A Country Doctor Reads: So Much for this Basic Quality Metric?
Another cornerstone in evaluating physician performance now in question.
One of the most basic quality indicators in medicine has been whether patients with a history of myocardial infarction are prescribed a beta blocker, like metoprolol. This month, the New England Journal of Medicine says this doesn’t seem to make any difference. So, will the guidelines and quality scoring change and, if so, how long will that take?
Routine Beta-Blockers in Secondary Prevention — On Injured Reserve | New England Journal of Medicine
The benefit of beta-blockers after myocardial infarction was established before the advent of reperfusion and percutaneous coronary intervention and the availability of effective secondary preventive medications. Since these other treatments became accessible, the value of beta-blocker therapy in patients with coronary artery disease or myocardial infarction but without heart failure has been challenged. Observational studies have yielded conflicting results, and so far, only one small, open-label, randomized trial has been conducted, which showed no difference in clinical outcomes after 3 years.
Yndigegn et al. now present in the Journal the results of the REDUCE-AMI trial (Randomized Evaluation of Decreased Usage of Beta-Blockers after Acute Myocardial Infarction) — a registry-nested, open-label, randomized trial. The investigators compared oral beta-1 receptor–selective blockers with no beta-blocker therapy in patients with myocardial infarction, a preserved left ventricular ejection fraction, and obstructive coronary artery disease. A total of 5020 patients were enrolled in the trial at a median of 2 days after hospital admission. The median doses that were received were 100 mg for metoprolol and 5 mg for bisoprolol. After 3.5 years of follow-up, death from any cause or new myocardial infarction (the composite primary end point) occurred in 7.9% of the patients assigned to the beta-blocker group and in 8.3% of those assigned to the no–beta-blocker group (hazard ratio, 0.96; 95% confidence interval, 0.79 to 1.16; P=0.64). In addition, beta-blocker treatment was not associated with an apparently lower cumulative incidence of secondary efficacy end-point events or of symptoms.
https://www.nejm.org/doi/full/10.1056/NEJMe2402731
This reminds me of a piece I wrote in 2009:
Quality or Conformity?
Yesterday I received something in the mail about how I might be judged by certain “Quality Indicators”, such as my patients’ mammography rate. This struck me as very odd, since just a few weeks ago the U.S. Public Health Service Taskforce reversed their longstanding recommendation that all women should have annual mammograms from age 40.
This is a striking example of how yesterday’s truths are tomorrow’s fallacies in modern medicine. A doctor who orders annual mammograms this month could be viewed as practicing poor quality medicine, even though the same behavior might have earned him or her bonus payments and honorable mentions last month.
I think it is time we speak honestly about what the agenda really is here. If we, or those who pay us or regulate us, choose quality indicators that are not based on solid scientific principles, but instead on expert opinions that could – and do – change at any moment, we are not measuring quality at all. What we are measuring and rewarding in that case is conformity. How fast and how consistently today’s physicians can implement new guidelines is certainly easier to measure than how well their patients are feeling.
We aren’t measuring how often doctors make the correct diagnosis on the first visit or how well they handle difficult clinical situations. We aren’t measuring how often we are able to reassure or comfort another human being who would otherwise keep circling within the health care system at great expense in search of peace of mind.
No, the things we measure are only the underpinnings of quality in health care. It is fine to measure doctors’ compliance with official guidelines, but we need to look well beyond such low hanging fruit if we want to be serious about quality.
Frankly, there are ways we can let our office staff, our disease registries or Electronic Medical Records handle a lot of the housekeeping items people think of as quality indicators. The quality measures of physicians’ work would then reflect how we practice the art and science of medicine. We need to look more to clinical results (outcomes) and appropriateness of care.
Just like in school, we can strive to master the subject or just pass the test. If we just want to pass the test, we can change the subject when our patients bare their souls to us, fumble with the chart or peer into the EMR and start talking about tetanus shots and cholesterol and mammograms (or perhaps why we won’t order a mammogram), or we can push the paper chart or computer screen aside, look them straight in the eyes and say:
“We’ll let the system catch up with you about those things. Tell me what’s bothering you…”
The general public expects that "better healthcare quality" means better outcomes. Most doctors want their quality metrics to be outcome measures. The quality metrics that CMS uses most are process measures. Can you check off the box? Did you order this or that intervention for the correct population? Did you get everyone their vaccines? Did you follow the protocol? If you did the things, you get lots of quality badges from NCQA and their HEDIS audits. And you guessed it, "the things" you are checking off usually means more $$ for their buddies in the industry. When a provider or a healthcare entitiy like a hospital has higher quality scores, that doesn't necessarily mean that their quality of care is better. It means they adhere to published protocols well, and they probably are paid better than those who do not have the fancy badges. Higher quality scores mean higher reimbursment from CMS and some insurance plans.
All the data collected about this or that quality metric has nothing to do with a physician treating patients effectively and well and everything to do with gathering useless data for the AI nerds to create nice reports to try to show big business medicine, big pharma, and the governemt are doing something useful to improve healthcare. Toss the PR data and go back to letting doctors be doctors. Patients recognize the difference between quality metrics and the care they receive from a good patient/physician relationship.