[Comparison of the "Trigger" tool with the minimum basic data set for detecting adverse events in general surgery]

Rev Calid Asist. 2017 Jul-Aug;32(4):209-214. doi: 10.1016/j.cali.2017.01.001. Epub 2017 Mar 15.
[Article in Spanish]

Abstract

Introduction: Surgery is a high risk for the occurrence of adverse events (AE). The main objective of this study is to compare the effectiveness of the Trigger tool with the Hospital National Health System registration of Discharges, the minimum basic data set (MBDS), in detecting adverse events in patients admitted to General Surgery and undergoing surgery.

Material and methods: Observational and descriptive retrospective study of patients admitted to general surgery of a tertiary hospital, and undergoing surgery in 2012. The identification of adverse events was made by reviewing the medical records, using an adaptation of "Global Trigger Tool" methodology, as well as the (MBDS) registered on the same patients. Once the AE were identified, they were classified according to damage and to the extent to which these could have been avoided. The area under the curve (ROC) were used to determine the discriminatory power of the tools. The Hanley and Mcneil test was used to compare both tools.

Results: AE prevalence was 36.8%. The TT detected 89.9% of all AE, while the MBDS detected 28.48%. The TT provides more information on the nature and characteristics of the AE. The area under the curve was 0.89 for the TT and 0.66 for the MBDS. These differences were statistically significant (P<.001).

Conclusions: The Trigger tool detects three times more adverse events than the MBDS registry. The prevalence of adverse events in General Surgery is higher than that estimated in other studies.

Keywords: Adverse event; Cirugía general; Conjunto mínimo básico de datos; Evento adverso; General surgery; Minimum basic data set; Patient safety; Seguridad del paciente; Trigger Tool; Trigger tool.

Publication types

  • Comparative Study
  • Observational Study

MeSH terms

  • Datasets as Topic
  • Hospital Information Systems
  • Humans
  • Medical Errors / statistics & numerical data*
  • Medical Records*
  • Patient Safety*
  • Quality Indicators, Health Care*
  • Retrospective Studies
  • Surgical Procedures, Operative*