Performance characteristics of a methodology to quantify adverse events over time in hospitalized patients

Health Serv Res. 2011 Apr;46(2):654-78. doi: 10.1111/j.1475-6773.2010.01156.x. Epub 2010 Aug 16.


Objective: To assess the performance characteristics of the Institute for Healthcare Improvement Global Trigger Tool (GTT) to determine its reliability for tracking local and national adverse event rates.

Data sources: Primary data from 2008 chart reviews.

Study design: A retrospective study in a stratified random sample of 10 North Carolina hospitals. Hospital-based (internal) and contract research organization-hired (external) reviewers used the GTT to identify adverse events in the same 10 randomly selected medical records per hospital in each quarter from January 2002 through December 2007.

Data collection/extraction: Interrater and intrarater reliability was assessed using κ statistics on 10 percent and 5 percent, respectively, of selected medical records. Additionally, experienced GTT users reviewed 10 percent of records to calculate internal and external teams' sensitivity and specificity.

Principal findings: Eighty-eight to 98 percent of the targeted 2,400 medical records were reviewed. The reliability of the GTT to detect the presence, number, and severity of adverse events varied from κ=0.40 to 0.60. When compared with a team of experienced reviewers, the internal teams' sensitivity (49 percent) and specificity (94 percent) exceeded the external teams' (34 and 93 percent), as did their performance on all other metrics.

Conclusions: The high specificity, moderate sensitivity, and favorable interrater and intrarater reliability of the GTT make it appropriate for tracking local and national adverse event rates. The strong performance of hospital-based reviewers supports their use in future studies.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Aged
  • Female
  • Hospitals / standards*
  • Hospitals / statistics & numerical data
  • Humans
  • Male
  • Medical Audit
  • Medical Errors / statistics & numerical data
  • Middle Aged
  • North Carolina
  • Observer Variation
  • Quality Indicators, Health Care* / statistics & numerical data
  • Quality of Health Care / standards
  • Retrospective Studies
  • Safety / statistics & numerical data
  • Safety Management