Enabling Medical Experts to navigate clinical text for cohort identification (meTAKES) Stephen Wu, Mayo Clinic SHARPn Summit 2012 June 12, 2012.

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Presentation transcript:

Enabling Medical Experts to navigate clinical text for cohort identification (meTAKES) Stephen Wu, Mayo Clinic SHARPn Summit 2012 June 12, 2012

Outline Motivation Methods (current) System architecture Data retrieval Search Cohort management Conclusion & Future Work

Motivation Clinical NLP out-of-the-box Comprehensive knowledge Customize? Collaborate! Diverse requirements Physician/Researcher tasks Enroll patients in study Define retrospective cohort Case abstraction Somali patients (unique terms) Drug-induced liver injury (rel’ns) Pediatric asthma (temporal) Somali patients (unique terms) Drug-induced liver injury (rel’ns) Pediatric asthma (temporal)

“Medical expert”-driven NLP Use case-specific Streamlined On-the-fly NLP  Diverse requirements Interactive interface Delivery mechanism Available data vs. expert knowledge Use case-agnostic Comprehensive Pre-computed NLP  Known requirements textsemanticsexpert criteriasource

ClientServer Web interface (GWT) GUI Lucene ranked records EHR data pool parameters records NLP (MedTagger) query parser query cohort manipulation records cohort mgmt

Data retrieval Parameters (current) Patient ID Date Sources (current) Enterprise Data Trust Mayo Clinic Text files on server

Search Parameters (current) Term lists Logic Expansion Techniques (current) Dictionary (Lucene) NLP results (e.g., negation)

Cohort Management Parameters: Cohort name/tag Selecting patients Export Iterative refinement

Conclusion and Future Work NLP / search Text characteristics Semantic search Relationships HCI / cohort management Learning Collaboration Interoperability Structured data API Mayo delivery: DDQB Clinical Notes Search Tool Evaluation framework

THANK YOU. meTAKES team: Stephen Wu Ravikumar K.E. Hongfang Liu Special thanks to: Siddhartha Jonnalagadda James Masanz Vinod Kaggal Sean Murphy Tom Suther Erik Voldal Carlos Garcia Melissa Gregg This work was supported in part by the SHARPn (Strategic Health IT Advanced Research Projects) Area 4: Secondary Use of EHR Data Cooperative Agreement from the HHS Office of the National Coordinator, Washington, DC. DHHS 90TR