Utilisation rates in capitated primary care centres serving low income populations

N Z Med J. 2000 Oct 27;113(1120):436-8.

Abstract

Aim: To measure utilisation rates in capitated primary care organisations serving low income populations with low or zero co-payments, and to examine the relationship between utilisation rates and organisation, age group, sex, ethnicity, community services card (CSC) holding rates, high use health card (HUHC) holding rates and deprivation of area of residence (NZDep96).

Methods: Data were collected during 1997/98, from eleven primary care organisations. Utilisation data were collected from practice computer information systems.

Results: 53.9% of registered patients were recorded as having consulted in a twelve-month period. Utilisation rates for doctor, nurse and midwife combined were higher amongst the young, elderly, and CSC holders. For males, they were higher amongst those living in the most socioeconomically deprived areas, but not for females. Utilisation rates were highest amongst the 'other' ethnic group, and lowest in the Pacific Island ethnic group. Organisation, age group, sex, ethnicity, CSC, HUHC and NZDep96 were independently predictive of total utilisation.

Conclusions: Utilisation rates in capitated practices tended to be lower than those in fee-for-service practices. If equitable needs-based capitation funding formulas are to be developed, utilisation data from capitated practices in a range of cultural and socioeconomic settings is urgently required.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adolescent
  • Adult
  • Age Factors
  • Aged
  • Capitation Fee*
  • Child
  • Child, Preschool
  • Community Health Centers / economics
  • Community Health Centers / statistics & numerical data*
  • Deductibles and Coinsurance
  • Female
  • Health Care Surveys
  • Humans
  • Infant
  • Infant, Newborn
  • Male
  • Middle Aged
  • Multivariate Analysis
  • Needs Assessment
  • New Zealand
  • Poverty Areas*
  • Primary Health Care / economics
  • Primary Health Care / statistics & numerical data*
  • Regression Analysis
  • Residence Characteristics / statistics & numerical data
  • Sex Factors
  • Utilization Review