I recently spoke to a quality measures development organization and it got me thinking — what makes a good doctor, and how do we measure it?
In thinking about this, I reflected on how far we have come on quality measurement. A decade or so ago, many physicians didn’t think the quality of their care could be measured and any attempt to do so was “bean counting” folly at best or destructive and dangerous at worse. Yet, in the last decade, we have seen a sea change.
We have developed hundreds of quality measures and physicians are grumblingly accepting that quality measurement is here to stay. But the unease with quality measurement has not gone away and here’s why. If you ask “quality experts” what good care looks like for a patient with diabetes, they might apply the following criteria: good hemoglobin A1C control, regular checking of cholesterol, effective LDL control, smoking cessation counseling, and use of an ACE Inhibitor or ARB in subsets of patients with diabetes.
Yet, when I think about great clinicians that I know – do I ask myself who achieves the best hemoglobin A1C control? No. Those measures – all evidence-based, all closely tied to better patient outcomes –don’t really feel like they measure the quality of the physician.
So where’s the disconnect? What does make a good doctor? Unsure, I asked Twitter:
Over 200 answers came rolling in.
There is a plethora of health care quality data being pushed out to the public, yet no rules to assure the accuracy of what is being presented publicly. The health care industry lacks standards for how valid a quality measure should be before it is used in public reporting or pay-for-performance initiatives, although some standards have been proposed.
The NQF does a good job of reviewing and approving proposed measures presented to it, but lacks the authority to establish definitive quantitative standards that would apply broadly to purveyors of performance measures. However, as discussed earlier, many information brokers publically report provider performance without transparency and without meeting basic validity standards. Indeed, even CMS, which helps support NQF financially, has adopted measures for the Physician Quality Reporting System that have not undergone NQF review and approval. Congress now is considering “SGR repeal,” or sustainable growth rate legislation, that would have CMS work directly with specialty societies to develop measures and measurement standards, presumably without requiring NQF review and approval .
Without industry standards, payers, policy makers, and providers often become embroiled in a tug-of-war; with payers and policy-makers asserting that existing measures are good enough, and providers arguing they are not. Most often, neither side has data on how good the contested measures actually are. Most importantly, the public lacks valid information about quality, especially outcomes, and costs.
Indeed, most quality measurement efforts struggle to find measures that are scientifically sound yet feasible to implement with the limited resources available. Unfortunately, too often feasibility trumps sound science. In the absence of valid measures, bias in estimating the quality of care provided will likely increase in proportion to the risks and rewards associated with performance. The result is that the focus of health care organizations may change from improving care to “looking good” to attract business. Further, conscientious efforts to reduce measurement burden have significantly compromised the validity of many quality measures, making some nearly meaningless, or even misleading. Unfortunately, measurement bias often remains invisible because of limited reporting of data collection methods that produce the published results. In short, the measurement of quality in health care is neither standardized nor consistently accurate and reliable.