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Computerized diagnosis: implications for clinical education
1Evans Memorial Department of Clinical Research, Boston, Massachusetts.
Medical Education
|January 1, 1988
Summary
Small computers are transforming healthcare, enabling practical diagnostic programs and expert systems. Clinician data quality and diagnostic skills are crucial for the success of computerized medical diagnosis.
Area of Science:
- Medical Informatics
- Clinical Decision Support
Background:
- Small computers are becoming essential clinical tools, impacting medical practice and training.
- Probability theory has driven the creation of diagnostic programs for small computers.
- Expert systems, acting as 'electronic consultants,' are now available for various clinical scenarios.
Purpose of the Study:
- To review the current state and future prospects of expert systems in medicine.
- To assess the suitability of different computer programs for clinical environments.
- To highlight the importance of clinician input and diagnostic skills for computerized diagnosis.
Main Methods:
- Review of existing literature on expert systems in medicine (e.g., INTERNIST/CADUCEUS, MYCIN).
- Analysis of the role of probability theory in developing diagnostic programs.
- Evaluation of less complex programs, including clinical prediction rules and expert system shells.
Main Results:
- Expert systems like INTERNIST/CADUCEUS and MYCIN offer valuable insights into medical diagnosis.
- Simpler programs and expert system shells are well-suited for clinical settings.
- The effectiveness of computerized diagnosis hinges on the quality of clinician-provided data.
Conclusions:
- Computerized medical diagnosis, aided by expert systems, holds significant promise.
- Enhanced understanding of data-gathering strategies is necessary for effective bedside diagnosis.
- Emphasis on fundamental diagnostic skills in clinical training is vital for leveraging diagnostic computer programs.
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