Comparison of two methods to report potentially avoidable hospitalizations in France in 2012: a cross-sectional study

BMC Health Serv Res. 2015 Jan 22:15:4. doi: 10.1186/s12913-014-0661-7.

Abstract

Background: Potentially avoidable hospitalizations represent an indirect measure of access to effective primary care. However many approaches have been proposed to measure them and results may differ considerably. This work aimed at examining the agreement between the Weissman and Ansari approaches in order to measure potentially avoidable hospitalizations in France.

Methods: Based on the 2012 French national hospital discharge database (Programme de Médicalisation des Systèmes d'Information), potentially avoidable hospitalizations were measured using two approaches proposed by Weissman et al. and by Ansari et al. Age- and sex-standardised rates were calculated in each department. The two approaches were compared for diagnosis groups, type of stay, severity, age, sex, and length of stay.

Results: The number and age-standardised rate of potentially avoidable hospitalizations estimated by the Weissman et al. and Ansari et al. approaches were 742,474 (13.3 cases per 1,000 inhabitants) and 510,206 (9.0 cases per 1,000 inhabitants), respectively. There are significant differences by conditions groups, age, length of stay, severity level, and proportion of medical stays between the Weissman and Ansari methods.

Conclusions: Regarding potentially avoidable hospitalizations in France in 2012, the agreement between the Weissman and Ansari approaches is poor. The method used to measure potentially avoidable hospitalizations is critical, and might influence the assessment of accessibility and performance of primary care.

Publication types

  • Comparative Study
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adolescent
  • Adult
  • Age Factors
  • Aged
  • Aged, 80 and over
  • Child
  • Child, Preschool
  • Cross-Sectional Studies
  • Female
  • France
  • Hospitalization / statistics & numerical data*
  • Humans
  • Infant
  • Infant, Newborn
  • Length of Stay / statistics & numerical data*
  • Male
  • Medical Futility*
  • Middle Aged
  • Patient Discharge / statistics & numerical data*
  • Primary Health Care / methods*
  • Sex Factors