Emergency Department Adverse Events Detected Using the Emergency Department Trigger Tool

Griffey, Richard T.; Schneider, Ryan; Todorov, Alexandre A.

doi:10.1016/j.annemergmed.2022.05.037

Cited by 1 publication

(3 citation statements)

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“…For example, if we know (via the trigger “M19: propofol”) the number of visits in which this medication was given in our sample and in the general population, and we know how often AEs were identified in cases in our sample in which propofol was given, then we have a much better sense for the scope and magnitude of this issue. In our single‐center study we estimated that propofol‐related AEs occurred in 33% of cases in which this medication was used, prompting an ongoing quality improvement initiative 27 . Third, knowing the trigger distribution in our overall population and trigger associations with harm, we can project anticipated levels of harm related to a trigger on a population basis.…”

Section: Introductionmentioning

confidence: 98%

“…In our single-center study we estimated that propofol-related AEs occurred in 33% of cases in which this medication was used, prompting an ongoing quality improvement initiative. 27 Third, knowing the trigger distribution in our overall population and trigger associations with harm, we can project anticipated levels of harm related to a trigger on a population basis. For example, we estimate that 9% of our annual ED visits are for AEs that are present on arrival, for harm that occurred elsewhere in the health care system.…”

Section: Introductionmentioning

confidence: 99%

“…We previously created a trigger tool specific to the ED (EDTT), describing its development, 22 derivation, 23 use, 24 validation, 25 and details of near misses 26 and harm detected in the ED, 27 present on arrival to the ED, 28 and among postacute care and long‐term care patients 29 . The EDTT features: (1) a computerized query of the electronic medical record (EMR) for triggers, (2) use of only triggers demonstrated to be associated with AEs (not based on expert consensus alone), and (3) the use of trigger weights (the relative strengths of trigger associations with AEs) to allow a deliberate sampling strategy to enhance AE detection.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

The emergency department trigger tool: Multicenter trigger query validation

Griffey,

Schneider,

Kocher

et al. 2024

Academic Emergency Medicine

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ObjectivesWe previously described derivation and validation of the emergency department trigger tool (EDTT) for adverse event (AE) detection. As the first step in our multicenter study of the tool, we validated our computerized screen for triggers against manual review, establishing our use of this automated process for selecting records to review for AEs.MethodsThis is a retrospective observational study of visits to three urban, academic EDs over 18 months by patients ≥ 18 years old. We reviewed 912 records: 852 with at least one of 34 triggers found by the query and 60 records with none. Two first‐level reviewers per site each manually screened for triggers. After completion, computerized query results were revealed, and reviewers could revise their findings. Second‐level reviewers arbitrated discrepancies. We compare automated versus manual screening by positive and negative predictive values (PPVs, NPVs), present population trigger frequencies, proportions of records triggered, and how often manual ratings were changed to conform with the query.ResultsTrigger frequencies ranged from common (>25%) to rare (1/1000) were comparable at U.S. sites and slightly lower at the Canadian site. Proportions of triggered records ranged from 31% to 49.4%. Overall query PPV was 95.4%; NPV was 99.2%. PPVs for individual trigger queries exceeded 90% for 28–31 triggers/site and NPVs were >90% for all but three triggers at one site. Inter‐rater reliability was excellent, with disagreement on manual screening results less than 5% of the time. Overall, reviewers amended their findings 1.5% of the time when discordant with query findings, more often when the query was positive than when negative (47% vs. 23%).ConclusionsThe EDTT trigger query performed very well compared to manual review. With some expected variability, trigger frequencies were similar across sites and proportions of triggered records ranged 31%–49%. This demonstrates the feasibility and generalizability of implementing the EDTT query, providing a solid foundation for testing the triggers’ utility in detecting AEs.

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Section: Introductionmentioning

confidence: 98%

Section: Introductionmentioning

confidence: 99%