Measuring the quality of care and improving it over time is a fundamental obligation of healthcare providers. Increasingly, quality is also tied to reimbursement and is reported publicly. While I strongly agree with both trends, three recent articles point out some of the challenges ahead.
The common theme among them is that “risk-adjustment” is a hard thing to do. A brief diversion to provide some context.
There are two main ways to measure and compare quality. One is to assess processes of care, such as adherence to established best practices and evidence-based treatment guidelines. This is relatively easy to do, but is by definition highly reductionist. Clinicians understand that “good care” is more than the sum of a handful of isolated activities. Does anyone really think that good diabetes care is equivalent to measuring the HgbA1c level annually and making sure that everyone is screened for diabetic retinopathy? The other way to me is to assess patient outcomes, or how patients actually fare at the hands of different providers. This allows for comparison of endpoints that providers and patients find important, and frees providers to innovate. The challenge is that it is very difficult to separate the relative impacts of patients’ baseline characteristics from the care received in determining the outcomes.
Continue reading Adjusting the Adjustment
Every clinician knows that “framing” – how we present information to patients – has a big impact on decisions they make about their care. Even something as simple and apparently transparent as talking about “survival” versus “mortality” is important, with “a 90% chance of living” sounding a lot better than “a 10% chance of dying” even if both phrases convey the same estimate of risk.
Things get even more dicey when doctors start talking to patients about more subtle concepts like risk-reduction or number needed to treat. The clinical impact of a big relative risk reduction operating on a low absolute risk can be hard for doctors to explain and patients to understand.
The impact of that complexity was the subject of a recent editorial in Circulation. In it, Diprose and Verster speculate that doing a better job of explaining these things to patients, which certainly seems like a good idea, may paradoxically lead to worse population health outcomes. Here’s how it could happen.
Continue reading Prevention Paradox
I had a great time at the national meeting of the American College of Cardiology (ACC) this past weekend. I hadn’t been to “the meetings” in a few years, in part because my professional focus is no longer primarily clinical and well, I never really liked going even when it was. I generally believed (and still do) that I get more valuable information about new developments in cardiology by reading journals than by shlepping around some gargantuan convention center and listening to a few talks while dodging the barrage of drug and device manufacturers. Now that the results of “late breaking” clinical trials are instantly available (complete with slides and expert analysis) within hours of their presentation, I find the whole convention thing even less compelling.
So (with a nod toward the upcoming Passover holiday) why was this meeting different from all other meetings?
First, I had the pleasure of hearing my brother, David Nash, founding Dean of the Jefferson College of Population Health, deliver the Simon Dack lecture. As I said to him when he first told me he was invited (and wanted to know if it was a big deal), this is a big deal. It is the opening keynote for the conference, and is intended to set a tone or theme for the meeting, which draws almost 20,000 people from around the world. Here is a picture of him being introduced by the President of the ACC:
Continue reading Population (Heart) Health
It has been known for a long time that “healthcare” – all the stuff that we do, prescribe and provide – is a minor determinant of how “healthy” any of us is. Overall health, or more technically, the variability in health outcomes, is much more dependent on the combination of genetics, personal behavior (think smoking and seat belts), environmental factors and socioeconomic status than it is on healthcare.
I was thinking about that when I read in the New York Times about how some healthcare provider systems, driven by the need to cut costs, are starting to address some of the non-medical social needs of their patients. These kinds of innovative community-based interventions started to get traction after they were highlighted by an influential profile by Atul Gawande in the The New Yorker. Their diffusion has been driven by the expansion of novel payment models that have started to reward providers for reducing utilization of services like ER visits and hospitalizations, the very services that they have traditionally been paid for.
Continue reading Health and Healthcare
I wrote recently about the need to take into account patient characteristics when using patient outcomes to compare the quality of care provided by different physicians. That is a well-accepted principle, and the need for so-called “risk-adjustment” applies not only to evaluating physicians, but also to evaluating hospitals and larger care delivery systems. There has been a smoldering controversy, however, about which patient characteristics to consider and, in particular, the implications of including socioeconomic factors in such comparisons. This controversy played out again in a recent issue of the Annals of Internal Medicine.
Here is the core of the issue.
Continue reading Adjusting Outcomes
I was talking to a colleague last week about his practice, and remarked that he was still keeping a paper medical record. Without hesitation, he made it clear that he not only liked the paper record, but he positively dreaded switching to an electronic record. He said sadly that he thought it was inevitable that he would be forced to switch, but hoped that the day would be far into the future. Continue reading How to fix EMRs