Choice and Explanation in Medical Management

This paper explores a model of choice and explanation in medical management and makes clear its advantages and limitations. The model is based on multiattribute decision making (MADM) and consists of four distinct strategies for choice and explanation, plus combinations of these four. Each strategy is a restricted form of the general MADM approach, and each makes restrictive assumptions about the nature of the domain. The advantage of tailoring a restricted form of a general technique to a particular domain is that such efforts may better capture the character of the domain and allow choice and explanation to be more naturally modelled. The uses of the strategies for both choice and explanation are illustrated with analyses of several existing medical management artificial intelligence (Al) systems, and also with examples from the management of primary breast cancer. Using the model it is possible to identify common underlying features of these Al systems, since each employs portions of this model in different ways. Thus the model enables better understanding and characterization of the seemingly ad hoc decision making of previous systems. Key words: artificial intelligence; expert systems; explanation; medical management. (Med Decis Making 7:22-31, 1987)

[1]  P. Miller,et al.  Critiquing Anesthetic Management: The “ATTENDING” Computer System , 1983, Anesthesiology.

[2]  K E Willard,et al.  Probabilistic Analysis of Decision Trees Using Monte Carlo Simulation , 1986, Medical decision making : an international journal of the Society for Medical Decision Making.

[3]  Sholom M. Weiss,et al.  A Precedence Scheme for Selection and Explanation of Therapies , 1981, IJCAI.

[4]  G. Gorry,et al.  Capturing clinical expertise. A computer program that considers clinical responses to digitalis. , 1978, The American journal of medicine.

[5]  P. Miller,et al.  A critiquing approach to expert computer advice--ATTENDING , 1984 .

[6]  R. L. Keeney,et al.  Decisions with Multiple Objectives: Preferences and Value Trade-Offs , 1977, IEEE Transactions on Systems, Man, and Cybernetics.

[7]  William J. Clancey,et al.  Strategic Explanations for a Diagnostic Consultation System , 1983, Int. J. Man Mach. Stud..

[8]  Stanley Zionts,et al.  A special issue on multiple criteria decision making , 1988 .

[9]  William Clancey Details of the Revised Therapy Algorithm , 1984 .

[10]  J. Kastner Strategies for expert consultation in therapy planning (artificial intelligence) , 1983 .

[11]  Peter Szolovits,et al.  Categorical and Probabilistic Reasoning in Medical Diagnosis , 1990, Artif. Intell..

[12]  E. Shortliffe,et al.  An analysis of physician attitudes regarding computer-based clinical consultation systems. , 1981, Computers and biomedical research, an international journal.

[13]  William J. Clancey,et al.  Classification Problem Solving , 1984, AAAI.

[14]  Casimir A. Kulikowski,et al.  A Model-Based Method for Computer-Aided Medical Decision-Making , 1978, Artif. Intell..

[15]  B. McNeil,et al.  Probabilistic Sensitivity Analysis Using Monte Carlo Simulation , 1985, Medical decision making : an international journal of the Society for Medical Decision Making.

[16]  H. Silverman A DIGITALIS THERAPY ADVISOR , 1975 .

[17]  Ronald A. Howard,et al.  Decision analysis: Perspectives on inference, decision, and experimentation , 1970 .