PMID- 30395000 OWN - NLM STAT- MEDLINE DCOM- 20220217 LR - 20230930 IS - 1549-8425 (Electronic) IS - 1549-8417 (Print) IS - 1549-8417 (Linking) VI - 17 IP - 8 DP - 2021 Dec 1 TI - Multicenter Test of an Emergency Department Trigger Tool for Detecting Adverse Events. PG - e843-e849 LID - 10.1097/PTS.0000000000000516 [doi] AB - OBJECTIVES: Traditional approaches to safety and quality screening in the emergency department (ED) are porous and low yield for identifying adverse events (AEs). A better approach may be in the use of trigger tool methodology. We recently developed a novel ED trigger tool using a multidisciplinary, multicenter approach. We conducted a multicenter test of this tool and assess its performance. METHODS: In design and participants, we studied the ED trigger tool for a 13-month period at four EDs. All patients 18 years and older with Emergency Severity Index acuity levels of 1 to 3 seen by a provider were eligible. Reviewers completed standardized training modules. Each site reviewed 50 randomly selected visits per month. A first-level reviewer screened for presence of predefined triggers (findings that increase the probability of an AE). If no trigger is present, the review is deemed complete. When present, a trigger prompts an in-depth review for an AE. Any event identified is assigned a level of harm using the Medication Event Reporting and Prevention (MERP) Index, ranging from a near miss (A) to patient death (I). Events are noted as present on arrival or in the ED, an act of commission or omission, and are assigned one of four event categories. A second-level physician performs a confirmatory review of all AEs and independently reviews 10% of cases to estimate the false-negative rate. All AEs or potential AEs were reviewed in monthly group calls for consensus on findings. The primary outcome is the proportion of visits in which an AE is identified, overall and by site. Secondary outcomes include categories of events, distribution of harm ratings, and association of AEs with sociodemographic and clinical factors and triggers. We present sociodemographic data and details about AEs and results of logistic regression for associations of AEs with of triggers, sociodemographics, and clinical variables. RESULTS: We captured 2594 visits that are representative, within site, of their patient population. Overall, the sample is 64% white, 54% female, and with a mean age of 51. Variability is observed between sites for age, race, and insurance, but not sex. A total of 240 events were identified in 228 visits (8.8%) of which 53.3% were present on arrival, 19.7% were acts of omission, and 44.6% were medication-related, with some variability across sites. A MERP F score (contributing to need for admission, higher level of care, or prolonged hospitalization) was the most common severity level (35.4% of events). Overall, 185 (77.1%) of 240 events involved patient harm (MERP level >/= E), affecting 175 visits (6.7%). Triggers were present in 951 visits (36.6%). Presence of any trigger was strongly associated with an AE (adjusted odds ratio = 4.6, 95% confidence interval = 3.2-6.6). Ten triggers were individually associated with AEs (adjusted odds ratio = 2.1-7.7). Variability was observed across sites in individual trigger associations, event rates, and categories, but not in severity ratings of events. The overall false-negative rate was 6.1%. CONCLUSIONS: The trigger tool approach was successful in identifying meaningful events. The ED trigger tool seems to be a promising approach for identifying all-cause harm in the ED. CI - Copyright (c) 2018 Wolters Kluwer Health, Inc. All rights reserved. FAU - Griffey, Richard T AU - Griffey RT AD - From the Division of Emergency Medicine, Washington University School of Medicine, St. Louis, Missouri. FAU - Schneider, Ryan M AU - Schneider RM AD - From the Division of Emergency Medicine, Washington University School of Medicine, St. Louis, Missouri. FAU - Sharp, Brian R AU - Sharp BR AD - Department of Emergency Medicine, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin. FAU - Pothof, Jeff AU - Pothof J AD - Department of Emergency Medicine, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin. FAU - Vrablik, Marie C AU - Vrablik MC AD - Department of Emergency Medicine, University of Washington, Seattle, Washington. FAU - Granzella, Nic AU - Granzella N AD - Department of Emergency Medicine, University of Washington, Seattle, Washington. FAU - Todorov, Alexandre A AU - Todorov AA AD - Department of Psychiatry, Washington University School of Medicine, St. Louis, Missouri. FAU - Adler, Lee AU - Adler L AD - Department of Medicine, University of Central Florida, Orlando, Florida; and Office of Clinical Effectiveness, Adventist Health System, Altamonte, Florida. LA - eng GR - R18 HS025052/HS/AHRQ HHS/United States PT - Journal Article PT - Multicenter Study PL - United States TA - J Patient Saf JT - Journal of patient safety JID - 101233393 SB - IM MH - *Emergency Service, Hospital MH - Female MH - Humans MH - Logistic Models MH - Male MH - Mass Screening MH - Middle Aged MH - *Patient Harm MH - Patient Safety PMC - PMC6343477 MID - NIHMS972688 EDAT- 2018/11/06 06:00 MHDA- 2022/02/19 06:00 PMCR- 2022/12/01 CRDT- 2018/11/06 06:00 PHST- 2018/11/06 06:00 [pubmed] PHST- 2022/02/19 06:00 [medline] PHST- 2018/11/06 06:00 [entrez] PHST- 2022/12/01 00:00 [pmc-release] AID - 01209203-202112000-00030 [pii] AID - 10.1097/PTS.0000000000000516 [doi] PST - ppublish SO - J Patient Saf. 2021 Dec 1;17(8):e843-e849. doi: 10.1097/PTS.0000000000000516.