Measuring hospital adverse events: assessing inter-rater reliability and trigger performance of the Global Trigger Tool

Int J Qual Health Care. 2010 Aug;22(4):266-74. doi: 10.1093/intqhc/mzq026. Epub 2010 Jun 9.


Objective: To determine the inter-rater reliability of the Institute for Healthcare Improvement's Global Trigger Tool (GTT) in a practice setting, and explore the value of individual triggers.

Design: Prospective assessment of application of the GTT to monthly random samples of hospitalized patients at four hospitals across three regions in the USA.

Setting: Mayo Clinic campuses are in Minnesota, Arizona and Florida.

Participants: A total of 1138 non-pediatric inpatients from all units across the hospital.

Intervention: GTT was applied to randomly selected medical records with independent assessments of two registered nurses with a physician review for confirmation.

Main outcome measure: The Cohen Kappa coefficient was used as a measure of inter-rater agreement. The positive predictive value was assessed for individual triggers.

Results: Good levels of reliability were obtained between independent nurse reviewers at the case-level for both the occurrence of any trigger and the identification of an adverse event. Nurse reviewer agreement for individual triggers was much more varied. Higher agreement appears to occur among triggers that are objective and consistently recorded in selected portions of the medical record. Individual triggers also varied on their yield to detect adverse events. Cases with adverse events had significantly more triggers identified (mean 4.7) than cases with no adverse events (mean 1.8).

Conclusions: The trigger methodology appears to be a promising approach to the measurement of patient safety. However, automated processes could make the process more efficient in identifying adverse events and has a greater potential of improving care delivery and patient 'outcomes'.

MeSH terms

  • Arizona
  • Florida
  • Hospitals / standards*
  • Hospitals / statistics & numerical data
  • Humans
  • Medical Audit
  • Medical Errors / prevention & control
  • Medical Errors / statistics & numerical data
  • Minnesota
  • Observer Variation*
  • Quality Indicators, Health Care / standards
  • Safety Management / methods
  • Safety Management / statistics & numerical data