(Hat-tip to Modern Healthcare for spotting this one). While there was lots of fuss about the IHI 1OOK lives campaign recently and whether it did or didn’t meet its target—and the NY Times gave it a pat on the back this morning in the Editorial section—there’s perhaps even more important news from a study published in JAMA today. A large multi-center team looked at the Medicare data for performance measures on post-heart attack patients with regard to how improved processes related to outcomes. These measures are the bedrock of the “we know what to do, but we don’t know how to do it” meme of IHI and the quality movement. In other words, the theory is that if we just did it all as well as the literature says we should, then there is potential for vast improvement. Unfortunately the outcomes are sobering for those of us who believe that if you apply relatively simple industrial processes to medicine it can markedly improve outcomes (and lower costs too).
We found moderately strong correlations (correlation coefficients
0.40; P values <.001) for all pairwise comparisons between
-blocker use at admission and discharge, aspirin use at admission and discharge, and angiotensin-converting enzyme inhibitor use, and weaker, but statistically significant, correlations between these medication measures and smoking cessation counseling and time to reperfusion therapy measures (correlation coefficients <0.40; P values <.001). Some process measures were significantly correlated with risk-standardized, 30-day mortality rates (P values <.001) but together explained only 6.0% of hospital-level variation in risk-standardized, 30-day mortality rates for patients with AMI.
In other words, even when the hospitals did well on the performance measures, it only explained a small fraction of the overall variation in outcomes. So there are to my mind only two possible conclusions. Either performance measurements and controlling process variation don’t matter too much, or we actually—in this case at least—don’t know what works. Neither one is a particularly satisfying explanation.
				
0.40; P values <.001) for all pairwise comparisons between 
-blocker use at admission and discharge, aspirin use at admission and discharge, and angiotensin-converting enzyme inhibitor use, and weaker, but statistically significant, correlations between these medication measures and smoking cessation counseling and time to reperfusion therapy measures (correlation coefficients <0.40; P values <.001). Some process measures were significantly correlated with risk-standardized, 30-day mortality rates (P values <.001) but together explained only 6.0% of hospital-level variation in risk-standardized, 30-day mortality rates for patients with AMI.