What determines frequent attendance at out-of-hours primary care services?

Eur J Public Health. 2015 Aug;25(4):563-8. doi: 10.1093/eurpub/cku235. Epub 2015 Jan 22.

Abstract

Background: A detailed description of the characteristics of frequent attenders (FAs) at primary care services is needed to devise measures to contain the phenomenon. The aim of this population-registry-based research was to sketch an overall picture of the determinants of frequent attendance at out-of-hours (OOH) services, considering patients' clinical conditions and socio-demographic features, and whether the way patients' genaral practitioners (GPs) were organized influenced their likelihood of being FAs.

Methods: This study was a retrospective cohort study on electronic population-based records. The dataset included all OOH primary care service contacts from 1 January to 31 December 2011, linked with the mortality registry and with patients' exemption from health care charges. A FA was defined as a patient who contacted the service three or more times in 12 months. A logistic regression model was constructed to identify independent variables associated with this outcome.

Results: Multivariate analysis showed that not only frailty and clinical variables such as psychiatric disease are associated with FA status, but also socio-demographic variables such as sex, age and income level. Alongside other environmental factors, the GP's gender and mode of collaboration in the provision of health services were also associated with OOH FA.

Conclusion: Our study demonstrates that the determinants of OOH FA include not only patients' clinical conditions, but also several socio-economic characteristics (including income level) and their GPs' organizational format.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adolescent
  • Adult
  • After-Hours Care / statistics & numerical data*
  • Age Factors
  • Aged
  • Aged, 80 and over
  • Child
  • Child, Preschool
  • Female
  • General Practitioners / statistics & numerical data*
  • Humans
  • Infant
  • Infant, Newborn
  • Italy
  • Logistic Models
  • Male
  • Middle Aged
  • Physician-Patient Relations
  • Psychotic Disorders / therapy
  • Retrospective Studies
  • Sex Factors
  • Socioeconomic Factors
  • Young Adult