Experimenting with incentives for quality is a risky task. The variable requires a precise measure and it must indicate the appropriate signal to the provider to have impact in decisions and behaviour. Usually, rational behaviour is assumed int the models. A recent review highlights this is issue:
Advocates of pay-for-performance in health care maintain that its early failures are the result of inadequate design, a failure to incorporate a more sophisticated understanding of provider motivation into program design (26). On the basis of evidence from early schemes and readings of economic and psychological theory, several researchers have produced blueprints for secondgeneration pay-for-performance frameworks. Their recommendations for designers include making rewards large enough to be meaningful; using penalties in addition to rewards; aligning incentives to professional priorities; using absolute rather than relative performance targets; providing frequent, discrete rewards or punishments; and making an explicit long-term commitment to incentivesBut the authors admit that: " Some of these solutions are difficult to implement, are contradictory, or introduce further unintended consequences". And this paves the way to a pessimist view:
Programs are slowly becoming more sophisticated, but unless clear evidence for cost-effectiveness emerges soon, the incentive experiment may have to be abandoned. Many commentators see this abandonment as inevitable, believing incentive programs to be fundamentally flawed. Some concerns are technical in nature and relate to the difficulty of accurately defining and measuring the most important aspects of quality with the greatest impacts on patient outcomesMy impression is that the unit of analysis is usually wrong. Until we are not able to measure patient focused episodes of care properly, in a holistic way, will miss something. This should be the first concern. Of course, this is an overwhelming task, not an easy one.
Camille Pissarro in Sant Feliu de Guixols right now
