The push to make hospitals and doctors more accountable for health care quality means more attention must be paid to the accuracy and reliability of measures used to evaluate caregivers, according to Johns Hopkins patient safety expert Peter Pronovost.
There is little consensus as to which measures are scientifically valid and accurate assessments of quality, and this risks misinforming patients who may make decisions based on metrics that poorly reflect the state of health care, Pronovost wrote in the April issue of Health Affairs.
Pronovost supports the bipartisan effort to pay for value rather than volume with health care, but says serious work needs to be done to create a “whole library of outcome measures” such efforts require. Failure to create such measures “could ultimately lead to a failure to make improvements in hospitals where quality is judged to be better than it is,” he says.
Pronovost maintains that despite the substantial, persistent shortcomings in the quality of care that causes needless patient harm and increases health care costs, fixes can’t be put in place until rigorous scientific data show exactly where systems are broken, and until hard comparative evidence points to what types of repairs work best.
In the absence of such safety and efficacy science, he says, there will remain little consensus among hospitals and physicians about the best methods to judge quality or improvement. He points to overall hospital death rates as an example of an imperfect reflection of quality of care that in many cases is the only measure used.
Pronovost notes that physicians typically support the use of outcome measures if they are valid and reliable enough to enable conclusions to be drawn about the quality of care. Unfortunately, too often they aren’t.
For example, he says, some states penalize institutions for what they deem are preventable complications contracted by patients during their hospital stays, even though the hospitals don’t know exactly what they are being judged on because those states use a proprietary algorithm (commonly referred to as a “black box”) created by a private company to determine which hospitals are “successful” and which ones should be sanctioned. Clinicians and the public end up not knowing how accurate the measures are or how they were calculated.
Source: The Johns Hopkins University Gazette
You can read the abstract of the article in Health Affairs here.
