Evaluation of the quality of an injury surveillance system

Am J Epidemiol. 1999 Mar 15;149(6):586-92. doi: 10.1093/oxfordjournals.aje.a009856.

Abstract

The sensitivity, positive predictive value, and representativeness of the Canadian Hospitals Injury Reporting and Prevention Program (CHIRPP) were assessed. Sensitivity was estimated at four centers in June through August 1992, by matching independently identified injuries with those in the CHIRPP database. The positive predictive value was determined by reviewing all "injuries" in the database (at Montreal Children's Hospital) that could not be matched. Representativeness was assessed by comparing missed with captured injuries (at Montreal Children's Hospital) on demographic, social, and clinical factors. Sensitivity ranged from 30% to 91%, and the positive predictive value was 99.9% (i.e., the frequency of false-positive capture was negligible). The representativeness study compared 277 missed injuries with 2,746 captured injuries. The groups were similar on age, sex, socioeconomic status, delay before presentation, month, and day of presentation. Injuries resulting in admissions, poisonings, and those presenting overnight were, however, more likely to be missed. The adjusted odds ratio of being missed by CHIRPP for admitted injuries (compared with those treated and released) was 13.07 (95% confidence interval 7.82-21.82); for poisonings (compared with all other injuries), it was 9.91 (95% confidence interval 5.39-18.20); and for injuries presenting overnight (compared with those presenting during the day or evening), it was 4.11 (95% confidence interval 3.11-5.44). These injuries were probably missed because of inadequate education of participants in the system. The authors conclude that CHIRPP data are of relatively high quality and may be used, with caution, for research and public health policy.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adolescent
  • Bias
  • Canada / epidemiology
  • Causality
  • Child
  • Child, Preschool
  • Cross-Sectional Studies
  • Data Interpretation, Statistical
  • Evaluation Studies as Topic
  • Female
  • Humans
  • Incidence
  • Infant
  • Male
  • Patient Admission / statistics & numerical data
  • Poisoning / epidemiology
  • Poisoning / prevention & control
  • Population Surveillance*
  • Quality Assurance, Health Care*
  • Sensitivity and Specificity
  • Wounds and Injuries / epidemiology*
  • Wounds and Injuries / prevention & control