1 Bridging Terminology and Classification Gaps among Patient Safety Information Systems Andrew Chang, JD, MPH, Laurie Griesinger, MPH, Peter Pronovost,

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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

A Centralized Patient Safety Information System?

3 Background 1. Uniform formats and data standards for reporting adverse events and near-misses 2. Data standards applicable to the coding and classification of patient safety information 3. Data standards that are understandable to all 4. Data standards to enable interoperability within and across health care organizations (2003 IOM Patient Safety: Achieving a New Standard for Care)

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

Challenge #2: Discordant Nomenclature

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

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

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

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

Methods 1. Classification nodes of the PSET were mapped to the fields in the ICUsrs 2. The degree of match was assessed using a 5-point Likert Scale (match, synonymous, related, extrapolated, no match) 3. Overall similarity of the schemas was found by averaging the scores of the secondary classifications under each primary classification

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

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

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

Results The average Likert Scale ranking of secondary, tertiary and quaternary nodes by PSET primary classification 5 Match 4 Synonymous 3 Related 2 Extrapolated 1 No match

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

Map to a Standardized Taxonomy

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.