Journal article
Use of Triggers to Detect Adverse Events After Outpatient Orthopedic Surgery at a Single Ambulatory Surgery Center
Orthopedics (Thorofare, N.J.), v 45(2), pp 116-121
01 Mar 2022
PMID: 35021026
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
Literature on adverse events (AEs) after outpatient orthopedic surgery is relatively sparse, and efforts to detect, measure, and track AEs after outpatient surgery lag behind those for the inpatient setting. Detection of AEs has traditionally relied on patient safety indicators (from billing data) and self-reporting, but these methods have been shown to have low sensitivity, missing up to 90% of AEs. There is growing recognition that the trigger method, which uses 'triggers" as red flags to initiate more detailed chart audits, can serve as a more sensitive alternative to detect AEs. Moreover, the recent widespread adoption of electronic health records (EHRs) can provide faster automated methods for identifying triggers and estimating AE rates. this study evaluates the ability of 6 separate EHR-based triggers to predict AEs after outpatient orthopedic surgery and compares this trigger method with AE self-reporting. Triggers have the potential to decrease postoperative morbidity after out- patient orthopedic surgery and may lead to quality improvement. Further research is needed to qualify triggers as screening tools in the outpatient setting.
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Details
- Title
- Use of Triggers to Detect Adverse Events After Outpatient Orthopedic Surgery at a Single Ambulatory Surgery Center
- Creators
- Daniel B. Calem - Thomas Jefferson UniversityDylan P. Horan - Thomas Jefferson UniversityMatthew T. Taylor - Thomas Jefferson UniversityRichard M. McEntee - Thomas Jefferson UniversityDavid Pedowitz - Thomas Jefferson UniversityWilliam D. Emper - Thomas Jefferson UniversityAsif M. Ilyas - Thomas Jefferson University
- Publication Details
- Orthopedics (Thorofare, N.J.), v 45(2), pp 116-121
- Publisher
- Slack Inc
- Number of pages
- 6
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Pediatrics
- Web of Science ID
- WOS:000819930500018
- Scopus ID
- 2-s2.0-85127729736
- Other Identifier
- 991021838159004721
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InCites Highlights
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- Collaboration types
- Domestic collaboration
- Web of Science research areas
- Orthopedics