Development and Testing of Tools to Detect Ambulatory Surgical Adverse Events

• DOI: 10.1097/pts.0b013e31827d1a88
• Publication Date: 2013-01-31T13:20:22Z
• Authors: Hillary J. Mull; Ann M. Borzecki; Kathleen Hickson; Kamal M.F. Itani; Amy K. Rosen
• Keywords: Time Factors; Reproducibility of Results; United States; 3. Good health; United States Department of Veterans Affairs; 03 medical and health sciences; Postoperative Complications; 0302 clinical medicine; Ambulatory Surgical Procedures; Risk Factors; Data Mining; Electronic Health Records; Humans; Patient Safety; Algorithms; Quality Indicators, Health Care

Numerous health-care systems in the United States, including Veterans Health Administration (VA), use National Surgical Quality Improvement Program (NSQIP) to detect surgical adverse events (AEs). VASQIP sampling methodology excludes many routine ambulatory surgeries from review. Triggers, algorithms derived clinical logic flag cases where AEs have most likely occurred, could complement by detecting a higher yield of with true AE.We developed and tested set AE trigger using sample fiscal year 2008 VA Boston Healthcare System. We used VASQIP-assessed refine triggers VASQIP-excluded test how trigger-flagged had nurse chart review-detected AE. Chart review was performed electronic medical record. calculated ratio over flagged (i.e., positive predictive value [PPV]), 95% confidence interval for each trigger.Compared rate (9 AEs, or 2.8%, 322 charts assessed), 198 yielded more at least 1 (47 an AE, 6.0%, 782 surgeries). Individual PPVs ranged 12.4% 58.3%.In comparison VASQIP, our identified fewer chart-reviewed cases. Because results are based on relatively small sample, further research is necessary confirm these findings.