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Merge Away!!!

Art Caplan 2The New York Times editorial page is the latest in a lengthening series of commentaries worrying about the impact of two proposed corporate mergers in the health insurance market.   Anthem has agreed to acquire Cigna and Aetna is taking over Humana. That means the number of big health insurers will drop from five to three.

The Times and every other commentator who has weighed in including the AMA has warned that diminished competition is not good for taxpayers or consumers. They want the Justice Department to take a long hard look at these latest mergers to insure that consumers are not stuck with higher premium costs as many parts of the country turn into markets with only one insurance provider.

The critics are wrong. Blocking these deals is a terrible idea. The mergers should be allowed to continue. In fact they should proceed until there is only one private insurer left. Only, at that point should the government step in, declare the last company standing to be required to merge with Medicare thereby letting the free market produce what many reformers have only been able to dream of—a single payer system.

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Qualcomm Life adds inpatient strategy with Capsule purchase

Qualcomm Life has built a big ecosystem of device partners on its 2net platform, focusing mostly on moving data from devices used by patients in their home. Today they sped up that development by buying Capsule which has a strong business on integrating data between different devices in the hospital.

I had a quick interview with Rick Valencia, GM of Qualcomm Life about their business. Two quick things to note. 1) I’m on the Qualcomm Life Advisory Board (although I knew nothing about this acquisition beforehand) and 2) I caught Rick at the end of a long day and tried to get him to talk about some recent customer data but neither of us could remember the reference. I was hoping he’d tell me more about this successful roll out of the 2net ecosystem in Northern Arizona, which is well worth a read. Meanwhile for more on Qualcomm & Capsule, watch the interview.

Health Information Technology: A Guide to Study Design For the Perplexed

Evidence is mounting that publication in a peer-reviewed medical journal does not guarantee a study’s validity. Many studies of health care effectiveness do not show the cause-and-effect relationships that they claim. They have faulty research designs. Mistaken conclusions later reported in the news media can lead to wrong-headed policies and confusion among policy makers, scientists, and the public. Unfortunately, little guidance exists to help distinguish good study designs from bad ones, the central goal of this article.

There have been major reversals of study findings in recent years. Consider the risks and benefits of postmenopausal hormone replacement therapy (HRT). In the 1950s, epidemiological studies suggested higher doses of HRT might cause harm, particularly cancer of the uterus. In subsequent decades, new studies emphasized the many possible benefits of HRT, particularly its protective effects on heart disease — the leading killer of North American women. The uncritical publicity surrounding these studies was so persuasive that by the 1990s, about half the postmenopausal women in the United States were taking HRT, and physicians were chastised for under-prescribing it. Yet in 2003, the largest randomized controlled trial (RCT) of HRT among postmenopausal women found small increases in breast cancer and increased risks of heart attacks and strokes, largely offsetting any benefits such as fracture reduction.

The reason these studies contradicted each other had less to do with the effects of HRT than the difference in study designs, particularly whether they included comparable control groups and data on preintervention trends. In the HRT case, health-conscious women who chose to take HRT for health benefits differed from those who did not — for reasons of choice, affordability, or pre-existing good health. Thus, although most observational studies showed a “benefit” associated with taking HRT, findings were undermined because the study groups were not comparable. These fundamental nuances were not reported in the news media.

Another pattern in the evolution of science is that early studies of new treatments tend to show the most dramatic, positive health effects, and these effects diminish or disappear as more rigorous and larger studies are conducted. As these positive effects decrease, harmful side effects emerge. Yet the exaggerated early studies, which by design tend to inflate benefits and underestimate harms, have the most influence.

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ACA Database: The Doctor Is a Monopoly

Undisclosed location, TN writes:

flying cadeuciiI have a concern that some of the medical specialty groups of physicans in my area are forming their own monopolies. They are joining together in a way that patients can no longer have access to a new physician if they feel they are not getting the care they need or are not comfortable with the physician they chose.

The [ name withheld ] or [ withheld ] Tn. is one of those groups.

I had been seeing one of their physicians for a number of years and had wanted to try someone else for a long time before I actually tried.  I was told that I could not see any other physician in the group.  When I then tried to go elsewhere, I discovered their group was the only game in town.  I called several hospitals to try and find a doctor.  They all named this one group.  There were a lot of physicans, but they were all connected to the group.  I then tried Maryville only to find, they also were part of this group.

My cardiologist tried to get me an appointment only to be told they could not see me.

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Goldilocks and The Three Bearers of Value-Based Health Reform

Brian F

While serving as a panelist at a recent health care conference in New York, an audience member asked me how we’re advising clients to help them navigate the transition from volume to value-based systems.

So I talked about Goldilocks, using the time-honored children’s story as a metaphor for steering clear of extremes, maintaining a steady pace, and not going too fast or too slow. Heads nodded in agreement, a sign I was striking a responsive chord.

I’m not comparing the complexity of current health reform to a fairy tale. But, choosing the path that’s “just right,” to quote Goldilocks herself, is central to an organization’s ability to adapt to a value-based care system that relies on new and creative collaborations and data analytics to reduce cost and improve patient outcomes.

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Getting (to the Value) of Value In Health Care

Susan-Dentzer-For PostHow would you judge the value of your health care? A longstanding definition of treatment holds that value is the health outcomes achieved for the dollars spent. Yet behind that seemingly simple formula lies much complexity.

Think about it: Calculating outcomes and costs for treating a short-term acute condition, such as a child’s strep throat, may be easy. But it’s far harder to pinpoint value in a long-term serious illness such as advanced cancer, in which both both the outcomes and costs of treating a given individual—let alone a population with a particular cancer—may be unknown for years. And then there’s the complicating issue of our individual preferences, since one person’s definition of a good outcome—say, another few years of life—may differ from another’s, who may be seeking a total cure.Continue reading…

The AMA’s Forgotten Fight Against Physician Greed

Michael MillensonPerhaps the most well-known part of the 1965 Medicare creation tale is the opposition by the American Medical Association (AMA) to “socialized medicine.” Yet with financial incentives assuming a new prominence for provider and patient alike, we shouldn’t overlook the AMA’s equally unsuccessful battle against the excesses of capitalistic medicine. The forgotten story of the professionalism’s failure to contain physician greed provides an important policy perspective.

The Myth Of Medicine’s ‘Golden Age’

Medical practice pre-1965 is often portrayed as a mythical “Golden Age.” The truth, as I found researching my 1997 book, Demanding Medical Excellence: Doctors and Accountability in the Information Age, was that the post-war years were a time when way too many doctors grasped for the gold.

The most common “entrepreneurial” excesses were fee splitting, where a specialist paid a kickback to the referring doctor, and ghost surgery, where a surgeon secretly paid a colleague to operate on an anesthetized patient. The first surgeon paid the “ghost” a small part of the total fee and pocketed the difference. Even worse was rampant surgical overuse, where common excesses included appendectomies for stomachaches and hysterectomies on young women with nothing more than back pain.

Although professional societies wielded far more influence than now, efforts by leaders of the AMA and the American College of Surgeons to stop these abuses repeatedly fell short. Doctors “display a consistent preoccupation with their economic insecurity,” a 1955 report by the AMA concluded with discomfiting bluntness.

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Why Data Governance Needs a Henry Kissinger

Dale SandersThe number of mergers, acquisitions, and collaborative partnerships in healthcare continues to skyrocket. That’s not going to change for the next few years unless the FTC decides to be more restrictive. In all of these activities, older generation executives (I can say that because I’m older) have underestimated the importance and difficulties—technically and culturally—of integrating data and data governance in these new organizations, and the difficulties are exponentially more complicated in partnerships and collaboratives that have no formal overarching governance body. In 2014, 100 percent of Pioneer ACOs reported that they had underestimated the challenges of data integration and how the lack of data integration has had a major and negative impact on the performance of the ACOs.

Seamless Data Governance

After 33 years of professional observations and being buried up to my neck in this topic, especially the last two years as the topic finally matures in healthcare, I’m convinced that the role model organizations in data governance practice it seamlessly. That is, it’s difficult to point a finger directly at a thing called “Data Governance” in these organizations, because it’s completely engrained, everywhere. As I’ll state below, it reminds me of the U.S. transition in the early 1980s when organizations finally realized that product quality was not something that you could put in an oversight-driven Quality Department, operating as a separate function. Quality must be culturally embedded in every teammates’ DNA. Data governance is the same, especially data quality.Continue reading…

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