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Computerized surveillance of opioid-related adverse drug events in perioperative care: a cross-sectional study.

dc.contributor.author Eckstrand, Julie
dc.contributor.author Habib, Ashraf Samir
dc.contributor.author Williamson, A
dc.contributor.author Horvath, MM
dc.contributor.author Gattis, Katherine
dc.contributor.author Cozart, H
dc.contributor.author Ferranti, Jeffrey
dc.coverage.spatial England
dc.date.accessioned 2018-01-01T14:43:36Z
dc.date.available 2018-01-01T14:43:36Z
dc.date.issued 2009-08-11
dc.identifier https://www.ncbi.nlm.nih.gov/pubmed/19671171
dc.identifier 1754-9493-3-18
dc.identifier.uri https://hdl.handle.net/10161/15924
dc.description.abstract BACKGROUND: Given the complexity of surgical care, perioperative patients are at high risk of opioid-related adverse drug events. Existing methods of detection, such as trigger tools and manual chart review, are time-intensive which makes sustainability challenging. Using strategic rule design, computerized surveillance may be an efficient, pharmacist-driven model for event detection that leverages existing staff resources. METHODS: Computerized adverse drug event surveillance uses a logic-based rules engine to identify potential adverse drug events or evolving unsafe clinical conditions. We extended an inpatient rule (administration of naloxone) to detect opioid-related oversedation and respiratory depression to perioperative care at a large academic medical center. Our primary endpoint was the adverse drug event rate. For all patients with a naloxone alert, manual chart review was performed by a perioperative clinical pharmacist to assess patient harm. In patients with confirmed oversedation, other patient safety event databases were queried to determine if they could detect duplicate, prior, or subsequent opioid-related events. RESULTS: We identified 419 cases of perioperative naloxone administration. Of these, 101 were given postoperatively and 69 were confirmed as adverse drug events after chart review yielding a rate of 1.89 adverse drug events/1000 surgical encounters across both the inpatient and ambulatory settings. Our ability to detect inpatient opioid adverse drug events increased 22.7% by expanding surveillance into perioperative care. Analysis of historical surveillance data as well as a voluntary reporting database revealed that 11 of our perioperative patients had prior or subsequent harmful oversedation. Nine of these cases received intraoperative naloxone, and 2 had received naloxone in the post-anesthesia care unit. Pharmacist effort was approximately 3 hours per week to evaluate naloxone alerts and confirm adverse drug events. CONCLUSION: A small investment of resources into a pharmacist-driven surveillance model gave great gains in organizational adverse drug event detection. The patients who experienced multiple events are particularly relevant to future studies seeking risk factors for opioid induced respiratory depression. Computerized surveillance is an efficient, impactful, and sustainable model for ongoing capture and analysis of these rare, but potentially serious events.
dc.language eng
dc.relation.ispartof Patient Saf Surg
dc.relation.isversionof 10.1186/1754-9493-3-18
dc.title Computerized surveillance of opioid-related adverse drug events in perioperative care: a cross-sectional study.
dc.type Journal article
pubs.author-url https://www.ncbi.nlm.nih.gov/pubmed/19671171
pubs.begin-page 18
pubs.issue 1
pubs.organisational-group Anesthesiology
pubs.organisational-group Anesthesiology, Women's
pubs.organisational-group Clinical Science Departments
pubs.organisational-group Community and Family Medicine
pubs.organisational-group Duke
pubs.organisational-group Obstetrics and Gynecology
pubs.organisational-group Pediatrics
pubs.organisational-group Pediatrics, Neonatology
pubs.organisational-group School of Medicine
pubs.organisational-group Staff
pubs.organisational-group Temp group - logins allowed
pubs.publication-status Published online
pubs.volume 3
dc.identifier.eissn 1754-9493


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