The Health Care Blog – Page 379 – Everything you always wanted to know about the Health Care system. But were afraid to ask.

Above the Fold

How Not to Research ACOs

Feb 22, 2016• 9

By KIP SULLIVAN

flying cadeucii In Part I of this series I noted that we have almost no useful information on what ACOs do that affects cost and quality. I described two causes of that problem: The amorphous, aspirational “definition” of ACOs, and the happy-go-lucky attitude toward evidence exhibited by ACO proponents and many analysts. I showed how the flabby “definition” of ACO makes it impossible to operationalize this thing – to reduce it to testable components. And I asked why the health policy community let ACO proponents get away with such a vague description of the ACO. I said the answer lies in the permissive culture of the US health policy community. It is a culture that tolerates, even encourages, the promotion of vague concepts and a cavalier attitude toward evidence.

In this installment, I illustrate these problems – the vague definition of “ACO,” and loose standards of evidence – by examining a paper published last month by the Center for Health Care Strategies (CHCS) entitled, “Accountable Care Organizations: Looking back and moving forward.” In the third installment of this series I will describe the emergence of the health policy culture that tolerates intellectually flabby proposals and a devil-may-care attitude toward evidence.

I chose the CHCS paper because the organization that funded it, the Robert Wood Johnson Foundation, and the organization that wrote it are prominent advocates of managed care and its latest iteration, the ACO. The Foundation describes itself as “an early supporter of the idea that later became known as managed care” The Foundation announced last July it “has been supporting … ACOs for several years now.” CHCS was established two decades ago with support from the Foundation, and receives funding from organizations that promote managed care and ACOs.

Moreover, the paper’s authors and funders made it clear they hoped the paper would provide a useful update on what ACOs have accomplished and how they accomplished it. In its July 2015 announcement of the $20,000 grant that supported this study, the Foundation said the study would “inform stakeholders of progress to date by accountable care organizations.” CHCS’s paper claims it “identifies key lessons from ACO activities across the country to date” (p. 1).

Apple and the 3 Kinds of Privacy Policies

Feb 22, 2016• 12

By ADRIAN GROPPER, MD

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Why Are Apple’s Competitors Staying Silent On the iPhone Unlocking Fight? is the question of the day on tech blogs. The answer is hardly technical and may not be legal, it’s all about privacy policies and business strategy and it is very evident in healthcare.

There are three classes of privacy policy in healthcare and everywhere else:

Class 1 – “Apple will not see your data.” This is Apple’s privacy policy for ResearchKit and HealthKit and apparently for whatever data the FBI is hoping to read from the terrorist’s phone. Obviously, in this case the person is in complete control of the data and it can be shared only with third-parties that the person authorizes.

Class 2 – “We will see and potentially use your data but you will have first-class access to your data”. This is the kind of privacy policy we see with Apple’s calendar and many Google services. The personal data is accessible to the service provider but it is also completely accessible via an interface or API. In healthcare, the equivalent would be having the FHIR API equally and completely accessible to patients and to _any_ third-parties authorized by the patient. This is Patient Privacy Rights’ recommendation as presented to the API Task Force.

Class 3 – “We will use your data according to xyz policy and if you don’t like it, take your illness elsewhere.” This is pretty much how healthcare and much of the Web world runs today. We have limited rights to our own data. On the other hand, the services that have our data can sell it and profit in dozens of ways. This includes selling de-identified data. In Class 3, you, the subject of the data are a third-class citizen, at best. In many cases, the subject doesn’t even know that the data exists. See, for example, The Data Map.

We are so completely engulfed by Class 3 privacy policies that we have lost perspective on what could or should be. A Class 1 policy like Apple’s is widely seen as un-American. A Class 2 policy like PPR’s is indirectly attacked as “insurmountable”.

A Reset For Workplace Wellness?

Feb 21, 2016• 1

By HARRIS ALLEN

flying cadeucii “The way I see it, if you want the rainbow, you gotta put up with the rain.”– Dolly Parton

Sometimes, helpful perspective can be found in the most unexpected places. Ms. Parton may be better known for her achievements in country music, but her maxim also applies to certain aspects of the public dialogue on workplace wellness that have become a recurrent feature..

An example is a thread that has its roots in a blog invited two-part response counter-response (i.e., see the comments at the end of Part II) exchange between Al Lewis (aka whynobodybeliev) and myself that began November, 2014. The resumption of this exchange was initiated with my comments on a 12/4/15 post on this blog page from Ms. Dentzer, who noted the focus on return on investment that dominated the “debate” between Goetzel and Lewis on workplace wellness at the PHA Forum 2015. Her post offered some questions for positioning future like-minded events in more looking forward ways. My 12/19/15 post, also on this page, offered a supplement to her formulation by urging wellness program implementers to also take stock of the empirical work that has been done to date on program impact. Indeed, it urged implementers to consider (re-) setting their sights toward the top end of what has been shown to be possible and referenced the success that Navistar achieved during the 1999-2009 period as a model. This, in turn, prompted another sharply worded response from Mr. Lewis, expressed in terms that were not only reminiscent of his counter-response noted above but have also come to typify much of his published commentary in this area, even on work that has met the test of peer-review.

A Better Pathway to Acute Care

Feb 21, 2016• 2

By KAREN SIBERT, MD

flying cadeucii When patients need acute interventional care, coordinating the transitions away from and back to primary care is a challenge. The common pathway for these patients, no matter what their diagnosis, is an encounter with anesthesiology. But it often happens too late in the process. If we’re involved earlier, physician anesthesiologists can help reduce procedure risk, control costs, and improve the long-term health of this high-risk, high-spend population.

The numbers haven’t changed significantly in several years—only five percent of the U.S. population consumes a full 50 percent of annual health care spending, and just one percent is responsible for nearly 23 percent of spending.

CMS Is the Reason We Have so Little Useful ACO Research

Feb 19, 2016• 4

By DAVID INTROCASO

flying cadeucii In his THCB essay, “Why We Have So Little Useful Research on ACOs,” Kip Sullivan correctly notes we know surprisingly little about the ACO program. (While he identifies Medicare, Medicaid and commercial plan ACOs, here I’m referring specifically to the Medicare Shared Savings Program (MSSP) ACOs that account for two-thirds of all ACOs.) Why there is little useful research is however not due to the two reasons Mr. Sullivan proposes. To understand why we lack useful ACO research look no further than the agency that manages the MSSP.

Mr. Sullivan’s explanations are: since ACOs have been defined amorphously or aspirationally they cannot be assessed based on a prescribed set of activities or services; and, policy analysts have been “cavalier” program performance-related evidence. Neither explanation is correct. Medicare ACOs are defined regulatorily in great detail. This fact is made obvious by the, to date, 430-relevant Federal Register pages. Generally defined MSSP ACOs are a model of care delivery that increasingly shifts financial risk from the payer to the provider in order to reduce spending growth and, though less definitively determined, improve care quality and patient health outcomes. An MSSP ACO’s “prescribed activities” are simply to provide beneficiaries all necessary Medicare Part A and B services. To define them beyond that or to expect the same precision or efficacy in delivering timely, comprehensive, population-based health care as administering a single prescription drug, as Mr. Sullivan would like, is impossible. Arguing ACO researchers or stakeholders are “cavalier” about how best to define and measure the program ignores, among other things, the fact CMS received over 1,670 comment letters in response to the agency’s 2011 and 2014 proposed MSSP rules.

Is Big Data a Big Deal…or Not?

Feb 19, 2016

By HealthCatalyst SPONSORED CONTENT

Dale Sanders The term “Big Data” emerged from Silicon Valley in 2003 to describe the unprecedented volume and velocity of data that was being collected and analyzed by Yahoo, Google, eBay, and others. They had reached an affordability, scalability and performance ceiling with traditional relational database technology that required the development of a new solution, not being met by the relational data base vendors.

Through the Apache Open Source consortium, Hadoop was that new solution. Since then, Hadoop has become the most powerful and popular technology platform for data analysis in the world. But, healthcare being the information technology culture that it is, Hadoop’s adoption in healthcare operations has been slow.

Date: Wednesday, February 24, 2016

Time: 1:00–2:30 PM ET

In this webinar, Dale Sanders, Executive Vice President of Product Development at HealthCatalyst will explore several questions:

Why should healthcare leaders and executives care about this technology?

What makes Hadoop so attractive and rapidly adopted in other industries but not in healthcare?

Why is Big Data a bigger deal to them than healthcare?

What do they see that we don’t and are we missing the IT boat again?

How is the cloud reducing the barriers to adoption by commoditizing the skilled labor impact at the local healthcare organizational level?

This webinar is intended to be valuable to both technical and non-technical audiences, as we explore the convergence of Big Data technology and Healthcare’s Age of Analytics.

A New Data Sharing Architecture for Medicine

Feb 19, 2016• 1

By BEN HEYWOOD

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Introduction: Dave Chase and Leonard Kish have been crowdsourcing 95 Theses for a New Healthcare Ecosystem. They have also asked those leading the development of the new ecosystem to offer insights into their own take on each of the theses. This is the first installment from Ben Heywood, Co-founder and President, PatientsLikeMe (PLM). Dave and Leonard believe the recent moonshot for cancer proposed by vice-president Joe Biden, highlighting the need for more data sharing, and the related uproar over research data sharing from the NEJM editorial, show that the need for a new architecture and a new ecosystem, based on sharing, all the more immediate. PLM, as one of the first successful peer to peer health data sharing applications, may serve as a model.

Thesis # 5. Ben Heywood:

A new science will arrive at evidence-based understanding of what works through a great wealth of shared longitudinal health data captured through mobile devices, sensors and health records. This science will be mindful of the concept of transforming Data, to Information, to Knowledge, to Wisdom.
Ben Heywood, Co-founder and President, PatientsLikeMe

If we’re going to talk about evidence-based understanding in the context of a reinvented and redefined health system, we need to first reassess what we mean by evidence, and redefine how we understand it.

When most people think of medical evidence, they think of carefully controlled studies in peer-reviewed journals. The “pyramid of evidence” runs from animal studies and editorials through case series and clinical trials, all the way up to systematic meta-analysis. There’s an emphasis on clinical trials, and it’s strong. But the pyramid reflects a very black and white view of the world—good quality evidence exists, or it does not.

In reality, the evidence we rely on to practice medicine every day is a lot more ambiguous, and grey. Physicians and patients make crucial decisions on the basis of limited evidence and incomplete records. They do so for comorbid or “hard to reach” populations that never take part in research in the first place.

Electronic Health Records: From Ebola to Zika, Fighting the Last War

Feb 17, 2016• 5

By SHIRA FISCHER

flying cadeucii When I showed up at the obstetrical urgent care unit at Brigham and Women’s Hospital, the care I received was swift and appropriate. I saw a nurse quickly and a doctor soon after. They asked relevant questions and immediately put a plan for further evaluation in place. Only then did the nurse turn to the computer to enter everything into the electronic record. As she worked her way through the required documentation, she asked several more questions. Any allergies that weren’t already in the system? Surgeries she should note? And, of course, importantly, had I been to an Ebola-infected country recently?

In September 2014, Texas Health Presbyterian Hospital missed acting upon the fact that a patient had just returned from West Africa, even though it was documented in his record. He came down with Ebola, but wasn’t treated with appropriate precautions, and many patients and staff were put at risk. The hospital was publicly criticized for its behavior. The hospital administration responded by blaming its electronic health records (EHR), since the system didn’t bring the travel history to the forefront as part of the doctor’s workflow. Since then, hospitals have scrambled to systematically screen for the often-fatal virus that took more than 10,000 lives in the past three years. Hospitals have incorporated a relevant screening question into their EHR, like the one I was dutifully asked during my recent urgent care visit. A win for technology and public health?

Why We Have so Little Useful Research on ACOs

Feb 16, 2016• 16

By KIP SULLIVAN

flying cadeucii Our country urgently needs research on the impact of “accountable care organizations” on cost and quality. The ACO has been the establishment’s great hope for health care reform since the concept was invented at the November 9, 2006 meeting of the Medicare Payment Advisory Commission. If ACOs are not going to work, we need to know sooner rather than later.

Although it’s been almost a decade since the ACO concept was invented and six years since Congress endorsed it, we know remarkably little about ACOs. What little reliable research we have was done on CMS’s ACO programs, but even that research is woefully incomplete. As for the ACOs set up by state Medicaid agencies and insurance companies, we know almost nothing.

Yes, I know, we have a few dozen papers telling us where ACOs are starting up, whether physicians or hospitals are “leading” them, and whether their managers tells pollsters they can “monitor care across the continuum” and “have programs in place to reduce hospital admissions,” etc. But we have no idea what ACOs do for patients that non-ACO providers do not do.

There are two reasons for this information vacuum. The first is the definition of the ACO. ACO proponents have never defined the ACO; they have told us only what they hope ACOs will do (they tell us they want ACOs to “hold providers accountable”). The second problem is the cavalier attitude toward evidence with which ACO proponents and analysts approach ACO research. Until the US health policy community addresses these problems, the dearth of useful research on ACOs will continue.

In this comment, I will describe these twin problems – the amorphous, aspiration-based definition of ACO, and the casual attitude toward evidence exhibited by ACO proponents and analysts. In Part II of this series I will illustrate these problems with a report on ACOs financed by the Robert Wood Johnson Foundation. The report, entitled “Accountable Care Organizations: Looking back and moving forward,”http://www.chcs.org/media/ACOs-Looking-Back-and-Moving-Forward.pdf was released last month by the Center for Health Care Strategies. In Part III I will argue that the vague definition of ACOs and the cavalier attitude toward evidence exhibited by ACO proponents is a result of a permissive culture that evolved first within the managed care movement and then spread throughout the American health policy community.

Why I Don’t Believe In Science

Feb 16, 2016• 14

By MICHEL ACCAD, MD

A few days ago, cardiologist and master blogger John Mandrola wrote a piece that caught my attention. More precisely, it was the title of his blog post that grabbed me: “To Believe in Science Is To Believe in Data Sharing.”

Mandrola wrote about a proposal drafted by the International Committee of Medical Journal Editors (ICMJE) that would require authors of clinical research manuscripts to share patient-level data as a condition for publication. The data would be made available to other researchers who could then perform their own analyses, publish their own papers, etc.

The ICMJE proposal is obviously controversial, raising thorny questions about whether “data” are the kinds of things that can be subject to ownership and, if so, whether there are sufficient ethical or utilitarian grounds to demand that data be “forked over,” so to speak, for others to review and analyze.

Now all of that is of great interest, but I’d like to focus attention on the idea that conditions Mandrola’s endorsement of data sharing. And the question I have is this: Should we believe in science?

Mandrola’s belief in science must assume that medical science can reveal durable answers, truths upon which we can base our clinical decisions confidently. He comments:

I often find myself looking at a positive trial and thinking: “That’s a good result, but can I believe it?”…Are the authors, the keepers of the data sets, telling the whole story?