Performance of four computer-based diagnostic systems

Abstract

Background: Computer-based diagnostic systems are available commercially, but there has been limited evaluation of their performance. We assessed the diagnostic capabilities of four internal medicine diagnostic systems: Dxplain, Iliad, Meditel, and QMR.

Methods: Ten expert clinicians created a set of 105 diagnostically challenging clinical case summaries involving actual patients. Clinical data were entered into each program with the vocabulary provided by the program's developer. Each of the systems produced a ranked list of possible diagnoses for each patient, as did the group of experts. We calculated scores on several performance measures for each computer program.

Results: No single computer program scored better than the others on all performance measures. Among all cases and all programs, the proportion of correct diagnoses ranged from 0.52 to 0.71, and the mean proportion of relevant diagnoses ranged from 0.19 to 0.37. On average, less than half the diagnoses on the experts' original list of reasonable diagnoses were suggested by any of the programs. However, each program suggested an average of approximately two additional diagnoses per case that the experts found relevant but had not originally considered.

Conclusions: The results provide a profile of the strengths and limitations of these computer programs. The programs should be used by physicians who can identify and use the relevant information and ignore the irrelevant information that can be produced.