title: Characterization of adverse events detected in a large health care delivery system using an enhanced global trigger tool over a five-year interval.
abstract: OBJECTIVE
  To report 5 years of adverse events (AEs) identified using an enhanced Global Trigger Tool (GTT) in a large health care system.
  
  
  METHODS
  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.
  
  
  METHODS
  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.
  
  
  METHODS
  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).
  
  
  RESULTS
  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.
authors.affiliation: Office of the Chief Quality Officer, Baylor Health Care System, Baylor Scott and White Health, 8080 N. Central Expressway, Suite 500, Dallas, TX 75206.
authors.forename: Donald A
authors.initials: DA
authors.lastname: Kennerly
authors.forename: Rustam
authors.initials: R
authors.lastname: Kudyakov
authors.forename: Briget
authors.initials: B
authors.lastname: da Graca
authors.forename: Margaret
authors.initials: M
authors.lastname: Saldaña
authors.forename: Jan
authors.initials: J
authors.lastname: Compton
authors.forename: David
authors.initials: D
authors.lastname: Nicewander
authors.forename: Richard
authors.initials: R
authors.lastname: Gilder
mesh_terms: D000328:Adult; D019033:Delivery of Health Care, Integrated / Q000706:statistics & numerical data*; D064420:Drug-Related Side Effects and Adverse Reactions / Q000453:epidemiology*; D006801:Humans; D015994:Incidence; D007902:Length of Stay / Q000706:statistics & numerical data*; D019300:Medical Errors / Q000706:statistics & numerical data*; D008499:Medical Records / Q000706:statistics & numerical data*; D015233:Models, Statistical; D061214:Patient Safety / Q000706:statistics & numerical data*; D019984:Quality Indicators, Health Care; D012189:Retrospective Studies; D013781:Texas / Q000453:epidemiology
keywords: Adverse events; Global Trigger Tool