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[The use of the microcomputer in selecting the basic cause of death]
1Universidade de São Paulo, Faculdade de Saúde Pública, Departamento de Epidemiologia, Brasil.
Summary
The Underlying Cause Selection System (SCB) improves mortality data quality in Brazil by using artificial intelligence to select the underlying cause of death. This microcomputer-based system addresses limitations of previous mainframe systems.
Area of Science:
- Public Health
- Medical Informatics
- Artificial Intelligence
Context:
- Manual selection of underlying cause of death presents challenges.
- Existing computerized systems like ACME have limitations, including mainframe dependency.
- There is a growing need for comprehensive mortality data, including associated causes.
Purpose:
- To standardize and enhance the quality of mortality data across Brazil.
- To develop a microcomputer-based system for selecting the underlying cause of death.
- To overcome the operational limitations of previous mainframe systems.
Summary:
- The Underlying Cause Selection System (SCB) is an expert system developed in 1993.
- It utilizes artificial intelligence to replicate the logic of human coders for cause of death selection, adhering to ICD-9 guidelines.
- The SCB is user-friendly, requires minimal disk space, and runs on standard PCs, also storing data on associated conditions.
Impact:
- Facilitates improved accuracy and consistency in national mortality statistics.
- Enables wider adoption of computerized cause of death selection due to its microcomputer-based architecture.
- Supports better public health surveillance and policy-making through enhanced data quality.