Quantifying Patient Preferences for Out-Of-Hours Primary Care

J Health Serv Res Policy. 2000 Oct;5(4):214-8. doi: 10.1177/135581960000500405.

Abstract

Objective: To quantify public preferences for different attributes of out-of-hours primary medical care.

Methods: This study applies a technique called conjoint analysis. A focus group was convened to identify the most important attributes for inclusion in the study, followed by a postal questionnaire asking people to choose between hypothetical services containing different mixes of these attributes. Multi-variate regression analysis estimated the relative importance of different attributes to respondents. The respondents were 436 adults who were among respondents to an earlier postal survey of 25,090 randomly selected Sheffield residents.

Results: The doctor's manner (whether the doctor takes time to listen), the type of consultation (whether the patient receives a home visit, telephone advice, sees an accident and emergency doctor or attends a primary care treatment centre) and waiting time for consultation best predicted the public's preferences for out-of-hours care. Another three attributes--ease of access; seeing a familiar doctor; and the doctor's shift arrangements--were not statistically significant.

Conclusions: By asking people to make simple choices between hypothetical services, it is possible to quantify their strength of preference for different aspects of a service. This has important implications for the planning of services. Specifically, for out-of-hours services, more consideration should be given to the doctor's manner and waiting times rather than familiarity of doctor.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Data Interpretation, Statistical
  • Decision Making
  • Focus Groups
  • Health Services Accessibility
  • Health Services Research
  • Humans
  • Night Care / organization & administration*
  • Night Care / statistics & numerical data
  • Patient Acceptance of Health Care / statistics & numerical data*
  • Patient Satisfaction / statistics & numerical data*
  • Primary Health Care / organization & administration
  • Primary Health Care / statistics & numerical data*
  • State Medicine / organization & administration
  • Surveys and Questionnaires
  • United Kingdom