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Why the Fragility of Health Outcomes Research May Be a Good Outcome for Health One Comment

From the 5 April 2012 article by DAVID SHAYWITZ, MD at The Health Care Blog

Durably improving health is really, really hard.
I’ve discussed this in the context of drug discovery, which must contend with the ever-more-apparent reality that biology is incredibly complex, and science remarkably fragile.  I’ve discussed this in the context of patient behavior, focusing on the need to address what Sarah Cairns-Smith and I have termed the “behavior gap.”
Here, I’d like to focus on a third challenge: measuring and improving the quality of patient care.
I’ve previously highlighted the challenges faced by Peter Pronovost of Johns Hopkins in getting physicians to adhere to basic checklists, or to regularly do something as simple and as useful as washing hands, topics that have been discussed extensively and in a compelling fashion by Atul Gawande and others….

…Consider the recent JAMA article (abstract only) by Lindenauer et al. analyzing why the mortality rate of pneumonia seems to have dropped so dramatically from 2003-2009.  Originally, this had been attributed to a combination of quality initiatives (including a focus on processes of care) and clinical advances.  The new research, however, suggests a much more prosaic explanation: a change in the way hospitals assign diagnostic codes to patients; thus, while rates for hospitalization due to a primary diagnosis of pneumonia decreased by 27%, the rates for hospitalization for sepsis with a secondary diagnosis of pneumonia increased by 178%, as Sarrazin and Rosenthal highlight in an accompanying editorial (public access not available).
Why did the coding pattern change? Multiple explanations were proposed by the authors; possibilities range from the benign — changes in diagnostic guidelines, greater awareness of sepsis, etc. – to the cynical (and quite likely) — utilizing different coding to maximize reimbursement.
One key take-home is that reliable measurement of health variables is so much more of a challenge than is typically appreciated, and ensuring that we’re robustly measuring what we think we’re measuring, rather than a paraphenomenon, is going to be very important.  We’re learning this lesson the hard way in so many areas of science, and health outcomes research is unlikely to be the solitary exception.
A second and equally important lesson is to remember that in many cases in health outcome research, the people who are doing the measurements and assessments often have a significant stake in the results, introducing the very real possibility of data distortion….


April 6, 2012 Posted by | health care | , , | Leave a comment


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