Characterisations of adverse events detected in a university hospital: a 4-year study using the Global Trigger Tool method

BMJ Open. 2014 May 28;4(5):e004879. doi: 10.1136/bmjopen-2014-004879.

Abstract

Objectives: To describe the level, preventability and categories of adverse events (AEs) identified by medical record review using the Global Trigger Tool (GTT). To estimate when the AE occurred in the course of the hospital stay and to compare voluntary AE reporting with medical record reviewing.

Design: Two-stage retrospective record review.

Setting: 650-bed university hospital.

Participants: 20 randomly selected medical records were reviewed every month from 2009 to 2012.

Primary and secondary outcome measures: AE/1000 patient-days. Proportion of AEs found by GTT found also in the voluntary reporting system. AE categorisation. Description of when during hospital stay AEs occur.

Results: A total of 271 AEs were detected in the 960 medical records reviewed, corresponding to 33.2 AEs/1000 patient-days or 20.5% of the patients. Of the AEs, 6.3% were reported in the voluntary AE reporting system. Hospital-acquired infections were the most common AE category. The AEs occurred and were detected during the hospital stay in 65.5% of cases; the rest occurred or were detected within 30 days before or after the hospital stay. The AE usually occurred early during the hospital stay, and the hospital stay was 5 days longer on average for patients with an AE.

Conclusions: Record reviewing identified AEs to a much larger extent than voluntary AE reporting. Healthcare organisations should consider using a portfolio of tools to gain a comprehensive picture of AEs. Substantial costs could be saved if AEs were prevented.

Keywords: Public Health.

MeSH terms

  • Adolescent
  • Adult
  • Aged
  • Aged, 80 and over
  • Cross Infection / epidemiology*
  • Drug-Related Side Effects and Adverse Reactions / epidemiology*
  • Female
  • Hospitals, University*
  • Humans
  • Male
  • Medical Errors / statistics & numerical data*
  • Medical Records
  • Middle Aged
  • Retrospective Studies
  • Time Factors
  • Young Adult