GLINDA: Automated Reasoning for Application of Clinical Guidelines

1. GLINDA: Automated Reasoning for Application of Clinical Guidelines BMIR Research-in-Progress Presentation Csongor Nyulas Samson Tu

2. Acknowledgement • Funder: National Library of Medicine • Project Members • Mark Musen • Mary Goldstein • Susana Martins • Hyunggu Jung • Pamela Kum

3. Problem Statement • Populations are aging worldwide • Older adults tend to have multiple chronic conditions • Data?? • Management of multiple comorbidities presents a challenging problem • Almost all clinical practice guidelines focus on the management of single diseases • May take comorbidities into account • Simultaneous application of multiple guidelines leads to suboptimal care

4. Research Goals • Develop a modular and extensible platform for exploring informatics and clinical issues • Integrate and reuse best-of-breed knowledge resources and applications • Create methods for detecting, repairing and integrating treatment recommendations from multiple guideliens

5. Method • Adapt BioSTORM agent architecture • Task decomposition • Problem-solving method • Reuse ATHENA CDSS • Clinical domains: Hypertension, diabetes mellitus, heart failure, hyperlipidemia, chronic kidney disease • Develop new agents for detecting, repairing, and integrating treatment recommendations • Apply methods on anonymized patient cases from the Stanford STRIDE database

6. Outline of Method Section • STRIDE patient selection and preparation • BioSTORM agent architecture and its application to GLINDA • ATHENA DSS agents • New agents for detecting, repairing and integrating guideline recommendations • Presentation for review

7. STRIDE Patient Extraction

8. Test Patients Selection

9. Data Preparation

10. BioSTORM Agent Architecture

11. GLINDA Agent Configurations

12. ATHENA CDSS

13. Integrating Recommendations from Multiple Guidelines

14. Detecting Interactions

15. Current Status

16. Future Work