Variation in detected adverse events using trigger tools: A systematic review and meta-analysis

Abstract

Background Adverse event (AE) detection is a major patient safety priority. However, despite extensive research on AEs, reported incidence rates vary widely. Objective This study aimed: (1) to synthesize available evidence on AE incidence in acute care inpatient settings using Trigger Tool methodology; and (2) to explore whether study characteristics and study quality explain variations in reported AE incidence. Design Systematic review and meta-analysis. Methods To identify relevant studies, we queried PubMed, EMBASE, CINAHL, Cochrane Library and three journals in the patient safety field (last update search 25.05.2022). Eligible publications fulfilled the following criteria: adult inpatient samples; acute care hospital settings; Trigger Tool methodology; focus on specialty of internal medicine, surgery or oncology; published in English, French, German, Italian or Spanish. Systematic reviews and studies addressing adverse drug events or exclusively deceased patients were excluded. Risk of bias was assessed using an adapted version of the Quality Assessment Tool for Diagnostic Accuracy Studies 2. Our main outcome of interest was AEs per 100 admissions. We assessed nine study characteristics plus study quality as potential sources of variation using random regression models. We received no funding and did not register this review. Results Screening 6,685 publications yielded 54 eligible studies covering 194,470 admissions. The cumulative AE incidence was 30.0 per 100 admissions (95% CI 23.9–37.5; I2 = 99.7%) and between study heterogeneity was high with a prediction interval of 5.4–164.7. Overall studies’ risk of bias and applicability-related concerns were rated as low. Eight out of nine methodological study characteristics did explain some variation of reported AE rates, such as patient age and type of hospital. Also, study quality did explain variation. Conclusion Estimates of AE studies using trigger tool methodology vary while explaining variation is seriously hampered by the low standards of reporting such as the timeframe of AE detection. Specific reporting guidelines for studies using retrospective medical record review methodology are necessary to strengthen the current evidence base and to help explain between study variation.

Incidence and characteristics of adverse events in paediatric inpatient care: a systematic review and meta-analysis

“…This is also considerably lower than our corresponding estimate for GTT/TT studies at 24.8 and 103.6 (general care and intensive care populations) AEs per 100 admissions. On the other hand, a newly published systematic review29 including GTT/TT studies in general care reported a pooled incidence of 30.0 AEs per 100 adult admissions which is higher compared with our findings in the general care population.…”

“…In a recently published meta-analysis for adult inpatients, some of the variation could be explained by those methodological aspects (type of hospital included, age of sample included and experience of the review team). 29 …”

“…Although, it would have been very interesting to analyse the variation based on the different methodological applications, it was outside of the scope of this review. In a recently published meta-analysis for adult inpatients, some of the variation could be explained by those methodological aspects (type of hospital included, age of sample included and experience of the review team) 29…”

“…To assess the methodological quality of each included study, a previously used quality assessment tool (QAT) was adapted. This QAT was based on the structure of the Quality Assessment Tool for Diagnostic Accuracy Studies 2 tool 27 and the content of the QAT by Musy et al 28 and later by Eggenschwiler et al 29 ( online supplemental material 1, page 14 ). The QAT consists of five domains: patient selection, reviewers, record review process, outcomes and flow.…”

Identifying neonatal adverse events in preterm and term infants using a paediatric trigger tool

“…One explanation for the variation of AE rates may be the patients' care need, as patients in need of complex medical procedures are more likely to experience AEs 18 . Another reason may be related to methodological differences, for example, the AE definition used and time frame of AE detection 19 . The high rate of AEs in the present study might partly be explained by the 88 triggers including ‘other’ as an alternative.…”