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Validating the Patient Safety Indicators in the Veterans Health Administration

Do They Accurately Identify True Safety Events

Bibliographic Data

ID9105113
AuthorsAmy K Rosen (0000-0002-7539-7749, University School, corresponding author), Kamal M F Itani (Harvard University), Marisa Cevasco (Brigham and Women's Hospital), Haytham M A Kaafarani (0000-0002-4682-9135, Tufts Medical Center, corresponding author), Amresh Hanchate (0000-0002-7038-4463, University School, corresponding author), Marlena H Shin (0000-0001-5555-6258, VA Boston Healthcare System, corresponding author), Marlena Shin, Michael Shwartz (0000-0003-4840-1682, Boston University, corresponding author), Susan Loveland (VA Boston Healthcare System, corresponding author), Qi Chen (0000-0002-2835-5394, Boston University, corresponding author), Ann M Borzecki (0000-0003-1894-1274, University School), Ann Borzecki
Year2012
Volume50
Issue1
Pages74-85
Publication date2012-01-01
Peer ReviewedYes
Open AccessNo
TypeARTICLE
VenueMedical Care (JOURNAL)
Journal identifiersISSN: 0025-7079 • E-ISSN: 1537-1948
PublisherOvid Technologies (Wolters Kluwer Health) (PUBLISHER)
DOI10.1097/mlr.0b013e3182293edf
PMID21993057
OpenAlexW2024862564
LanguageEN
Citations received3
References cited21

BACKGROUND: The Agency for Healthcare Research and Quality (AHRQ) Patient Safety Indicators (PSIs) use administrative data to detect potentially preventable in-hospital adverse events. However, few studies have determined how accurately the PSIs identify true safety events. OBJECTIVES: We examined the criterion validity, specifically the positive predictive value (PPV), of 12 selected PSIs using clinical data abstracted from the Veterans Health Administration (VA) electronic medical record as the gold standard. METHODS: We identified PSI-flagged cases from 28 representative hospitals by applying the AHRQ PSI software (v.3.1a) to VA fiscal year 2003 to 2007 administrative data. Trained nurse-abstractors used standardized abstraction tools to review a random sample of flagged medical records (112 records per PSI) for the presence of true adverse events. Interrater reliability was assessed. We evaluated PPVs and associated 95% confidence intervals of each PSI and examined false positive (FP) cases to determine why they were incorrectly flagged and gain insight into how each PSI might be improved. RESULTS: PPVs ranged from 28% (95% CI, 15%-43%) for Postoperative Hip Fracture to 87% (95% CI, 79%-92%) for Postoperative Wound Dehiscence. Common reasons for FPs included conditions that were present on admission (POA), coding errors, and lack of coding specificity. PSIs with the lowest PPVs had the highest proportion of FPs owing to POA. CONCLUSIONS: Overall, PPVs were moderate for most of the PSIs. Implementing POA codes and using more specific ICD-9-CM codes would improve their validity. Our results suggest that additional coding improvements are needed before the PSIs evaluated herein are used for hospital reporting or pay for performance

Adverse effect · Coding (social sciences) · Confidence interval · Health care · Inter-rater reliability · Medical record · Patient safety · Emergency Medicine · Internal Medicine · Medical Coding and Health Information · Medicine · Patient Safety and Medication Errors · Psychology · Sepsis Diagnosis and Treatment

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Unique citing works3
Citations per year0,23
Citation span2013 - 2016 (4)
Citation velocityhistorical
Highly citedNo
Citation typesNeutral: 1

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