CHIR MRSA Project:Clinical & Operational

Significance

Indianapolis, IN; Salt Lake City, UT; Palo Alto, CA; West Haven, CT; Tampa, FL

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 2011

CHIR-MRSA Project Overview

Example: Urinary Tract Infection

Combined Information

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

Example: Electronic Capture Medical Device Use

1. 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

*A problem confounding infection surveillance

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.

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 judgment

Ongoing 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)

Vision of Surveillance Tool

1. To rapidly design a user-centered tool to capture MRSA UTIs by fall of 2012

2. User-centered tool for IP/ ID/ Epi experts to:1. Display data, results, and outcomes that2. Support key decisions & optimal workflows, and3. 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

Workflow Capture & AnalysisTo Support Rapid, User-Centered Design

Engage Leadership:- National, Regional, and

Local- Clinical and Research- Identify Goals, Metrics, etc.

Interviews:- IP’s, Epi, ID Physicians- Identify & Validate Activities- Vision for Tool & Workflow

Iterate

Representations:- Workflows & Process Maps- Information & Screen Flows

Surveys:- Needs Assessment &

Validation (as needed)

Validate

Refine& Iterate

Rapid Ethnography:- Environmental Walkthrough

- Shadow Key Personnel- Artifact Collection

Observations:- Contextual Inquiry- Artifact Analysis- Think-Aloud

Electronic Data:- VINCI Data as available- Machine Learning and NLP

Models

Iterate

Inform, Refine,

Iterate &Validate

Key Deliverables:- Design Narratives- Interactive Prototypes

Refine Design through:

Analysis:- Grounded Theory- Follow-A-Thread