A comparison of hospital adverse events identified by three widely used detection methods

Int J Qual Health Care. 2009 Aug;21(4):301-7. doi: 10.1093/intqhc/mzp027.


Objective: Determine the degree of congruence between several measures of adverse events.

Design: Cross-sectional study to assess frequency and type of adverse events identified using a variety of methods.

Setting: Mayo Clinic Rochester hospitals.

Participants: All inpatients discharged in 2005 (n = 60 599).

Interventions: Adverse events were identified through multiple methods: (i) Agency for Healthcare Research and Quality-defined patient safety indicators (PSIs) using ICD-9 diagnosis codes from administrative discharge abstracts, (ii) provider-reported events, and (iii) Institute for Healthcare Improvement Global Trigger Tool with physician confirmation. PSIs were adjusted to exclude patient conditions present at admission.

Main outcome measure: Agreement of identification between methods.

Results: About 4% (2401) of hospital discharges had an adverse event identified by at least one method. Around 38% (922) of identified events were provider-reported events. Nearly 43% of provider-reported adverse events were skin integrity events, 23% medication events, 21% falls, 1.8% equipment events and 37% miscellaneous events. Patients with adverse events identified by one method were not usually identified using another method. Only 97 (6.2%) of hospitalizations with a PSI also had a provider-reported event and only 10.5% of provider-reported events had a PSI.

Conclusions: Different detection methods identified different adverse events. Findings are consistent with studies that recommend combining approaches to measure patient safety for internal quality improvement. Potential reported adverse event inconsistencies, low association with documented harm and reporting differences across organizations, however, raise concerns about using these patient safety measures for public reporting and organizational performance comparison.

MeSH terms

  • Cross-Sectional Studies
  • Documentation
  • Hospital Administration / statistics & numerical data*
  • Humans
  • Incidence
  • International Classification of Diseases / statistics & numerical data
  • Medical Errors / statistics & numerical data*
  • Quality Assurance, Health Care
  • Quality Indicators, Health Care / statistics & numerical data*
  • Safety Management / statistics & numerical data*
  • United States
  • United States Agency for Healthcare Research and Quality / statistics & numerical data