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Chir F2 F Mrsa 2011 10 18

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Consortium for Healthcare Informatics Research Steering Committee. Update on MRSA Applied Project 10.18.2011

Consortium for Healthcare Informatics Research Steering Committee. Update on MRSA Applied Project 10.18.2011


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  • This slide can be used as a template for CHIR F2F Presentations at the October 2011 F2F Meeting. It also outlines guidelines created by the CHIR Salt Lake City group for each presenter to consider including so members and/or guests can gain a sense of each project’s relevance/status.
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    • 1. CHIR MRSA Project: Clinical & Operational Significance  Healthcare-associated infections (HAIs) leading cause of preventable death.  VA Pittsburgh Reduced MRSA Significantly!  VHA National MRSA Reduction Initiative Effective!*  HAI Surveillance Highly Time Intensive  Staff need to Focus on Problems, Intervene Early  Need for Automated Surveillance Tools  Interdisciplinary, multisite collaborative extracting structured and unstructured data from EHR *Jain et al, NEJM 2011Indianapolis, IN; Salt Lake City, UT; Palo Alto, CA; West Haven, CT; Tampa, FL
    • 2. CHIR-MRSA Project Overview
    • 3. Example: Urinary Tract Infection Combined Information
    • 4. Annotation Goals & Progress• Key defining what is needed from TIU’s and where to get it for machine learning.• Used to create guidelines and interact (2-way) with ontologies. – UTI guidelines finalized (465 documents annotated).  UTI, urinary cath devices, & temp and fever – Guidelines for general machine learning written.  ~anything infection related to inform a machine learning approach and benefit ontology. – Guidelines for detecting CVADs (pilot).  ID when cath is present, when inserted or removed
    • 5. Example: Electronic Capture Medical Device Use *A problem confounding infection surveillance1. Identify possible methods for capturing medical device use data for acute care patients (focus groups)2. Identify the pros and cons associated with specific methods to measure medical device use (focus groups)3. Develop a prototype system to capture medical device use data for acute care patients in the VA Enhanced Metafile Record (EMR)Partnership with OI&T Innovation - West Haven-Martinello, Brandt, et al
    • 6. MRSA NLP Progress• Developed YTEX – a powerful combination NLP pipeline & database. -Integrated into VINCI MRSA database.• Analyzed 30,000 notes of MRSA cases, locally and on VINCI.• Developed lists of 2000 clinical abbreviations and 4000 concepts (manual chart review) specifying infections.• Developed patient-centered NLP approach to analyze notes in temporal window related to + MRSA culture in 2 use cases: UTI and bloodstream infections.• Prior infections in 90% of patients.• Sentences and document fragments with relevant terms retrieved and highlighted.
    • 7. MRSA NLP Findings and Ongoing Work• NLP successfully captures relevant clinical info. related to MRSA infection from heterogeneous clinical notes.• False positives a major problem. -Some rejected with improved NLP; -Others presented to experts for judgmentOngoing Work to Improve NLP accuracy• Incorporation of clinical rules into NLP process• Integration of Ontology with NLP• Improvement of temporality, section detection, template detection, abbreviations and negation (*key focus of collaboration with Information Extraction Methods group)
    • 8. Vision of Surveillance Tool1. To rapidly design a user-centered tool to capture MRSA UTIs by fall of 20122. User-centered tool for IP/ ID/ Epi experts to: 1. Display data, results, and outcomes that 2. Support key decisions & optimal workflows, and 3. Enable appropriate next steps (or actions)3. Incorporate Black Box surveillance as appropriate4. Demonstrate feasibility of and need for full feature HAI Dashboard System beyond 2012
    • 9. Workflow Capture & Analysis To Support Rapid, User-Centered Design Engage Leadership: Refine Design through: - National, Regional, and Local- Clinical and Research - Identify Goals, Metrics, etc. Analysis: Observations: - Contextual Inquiry - Grounded Theory - Follow-A-Thread - Artifact Analysis - Think-Aloud Interviews: - IP’s, Epi, ID Physicians - Identify & Validate Activities - Vision for Tool & Workflow Inform, Electronic Data: Validate Refine,Iterate - VINCI Data as available - Machine Learning and NLP Rapid Ethnography: Iterate & Models - Environmental Walkthrough Validate - Shadow Key Personnel Refine - Artifact Collection & IterateIterate Surveys: - Needs Assessment & Representations: Validation (as needed) - Workflows & Process Maps - Information & Screen Flows Key Deliverables: - Design Narratives - Interactive Prototypes