Medical informatics and clinical decision making: the science and the pragmatics.
There are important scientific and pragmatic synergies between the medical decision making field and the emerging discipline of medical informatics. In the 1970s, the field of medicine forced clinically oriented artificial intelligence (AI) researchers to develop ways to manage explicit statements of uncertainty in expert systems. Classic probability theory was considered and discussed, but it tended to be abandoned because of complexities that limited its use. In medical AI systems, uncertainty was handled by a variety of ad hoc models that simulated probabilistic considerations. To illustrate the scientific interactions between the fields, the author describes recent work in his laboratory that has attempted to show that formal normative models based on probability and decision theory can be practically melded with AI methods to deliver effective advisory tools. In addition, the practical needs of decision makers and health policy planners are increasingly necessitating collaborative efforts to develop a computing and communications infrastructure for the decision making and informatics communities. This point is illustrated with an example drawn from outcomes management research.
Shortliffe
E H
EH
Section of Medical Informatics, Stanford University School of Medicine, CA 94305-5479.
D001185:Artificial Intelligence; D003198:Computer Simulation; D016208:Databases, Factual; D003658:Decision Making, Computer-Assisted; D003661:Decision Support Techniques; D003936:Diagnosis, Computer-Assisted; D003937:Diagnosis, Differential; D005103:Expert Systems; D006801:Humans; D008491:Medical Informatics Applications; D008498:Medical Record Linkage; D016347:Medical Records Systems, Computerized; D015201:Meta-Analysis as Topic; D015233:Models, Statistical; D017063:Outcome Assessment, Health Care; D010934:Planning Techniques; D011336:Probability