Computer diagnosis in psychiatry: A bayes approach

Along with the recent work on standardizing definitions, interviews, and records in clinical psychiatry, there have been several attempts at designing computer models of the psychiatric diagnosis process (e.g., Spitzer’s DIAGNO and Wing’s CATEGO). Such models aid scientific evaluation of issues such as reliability and validity. Generally these models are judged upon how well they can replicate clinician’s diagnoses when presented with unknown clinical cases. This paper presents a model based on applied probability theory, Bayes method, which has been tested successfully in other medical fields, but has only been proposed without sufficient testing in psychiatry (because of inadequate samples). It describes the logic of Bayes method, details the samples used to develop and test the model, and compares the results of the model with the performance of DIAGNO (a well established, different type of computer model), and discusses the implications of this. Bayes method requires estimates of the relative frequencies of relevant symptoms in specified diseases (e.g., the relative incidence of disturbed reality testing in paranoid schizophrenia as compared with that in alcoholism). In this study estimates of these frequencies are derived from a sample of patients and nonpatients interviewed by New York psychiatrists using Spitzer’s Current and Past Psychopathology Scales (CAPPS). The formal mathematical procedure (Bayes method) which translates this information into predicted diagnoses is briefly described. The model is tested on a subset of this sample, and then on three completely separate samples: An inpatient group from Columbia and the Institute of Living, a group of women in a maternity clinic who were selected by a screening questionnaire for schizophrenia, and a mixed group of Italian inpatients and outpatients interviewed by Italian psychiatrists. The CAPPS records are processed by both Bayes method and DIAGNO, and the results compared. The agreement among clinician and computer varies between 40 and 70 per cent for Bayes method, and between 45 and 55 per cent for DIAGNO. The reasons for this difference are discussed. Finally a comparison of the advantages and disadvantages of the respective methods is presented.