Health for life

1. Using traditional research to detect a "statistically significant" decrease in insurance claims expense is notoriously difficult.

2. Theres scientific statistical proof and then there is a reasonable business assurance.  The latter may be enough for business-minded health insurers.

3. The conclusion is based on published research.  Unpublished "in house" data have convinced many insurers to include the medical home in their covered benefit.  They know something AHRQ doesnt.

4. While medical homes alone may be insufficient to save money, that doesnt mean that medical homes that are part of a package of interventions (value-based purchasing, P4P, vendor-based population health management or an ACO) are unnecessary.

5. While there is no evidence of savings, there is also no consistent evidence of increased cost. That means the quality associated with the medical home represents high value.

That being said, the U.S. Agency for Healthcare Research and Quality (AHRQ) Evidence Report Technology Assessment on the Patient Centered Medical Home says:

"Based on a combination of good- and fair-quality studies, there is a low strength of evidence that PCMH implementation may lead to lower utilization (inpatient and emergency department) for some subgroups of patients, but this effect was not uniform. Moreover, total costs were not lowered in the reviewed studies.

However, three observational studies specifically designed to test PCMH do report lower inpatient and emergency department utilization among patients in the PCMH program. However, total costs were not statistically different for PCMH and non-PCMH patients in the three studies. None of the clinical trials of functional PCMH interventions had statistically significant differences between intervention and control arms for inpatient or emergency department utilization.

No studies reported statistically significant cost savings among PCMH patients. In fact, when taking into account program costs, two studies, one good-quality trial and one fair-quality observational study, reported greater total costs among intervention patients."

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How would Ms. Antoinette ponder health orm with her advisors?

While commonly attributed to Marie Antoinette, the phrase may actually be testimony to Jean Jacque Rousseaus genius in using four words to capture an elites inability to grasp the plight of a struggling underclass.  For a more modern depiction of a lifestyle bubble, think of the 1% not getting just how difficult it can be to make a living wage.

And its not just the 1%. African Americans, with some justification, note that whites have yet to grasp "the set of experiences and a history" that perpetuates racial inequality. Its not just the "facts" but how facts are sorted, prioritized and interpreted by a brain wired by decades of being surrounded by like-minded people caught up in their information loops.

But it cuts both ways. When confronted by the hostility of tens of millions of Americans to the Affordable Care Act, liberal-progressives likewise respond with similar puzzlement. Who can blame them for rationalizing things with attempts to provide more "education" or blaming it all on obstinate Tea Bagger and "Birther" wackiness?

Its not that simple.  As pointed out in this The Atlantic article, conservative skepticism about the size, regulatory reach and spending of government was well underway long before Mr. Obama set foot in the White House.  Focus groups have little trouble finding deeply held opposition to expanding government entitlements, middle class dependency, pro-business globalization, wealth transfers and scary levels of deficit spending. Given the big picture,  Obamacare is less of a problem than a symptom. 

As result, even if the White House and its Democratic allies prevail on the shutdown showdown, successfully raise the October 17 debt ceiling, cancel the January 1 2014 sequester and take back the House in November 2014, the opposition to the health care law isnt going to simply fade away.

But, say my liberal friends.....

1. Much of the Affordable Care Act is based on Republican ideas, including the mandate and Romneycare.

The mandate and Romneycare were never intended to be imposed nationally, but adapted by each of the states. 

2.  It will save money.

Health care consumption declined before the passage of the Affordable Care Act. Experts legitimately disagree on the impact on future health care costs but it stands to reason that more people with insurance will lead to increased demand and higher spending..

3.  The health care system is broken

Actually, the part of the system that was broken was the individual insurance market.  This objective OECD Report summary points out that, compared to many other developed countries, U.S. quality has been quite good and our cost trends are lower.  And while its too early to tell, the health insurance exchanges travails combined with multiple other self-inflicted wounds suggest that the cure may end up being worse than the disease.

The point here isnt whos wrong or whos right.  Rather, its clear that skepticism over Obamacares ability to deliver on all its promises is not crazy.  Its critics not only deserve their time in the public square but to have their perences lected in policy and legislation..

Whats more, the Obamacare dust-up is part of a bigger concern over the expanding role of government that tens of millions of Americans find potentially intrusive and unaffordable.  The inability of the DMCBs liberal progressive colleagues to comprehend that may be a less a function of their superior intellect or the stupidity of the opposition than an Antoinette-esque inability to step outside their familiar biases and ponder a different point of view. 

"I  think I need to go back to the hospital....."

The Disease Management Care Blog remembers her very well. She had come to the United States after escaping on foot from post-war Hungary.  She liked to have sliced pears and cognac for lunch. As her health began to fail, her stubbornness began to exceed her self-sufficiency, leading to multiple hospitalizations. One time, despite making sure she had a post-discharge outpatient appointment, a fresh pile of prescriptions and home visiting nurse services, her illness flared and she had to come back to hospital.

She was not only my patient, but she represented one of Medicares dreaded readmission statistics.

By now, DMCB readers know that CMS, buoyed by its value-based purchasing program, has targeted readmissions by reducing payment levels to hospitals that fall outside the expected norm. Threatened by the loss of income, it’s assumed that hospitals will respond by developing higher quality discharge planning and care programs that keep patients from having to come back.

An important part of reducing readmissions is to identify those patients that are at greatest risk. That would help on two levels:

1) if a hospital had more than its fair share of patients at risk, it could argue that an increased number of readmissions is the result of a sicker patient population and not quality of care. As a result, the hospital could be held "harmless;

2) hospitals would be able to focus extra care resources on those patients who are spotted early as likely to come back, thereby reducing the readmission rate.

In other words, patients like the lady from Hungary would not necessarily lead to a cut in hospital payment rates and, for example, she could be proactively given extra care, such as a doctor appointment within 48 hours, a week’s supply of free medications and twice a day home nurse visits.

Which is why this just published JAMA article "Risk Prediction Models for Hospital Readmission" by Devan Kansagara, Honora Englander, Amanda Salanitro David Kagen, Cecelia Theobald, Michele Freeman and Sunil Kripalani is important.  The authors set out to see what the evidence-based published scientific literature had to say about predicting readmissions.   They filtered thousands of erences, reviewed 286 publications found 30 rigorous studies that described 26 models. 

To the DMCBs delight, the authors applied a “c statistic” to the 30 publications to assess a wide variety of retrospective and concurrent prediction methodologies using a host of data inputs such as age, gender and past diagnoses. According to this article, the c (or "concordance") statistic measures how well a test can predict the presence or absence of a "condition" which, in this case, was being readmitted to the hospital.  One way to think of this is the likelihood of correctly identifying a condition when there are two people, one with it and one without it.  If the likelihood is 50%, thats no better than random guessing.  If its 100%, thats perfect.  By the way,if this sounds a lot like the area under the receiver operator curve, youre right.

And what did the all-seeing "c statistic" say?  All of the published models had disappointingly similar levels of performance that ranged between the extremes of .52 to .83 with most in the .50 to .7 range. Whats more, only one study examined the most important question of all: is it possible to find patients with preventable readmissions?

What does the DMCB think?

1) This may be another area where national health policy has gotten out in front of the scientific evidence.  If we cant reliably assess or predict readmissions with sufficient accuracy, there is a distinct likelihood that statistical variation, not quality of care, will lead to some hospitals being victimized by CMS with lower payment rates. Whats more, if hospitals cant tell which patients are likely to come back, how are they supposed to target their expensive care management programs at those who are most likely to benefit?

2) There are undoubtedly some proprietary predictive models that havent been reported in the literature that claim to have higher levels of accuracy.  Yet, without the scrutiny of successful peer-reviewed publication, itd be difficult to believe that theyre really any better than the mainstream published range of .5 to .7.  The next time the DMCB runs into one of these outfits, its going to ask about the "c statistic" and if they havent published their results, why not.

3) Last but not least, while the hospital payment rates are being held hostage by CMS, its the doctors that are making the call on readmissions based on the best interest of their patient.  The c statistic suggests that that will be the most important determinant in the readmission rate.

Small business points at its competitor

It wasnt until the Disease Management Care Blog had read this Jan. 30 Wall Street Journal opinion piece that it realized that its "nano" corporate" status was packed with such futuristic potential. According to the editorialist, American companies should follow the DMCBs lead and be "protean" by dropping old fashioned W-2 employees and substituting 1099 contract relationships.  That way, everyone - including a single person "nano" - can enjoy the upsides of being a corporation and stay below Obamacares 50 employee pay-or-play $2000 penalty threshold.

Since the DMCB formed its own corporation more than 5 years ago, it has certainly participated in "protean" business relationships. Once things get underway, the DMCB often discovers that of the many prominent organizations that it does business with really consist of a small core office populated by a few owner-founders, a single administrative aide and one or two payroll folks who oversee the outsourcing of everything else.  While the term "protean" is certainly novel, the DMCB thinks distributed, adaptable and organic business networks have been around for years.

But the WSJ editorial opens a window into an underappreciated consequence of Obamacare and the underlying assumptions of the central planners who run Washington DC.  The DMCB doesnt necessarily think its bad, but it sure is interesting.

Read on.

While the Affordable Care Act (ACA) was intended to link employment and health insurance, what it has really done is handed many small nimble interlocked businesses another leg-up against their large traditional mainframe competitors. For example, one colleague pointed out to the DMCB that "new" pharma companies are really marketing departments that outsource manufacturing that, in turn, outsources supply management that outsources I.T. that outsources its cloud services. Its the only way they can compete. 

The new economics of health insurance will only accelerate similar trends in other manufacturing and service sectors of the economy.  Toss in the ability of people and capital to move and work across borders and the picture becomes even more dynamic. And in the meantime, Washington DC continues to implement the ACA with a legacy of large companies buying comprehensive health insurance for its employees.

Little did anyone anticipate that the ACA would hamper the success of American big business.

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