Reasonable patient care under uncertainty.

This paper discusses how limited ability to predict illness and treatment response may affect the welfare achieved in patient care. The discussion covers both decentralized clinical decision making and care that adheres to clinical practice guidelines. I explain why predictive ability has been limited, calling attention to questionable methodological practices in the research that supports evidence-based medicine. I summarize research on identification whose objective is to yield credible prediction of patient outcomes. Recognizing that uncertainty will continue to afflict medical decision making, I apply basic decision theory to suggest reasonable decision criteria with well-understood welfare properties. Previous research on medical decision making has largely embraced Bayesian decision theory. I summarize research studying the minimax-regret criterion, which seeks uniformly near-optimal decisions.