Characterization of adverse events detected in a large health care delivery system using an enhanced global trigger tool over a five-year interval

Health Serv Res. 2014 Oct;49(5):1407-25. doi: 10.1111/1475-6773.12163. Epub 2014 Mar 13.

Abstract

Objective: To report 5 years of adverse events (AEs) identified using an enhanced Global Trigger Tool (GTT) in a large health care system.

Study setting: Records from monthly random samples of adults admitted to eight acute care hospitals from 2007 to 2011 with lengths of stay ≥3 days were reviewed.

Study design: We examined AE incidence overall and by presence on admission, severity, stemming from care provided versus omitted, preventability, and category; and the overlap with commonly used AE-detection systems.

Data collection: Professional nurse reviewers abstracted 9,017 records using the enhanced GTT, recording triggers and AEs. Medical record/account numbers were matched to identify overlapping voluntary reports or AHRQ Patient Safety Indicators (PSIs).

Principal findings: Estimated AE rates were as follows: 61.4 AEs/1,000 patient-days, 38.1 AEs/100 discharges, and 32.1 percent of patients with ≥1 AE. Of 1,300 present-on-admission AEs (37.9 percent of total), 78.5 percent showed NCC-MERP level F harm and 87.6 percent were "preventable/possibly preventable." Of 2,129 hospital-acquired AEs, 63.3 percent had level E harm, 70.8 percent were "preventable/possibly preventable"; the most common category was "surgical/procedural" (40.5 percent). Voluntary reports and PSIs captured <5 percent of encounters with hospital-acquired AEs.

Conclusions: AEs are common and potentially amenable to prevention. GTT-identified AEs are seldom caught by commonly used AE-detection systems.

Keywords: Adverse events; Global Trigger Tool.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Delivery of Health Care, Integrated / statistics & numerical data*
  • Drug-Related Side Effects and Adverse Reactions / epidemiology*
  • Humans
  • Incidence
  • Length of Stay / statistics & numerical data*
  • Medical Errors / statistics & numerical data*
  • Medical Records / statistics & numerical data*
  • Models, Statistical
  • Patient Safety / statistics & numerical data*
  • Quality Indicators, Health Care*
  • Retrospective Studies
  • Texas / epidemiology