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Tag: Quality

What Will Tomorrow’s Doctor Look Like?

“What does the 21st Century Physician look like?”

Lisa Fields (@PracticalWisdom) cc’ed me on a tweet about this; it’s the featured question at www.tomorrowsdoctor.org, an organization founded by three young professionals who spoke at TEDMED last year.

I’ll admit that the question on the face of it struck me as a bit absurd, especially when juxtaposed with the term “tomorrow’s doctor.”

Tomorrow’s doctor needs to be doing a much better job of dealing with today’s medical challenges, because they will all be still here tomorrow. (Duh!) And the day after tomorrow.

(As for the 21st century in general, given the speed at which things are changing around us, seems hard to predict what we’ll be doing by 2050. I think it’s likely that we’ll still end up needing to take care of elderly people with physical and cognitive limitations but I sincerely hope medication management won’t still be a big problem. That I do expect technology to solve.)

After looking at the related Huffington Post piece, however, I realized that this trio really seems to be thinking about how medical education should be changed and improved. In which case, I kind of think they should change their organization’s name to “Next Decade’s Doctor,” but I can see how that perhaps might not sound catchy enough.

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The Promises and Pitfalls of Pay for Performance

There’s been a great deal of discussion about health care payment reform. Prominent in this discussion is “Pay for Performance” (P4P). The idea is simple — rather than pay providers based on volume of care (fee-for-service) or number of patients (capitation), tie their payment to a measure(s) of performance. There has been substantial concern about the quality of care delivered to patients, so pay for performance appears to make a lot of sense. Don’t we want to reward providers for good performance? Shouldn’t this encourage them to provide high quality care?

Unfortunately, this is not as straightforward as it might appear. While the idea of pay for performance is very appealing and intuitive, there are some major pitfalls in implementation.

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The Health IT Scandal the NY Times Didn’t Cover

In case you missed it, the shocking news was that health IT companies that stood to profit from billions of dollars in federal subsidies to potential customers poured in ­– well, actually, poured in not that much money at all when you think about it ­– lobbying for passage of the HITECH Act in 2009. This, putatively, explains why electronic health records (EHRs) have thus far failed to dramatically improve quality and lower cost, with a secondary explanation from athenahealth CEO Jonathan Bush that everything would be much better if the HITECH rules had been written by Jonathan Bush of athenahealth.

Next up: corporate lobbying for passage of the 1862 Pacific Railroad Bill is blamed for Amtrak’s dismal on-time record in 2013.

The actual scandal is more complicated and scary. It has to do with the adamant refusal by hospitals and doctors to adopt electronic records no matter what the evidence. Way back in 1971, for example, when Intel was a mere fledgling and Microsoft and Apple weren’t even gleams in their founders’ eyes, a study in a high-profile medical journal found that doctors missed up to 35 percent of the data in a paper chart. Thirty-seven years later, when Intel, Microsoft and Apple were all corporate giants, a study in the same journal of severely ill coronary syndrome patients found virtually the same problem: “essential” elements to quality care missing in the paper record.

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Data Mining Systems Improve Cost and Quality of Healthcare – Or Do They?

Several email lists I am on were abuzz last week about the publication of a paper that was described in a press release from Indiana University to demonstrate that “machine learning — the same computer science discipline that helped create voice recognition systems, self-driving cars and credit card fraud detection systems — can drastically improve both the cost and quality of health care in the United States.” The press release referred to a study published by an Indiana faculty member in the journal, Artificial Intelligence in Medicine [1].

While I am a proponent of computer applications that aim to improve the quality and cost of healthcare, I also believe we must be careful about the claims being made for them, especially those derived from results from scientific research.

After reading and analyzing the paper, I am skeptical of the claims made not only by the press release but also by the authors themselves. My concern is less about their research methods, although I have some serious qualms about them I will describe below, but more so with the press release that was issued by their university public relations office. Furthermore, as always seems to happen when technology is hyped, the press release was picked up and echoed across the Internet, followed by the inevitable conflation of its findings. Sure enough, one high-profile blogger wrote, “physicians who used an AI framework to make patient care decisions had patient outcomes that were 50 percent better than physicians who did not use AI.” It is clear from the paper that physicians did not actually use such a framework, which was only applied retrospectively to clinical data.

What exactly did the study show? Basically, the researchers obtained a small data set for one clinical condition in one institution’s electronic health record and applied some complex data mining techniques to show that lower cost and better outcomes could be achieved by following the options suggested by the machine learning algorithm instead of what the clinicians actually did. The claim, therefore, is that if the data mining were followed by the clinicians instead of their own decision-making, then better and cheaper care would ensue.

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The 30-day Readmission Rate: Not a Quality Measure but an Accountability Measure

Should we hold hospitals accountable for what happens after a patient leaves the hospitals’ doors? A year ago, I thought the answer was no. A hospital’s job was to take care of sick patients, make them better and send them on their way. With more thought and consideration, I have come to conclude that I was probably wrong. It may be perfectly reasonable to hold hospitals accountable for care beyond their walls, but we should be clear why we’re doing it. Readmissions are not a good quality measure – but they may be a very good way to change the notion of accountability within the healthcare delivery system.

The debate around the readmissions measure has come to the forefront because of the CMS Hospital Readmission Reduction Program, which penalizes hospitals for “greater than expected” readmission rates. It has raised the question — does a hospital’s 30-day readmission rate measure the “quality of care” it provides? Over the last three years, the evidence has come in, and to my read, it is unequivocal. By most standards, the readmissions metric fails as a quality measure.

Why do I say that readmissions are a poor measure of hospital quality? First, we have to begin by thinking about what makes a good quality measure. Quality is about the essence of the thing being produced – a good or a service. The job of a car is to get you from place A to place B and a high-quality car may be one that does the job reliably, safely, or maybe even comfortably. The job of a restaurant is to provide a meal that you don’t have to cook — and a high quality restaurant may provide food that is fresh, tasty, or with an attention to service that you enjoy. What is the job of a hospital? When you get sick and require hospital services, a high-quality hospital should give you the right treatments, attend to your needs while you’re there, and make sure nothing bad (i.e. a new nosocomial infection) happens along the way. That’s how we measure hospital quality.

Quality measures for healthcare come in three flavors – structural measures (do you have enough intensivists manning your ICU?), processes measures (did you give the heart attack patient his or her aspirin?) and outcomes measures (did the pneumonia patient die?). The elemental part of both structural measures and process measures is that they have to be tied to an outcome we care about. If having more intensivists in the ICU does not lead to lower ICU mortality (or lower complication rates), we wouldn’t think it’s a particularly good quality measure. We know that giving aspirin to heart attack patients lowers their chances of dying by 25%. We have multiple randomized trials. We don’t need much more evidence. Hospitals that have the right structures in place and reliably deliver the right treatments can reasonably be called high-quality hospitals.

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Getting Pay-For-Performance Right

Over the past decade, there has been yet another debate about whether pay-for-performance, the notion that the amount you get paid is tied to some measure of how you perform, “works” or not. It’s a silly debate, with proponents pointing to the logic that “you get what you pay for” and critics arguing that the evidence is not very encouraging. Both sides are right.

In really simple terms, pay-for-performance, or P4P, can be thought about in two buckets: the “pay” part (how much money is at stake) and the “performance” part (what are we paying for?). So, in this light, the proponents of P4P are right: you get what you pay for. The U.S. healthcare system has had a grand experiment with P4P: we currently pay based on volume of care and guess what? We get a lot of volume. Or, thinking about those two buckets, the current fee-for-service structure puts essentially 100% of the payments at risk (pay) and the performance part is simple: how much stuff can you do? When you put 100% of payments at risk and the performance measure is “stuff”, we end up with a healthcare system that does a tremendous amount of stuff to patients, whether they need it or not.

Against these incentives, new P4P programs have come in to alter the landscape. They suggest putting as much as 1% (though functionally much less than that) on a series of process measures. So, in this new world, 99%+ of the incentives are to do “stuff” to patients and a little less than 1% of the incentives are focused on adherence to “evidence-based care” (though the measures are often not very evidence-based, but let’s not get caught up in trivial details). There are other efforts that are even weaker. None of them seem to be working and the critics of P4P have seized on their failure, calling the entire approach of tying incentives to performance misguided.

The debate has been heightened by the new national “value-based purchasing” program that Congress authorized as part of the Affordable Care Act. Based on the best of intentions, Congress asked Medicare to run a program where 1% of a hospital’s payments (rising to 2% over several years) is tied to a series of process measures, patient experience measures, and eventually, mortality rates and efficiency measures. We tried a version of this for six years (the Premier Hospital Quality Incentives Demonstration) and it didn’t work. We will try again, with modest tweaks and changes. I really hope it improves patient outcomes, though one can understand why the skeptics aren’t convinced.Continue reading…

Building a Better Health Care System: Should We Be Tracking Misdiagnosis?

If you study misdiagnosis you realize how often patients get the wrong diagnosis.

But what do expert doctors think about how often it happens? And what do they think can be done to address it?

We wanted to find out so we partnered with the National Coalition on Healthcare to conduct a landmark, nationwide survey. We surveyed 400 cancer specialists from our Best Doctors database – and the findings were provocative.

The survey, “Exploring Diagnostic Accuracy in Cancer: A Nationwide Survey of 400 Leading Cancer Specialists,” focused on what doctors believe to be the most significant barriers in efforts to accurately diagnose cancers; the types of cancer they believe are most often misdiagnosed; and the tools and improvements they most need to combat misdiagnosis.

One of the most surprising findings was on how often doctors believe misdiagnosis happens. While published studies show that misdiagnosis occurs in about 15-28% of cases, the large majority of doctors we surveyed thought it happens in less than 10% of cases. At the same time, doctors recognized that the root causes of misdiagnosis were very prevalent – fragmented medical information, disparities in experience among pathologists and other factors.

So – how to explain the difference in doctors’ perceptions and the published research? I think it is because there is no systematic feedback loop for doctors letting them know of inaccuracies in their care. If you diagnose someone and they go on to get treatment someplace, and it’s later discovered that a diagnosis wasn’t exactly right, the original doctor may never find out about it. If you don’t hear about it, you can’t be blamed for thinking this problem is rare. It also means you miss out on the opportunity to improve the quality of care that these cases represent.

Another interesting point. Doctors reported that, regardless of how often they thought diagnostic inaccuracies happened, it is a problem that needed more attention from policy-makers. As NCHC President and CEO John Rother observed, “Not enough is being done on the state and federal policy end of things to acknowledge and firmly address this critical issue. Given our current health care climate and challenges, as decision-makers become more aware of the frequency of misdiagnosis and the enormous costs associated with it, they have a sizeable opportunity to make diagnostic accuracy much more of a ‘front and center’ issue in health care.”

Here’s to that promising thought.

Evan Falchuk is Vice Chairman of Best Doctors, Inc., where this post originally appeared. Prior to joining Best Doctors, Inc., in 1999, he was an attorney at the Washington, DC, office of Fried, Frank, Harris, Shriver and Jacobson, where he worked on SEC enforcement cases. This post originally appeared on Best Doctors, Inc.’s See First Blog.

Are Healthcare and Health IT in a Dysfunctional Relationship?

What a week last week! First the disgraced cyclist confession and later the baffling college-football-player-and-his nonexistent-(dead)-girlfriend story, with the RAND report sandwiched somewhere in between. It’s positively a scandal-palooza.

What’s that? You don’t feel like the recent RAND report, which basically says that a 2005 RAND study financed by GE and Cerner was wildly optimistic in predicting about $81 billion in potential health care cost savings through widespread adoption of electronic health records, qualifies as a genuine hoax, controversy, scandal?

Me neither.

But it does neatly frame what is arguably a unique characteristic of the healthcare industry—a trait that extends to peripheral industries as well. Basically, healthcare is an interconnected environment. Call it the systems theory of healthcare, co-dependency … or just regular dependency. Call it what you want, but there is an interconnectedness in healthcare that we ignore at the expense of national wellness.

Witness key data points provided by the RAND report:

  • Modern health IT systems are not interconnected and interoperable, functioning “less as ‘ATM cards,’ allowing a patient or provider to access needed health information anywhere at any time, than as ‘frequent flier cards’ intended to enforce brand loyalty…”
  • Neither are they widely adopted, with an estimated 27 percent of hospitals utilizing a basic electronic record. Without broad adoption, interoperability is far less relevant.
  • Improvements in quality of care / patient safety and reductions in healthcare costs (which have grown by $800 billion since 2005) are not manifesting with EHR adoption, in part because hospitals and clinics are rushing to adopt mediocre solutions and garner federal funds.
  • The provision of care is the same as it ever was, even though EHRs are frequently promoted as the optimal tool for a different kind of care.

The reasons for these disappointing stats are readily apparent and unalterably interconnected.
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Why Employers Should Stop Worrying About Health Costs

A report published by the Institute of Medicine (IOM) on high-value health care attracted attention when it was issued last June. Authored by a group of eleven leading hospital executives, A CEO Checklist for High-Value Health Care describes programs at various hospitals that resulted in quality improvements and lowered costs. The report has a section called “Yield,” quantifying the extent of these improvements. These programs sound notable, and in fact I know some of the executives and hospitals involved, and would vouch that many significantly improved patient care.

But the report is less impressive when it tackles the cost side of the value equation, especially when it names cost control outcomes like: “days cash on hand increased from 180 to 202,” and “multiple years of 4-5 percent [hospital] margin.” Clearly, the hospitals improved their own bottom lines, but by how much did patient bills decrease? The hospital executives don’t account for that in the “yield.”

It seems this report defines “high-value” to mean highly valuable to hospital CEOs. Strikingly, though, the authors do not find it necessary to explicitly say so anywhere within the report. Perhaps they simply assume that a high-value checklist for hospital CEOs is automatically high-value to CEOs in other industries that are paying for services from hospitals. No offense to these well-meaning and highly accomplished hospital executives, but that is not always the case. Purchasers don’t see high-value health care in hospital cash flow or profit margins. They see value when they get the best service at the best price.

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Why ACOs Are not HMOs and Other Important Questions

Mohammad Al-Ubaydli: Let’s just start from the beginning. Tom, can you please give us an introduction about yourself and your background?

Thomas Tsang: I’m a general internist by training. I practiced internal medicine in New York City, first at a small community hospital where I predominantly worked with residents and medical students and mostly taught principles of outpatient medicine, ambulatory care and interviewing techniques.

Then I was recruited by the Charles B. Wang Community Health Center. That’s when I got to use some of the public health knowledge that I had acquired: I worked on various public health initiatives for the community in New York City. The health center itself served a predominantly Asian population. It had four sites and one of the things that I did in the beginning was implement an electronic health record. That work led to my involvement with the Board of Health of New York City, which, in turn led to my work in Congress.

I was then selected for the Robert Wood Johnson Foundation/IOM Health Policy Fellowship on the Committee on Ways and Means-Subcommittee on Health and worked on some of the policies that led to the creation of ACO’s, i.e., Value-Based Purchasing, Pay for Performance and so on. I was fortunate enough to actually help implement some of the policies that I worked on! It’s a long answer to your question, but that’s the route I took.

Mohammad: It’s perfect. It’s really interesting to learn. Among the many things under your belt, it sounds like you have a successful electronic health record deployment, which is good–so well done! Tell me and our readers a bit about Accountable Care Organizations. What is an ACO and what is the point of it?

Thomas: The ACO is not a very new concept. It was a term that was coined by Elliott Fisher from Dartmouth Medical School, who is the director of Center for Health Policy and Clinical Practice. I hate to use the word HMO, but in a way, it’s almost like an HMO. It’s not really an HMO because it is actually a provider-led organization, not an insurance-led one.

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