess.

Thus, even if men and women don’t make the cognitive leap from seeing lower (or higher) medical expenses to issues of gender, but they still on balance get it right, adverse selection can exist. Thus, I end up doubting that ignorance of the correlation between gender and medical expense is going to retard adverse selection problems very much.

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Do You Care About My Health, Or Just Think I’m Gross? Be Honest.

 

Hi. I’m fat. I’m what most people call an in-betweenie—I have a heavy build, I wear plus sizes, my stomach poofs out, I have folds of fat along my back, I have chubby arms and legs. I can still buy clothes off the rack at a lot of stores, though.

Don’t rush to tell me I’m not ‘that kind’ of fattie or you’re ‘not talking about [me]‘ when you’re going on about how much you worry for fat people, though. We all know that you’re thinking of me, that when you think of fat people, my double chin comes to mind, my wobbling upper arms, my thighs broad in my jeans, my big ass. I’m fat. It’s okay. You can say it. I don’t have a problem with it.

I have a lot of issues with my body, but my size isn’t really one of them. It is what it is. The reasons I’m fat are complicated and not really your business. And yeah, I am unhealthy, and the reasons for that aren’t your business either, although I know you want to rush to assume that I’m unhealthy because I’m fat.

I don’t have an obligation to be healthy, actually, and I don’t have an obligation to rush to assure you that I’m a ‘good fatty’ with great cholesterol and good scores on other health indicators allegedly related to weight. I don’t have an obligation to tell you that fat isn’t correlated with health because I shouldn’t have to justify the existence of fat people by informing you that you don’t understand how fat bodies work, and you’re not familiar with the latest studies on fatness, morbidity and mortality, health indicators, and social trends.

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Will There Be An Obamacare Death Spiral in 2015? Probably Not.

By ROBERT LASZEWSKI

If the Obamacare health insurance exchanges are not able to get a good spread of risk––many more healthy people than sick––the long-term viability of the program will be placed in great jeopardy.

Given the early signs––far fewer people signing up than expected, enormous negative publicity about website problems, rate shock, big average deductibles, narrow provider networks, and a general growing dissatisfaction over the new health law––it is clear to me that this program is in very serious trouble.

But that trouble would not necessarily transfer to the health insurance plans participating on the state and federal health insurance exchanges.

Obamacare contains a $25 billion federal risk fund set up to benefit health insurance companies selling coverage on the state and federal health insurance exchanges as well as in the small group (less than 50 workers) market. The fund lasts only three years: 2014, 2015, and 2016.

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PepsiCo’s Wellness Program Falls Flat

For those of us who actually think wellness outcomes should be evidence-based, a landmark study was released today:  the first evidence provided by a major organization voluntarily (as opposed to being outed by us, like British Petroleum and Nebraska) that wellness doesn’t work.   January’s Health Affairs features a case study of PepsiCo, authored by RAND Wellness Referee Soeren Mattke and others, in which a major wellness program was shown to fall far short of breaking even.

The specific highlights of the PepsiCo study are as follows:

  • Disease management alone was highly impactful, with an ROI of almost 4-to-1;
  • Wellness alone was a money sink, with each dollar invested returning only $0.48 in savings;
  • The wellness savings were attributed to an alleged reduction in absenteeism, as self-reported by participants.  There was no measurable reduction in health spending due to wellness.

Even though the wellness ROI was far underwater, we suspect that the ROI was nonetheless dramatically overstated, for several reasons.  First, the authors acknowledge underestimating the likely costs of these programs, focusing only on the vendor fees without considering lost work time, program staff expense and false positives.  Second, no matter how hard one tries to “match” participants with non-participants (the wellness industry’s most utilized measurement scheme), it simply isn’t possible to compare mindsets of the two groups.  We learned from one of Health Fitness Corporation’s many missteps that participants always outperform non-participants, simply because they are more motivated.  Third, the absenteeism reductions were self-reported, by participants.

Finally, PepsiCo’s human resources department, having made the mistake of accepting Mercer’s advice to implement one of these programs, was already taking some political risk by acknowledging failure.  Had they incorporated the adverse morale impact, lost productivity due to workers fretting about false positives, Mercer fees and staff costs, participant bias, and self-reporting bias, the ROI could easily have turned negative (meaning the program would have been a loser even if the vendor had given it away) and the HR staff could have been taking serious career risk.

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Actually, We’d Probably All Be Better Off With Our Health Records on Facebook

A Facebook user’s timeline provides both a snapshot of who that user is and a historical record of the user’s activity on Facebook. My Facebook timeline is about me, and fittingly, I control it. It’s also one, single profile. Anyone I allow to view my timeline views my timeline—they don’t each create their own copies of it.

Intuitive, right? So why don’t medical records work that way? There is no unified, single patient record—every doctor I’ve ever visited has his or her own separate copy of my records. And in an age where we can conduct banking transactions on my smartphone, many patients still can’t access or contribute to the medical records their doctors keep for them.

My proposal? Medical records should follow Facebook’s lead.

Cross-industry innovation isn’t new. BMW borrowed from the tech world to create its iDrive; Fischer Sports reduced the oscillation of its skis by using a technologycreated for stringed instruments. So I asked myself: Who has mastered the user-centric storing and sharing platform? The more I thought about it, the more I decided a Facebook timeline approach could be just what medical records need.
To see what I mean, let’s explore some of Facebook timeline’s key features to see how each could map to features of the ideal medical record.

“About” for Complete, Patient-Informed Medical History

On Facebook: The “about” section is the one that most closely resembles the concept of a user profile. It includes a picture selected by the user and lists information such as gender; relationship status; age, political and religious views; interests and hobbies; favorite quotes, books and movies; and free-form biographical information added by the user.

In medical records: The “about” section would be a snapshot of the patient’s health and background. It should include the patient’s age, gender, smoking status, height, weight, address, phone number, and emergency contact information; the patient’s primary care provider; and insurance information. This section would include a summary list of the patient’s current diagnoses and medications, as well as family history. And importantly, both the doctor and the patient would be able to add details.

FACEBK about-patient

“Privacy Settings” and “Permissions” for Controlled Sharing

On Facebook: Privacy settings allow users to control who can see the information they post or that is posted about them. For example, in my general privacy settings I can choose to make my photos visible only to the people I’ve accepted as “friends.” However, if I post a photo I want the entire world to see, I can change the default setting for that photo to be visible publicly instead.

Facebook also allows users to grant “permissions” for outside applications to access their profiles. For example, let’s say I use TripAdvisor to read travel reviews. TripAdvisor lets me sign in to its site using my Facebook account, rather than creating a separate TripAdvisor account. But, to do this I must grant TripAdvisor “permission” to access my Facebook account.

In medical records: Patients could use “privacy settings” to control whether all or part of their information can be seen by a family member or caregiver. For
example, if my aging mother wanted to give me access to her “events” (upcoming doctor’s appointments), she could do so. If my college-aged son who is still on my health plan wanted to give me access to his knee X-rays, he could.

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