I have ranted about pay for performance (P4P). I recommend two blog contributions by DrRich.
However, I take issue with the DrRich’s comparison between widgets and patients in his first blog.
“P4P also relies on the Axiom of Industry – that the standardization of any process both improves quality and reduces cost. As DrRich has described elsewhere, the Axiom of Industry does not hold when the process involves actual human patients. This is because patients are not widgets. (While everyone agrees that patients are not widgets, the implication of this fact seems to have escaped many: What happens to the individual widget on an assembly line is immaterial – discarding even a high percentage of proto-widgets may be fine – as long as the ones that come out the other end are of sufficiently high quality as to yield the optimal price point in the market. Patients not being widgets, in theory we are supposed to care about what happens to the individual patient during the process.) Nonetheless, invoking the Axiom of Industry – equating reduced cost to improved quality – allows the central authorities to choose “quality measures” in their P4P efforts that will primarily reduce cost, and then to claim that their primary concern is for quality.”
There are several problems with this comparison. In a diagnostic process for patients, one would not throw out patients as implied by DrRich. One throws out (tentative) diagnoses that no longer meet evidence as it is collected. That is, one is dealing with the process of diagnosis (or the process of producing widgets). So this could mean that P4P would force one to accept an incorrect diagnosis which would harm a patient.
But the main issue is it is not whether one is dealing with patients or widgets but the state of knowledge one has (for either process). When the state of knowledge is high, then standardization* is appropriate. In DrRich’s site, a comment by bev M.D. reminds us that standardization works well for the process of transfusing blood. When the state of knowledge is not high enough, standardization does not work as well and other methods are needed and used. In reliability engineering, when the state of knowledge is insufficient, FMEA (Failure Mode Effects Analysis – a modeling method), is unable to predict all of the ways a process can fail and design errors will occur. Standardizing such a process would lock in design errors. Therefore FRACAS (Failure Reporting And Corrective Action System) is used, which is a “data-driven process improvement”, which corrects observed failures so they will not recur. These reliability engineering concepts are being applied to medicine and particularly medical errors.
*P4P could be viewed as a measure of compliance to standardization.