GLINDA: Automated Reasoning for Application of Clinical Guidelines BMIR Research-in-Progress PresentationCsongor NyulasSamson Tu

Acknowledgement

Funder: National Library of Medicine

Project MembersMark Musen

Mary Goldstein

Susana Martins

Hyunggu Jung

Pamela Kum

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

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

Method

Adapt BioSTORM agent architectureTask 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

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

STRIDE Patient Extraction

Test Patients Selection

Data Preparation

BioSTORM Agent Architecture

GLINDA Agent Configurations

ATHENA CDSS

Integrating Recommendations from

Multiple Guidelines

Detecting Interactions

Current Status

Future Work