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Bridging Terminology and Classification Gaps among Patient Safety Information Systems

Bridging Terminology and Classification Gaps among Patient Safety Information Systems. Andrew Chang, JD, MPH, Laurie Griesinger, MPH, Peter Pronovost, MD, PhD, Jerod Loeb, PhD. Joint Commission on Accreditation of Healthcare Organizations. A Centralized Patient Safety Information System?.

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Bridging Terminology and Classification Gaps among Patient Safety Information Systems

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  1. Bridging Terminology and Classification Gaps among Patient Safety Information Systems Andrew Chang, JD, MPH, Laurie Griesinger, MPH, Peter Pronovost, MD, PhD, Jerod Loeb, PhD Joint Commission on Accreditation of Healthcare Organizations

  2. A Centralized Patient Safety Information System?

  3. Background Uniform formats and data standards for reporting adverse events and near-misses Data standards applicable to the coding and classification of patient safety information Data standards that are understandable to all Data standards to enable interoperability within and across health care organizations (2003 IOM Patient Safety: Achieving a New Standard for Care)

  4. Challenge #1: Discordant Terminology • Adverse event/outcome • Unintended consequence • Unplanned clinical occurrence • Therapeutic misadventure • Peri-therapeutic accident • Iatrogenic complication/ injury • Hospital-acquired complication • Near miss • Close call • Incident • Medical mishap • Unexpected occurrence • Untoward incident • Bad call • Sentinel event • Failure • Mistake • Lapse • Slip

  5. Challenge #2: Discordant Nomenclature

  6. Challenge #3: Discordant Classification Severity of Harm (e.g., JCAHO Sentinel Events Type of health Reporting, care service NCC MERP) provided (e.g., Einthoven Classification) Overuse, Underuse, Misuse (Chassin, 1998) Active & Latent Failures (Reason, 1990) Legal definition Type of setting (e.g., errors Type of individual (e.g., hospital, resulting from involved (e.g., home health) negligence) physician , nurse, patient Interventions (e.g., JCAHO National Patient Safety Goals I. Impact II. Type III. Domain IV. Cause V. Prevention & Mitigation

  7. Methods • Comparison of two independent patient safety terminology, nomenclature, and classification schemas • Patient Safety Event Taxonomy (PSET) • Intensive Care Unit Safety Reporting System (ICUsrs)

  8. Patient Safety Event Taxonomy (PSET) • Alpha version developed by JCAHO in January 2002, refinement is ongoing • High-level taxonomy • Mapping and Classification Schema (“back-end”) • 5 primary classifications: • Impact; Type; Domain; Cause; Prevention & Mitigation • Under the 5 primary classifications, there are: • 16 secondary classifications • 60 tertiary classifications • 127 quaternary classifications • ICD-9, SNOMED, Narrative fields

  9. Intensive Care Unit Safety Reporting System (ICUsrs) • Developed by The Johns Hopkins University and funded by AHRQ starting in October, 2001 • Over 1900 events collected to date (“front-end”) • 31 ICUs in the U.S. participate • Web-based, confidential, non-punitive reporting tool that can be used by any hospital staff member • 114 coded and narrative fields

  10. Methods • Classification nodes of the PSET were mapped to the fields in the ICUsrs • The degree of match was assessed using a 5-point Likert Scale (match, synonymous, related, extrapolated, no match) • Overall similarity of the schemas was found by averaging the scores of the secondary classifications under each primary classification

  11. Methods Example: Classification of Causes • Cause (Primary) • Human Factors (Secondary) • Practitioner (Tertiary) • Skilled-based (Quaternary)

  12. Results Of the 75 coded fields in ICUsrs containing event-related data • 46 (61%) fields mapped to PSET • 29 (39%) fields unmapped

  13. Results Of the the most frequently coded fields that mapped to PSET (n=34), ICUsrs fields mapped with the following degree of similarity: • 4 (12%) match • 10 (29%) synonymous • 5 (15%) related • 4 (12%) extrapolated • 11 (32%) no match

  14. Results The average Likert Scale ranking of secondary, tertiary and quaternary nodes by PSET primary classification

  15. Results The average Likert Scale ranking by PSET primary classification 3 match 2 extrapolated 1 no match

  16. Map to a Standardized Taxonomy

  17. Conclusions • Results suggest that standardization of patient safety event data may not be as simple as presumed by the 2003 Institute of Medicine (IOM) report, Patient Safety: Achieving a New Standard of Care. • We believe that this overall approach of explicit linking of information via PSET provides a potentially powerful capability for common data exchange among non-common reporting systems.

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