Assessing the variation in workload among general practitioners in urban and rural areas: An analysis based on SMS time sampling data

Int J Health Plann Manage. 2019 Jan;34(1):e474-e486. doi: 10.1002/hpm.2663. Epub 2018 Sep 20.

Abstract

Objective: An important reason why general practitioners (GPs) are less inclined to work in rural areas is a perception of a higher workload. This study assesses the differences in the workloads of GPs in rural and urban areas. We used two definitions of rurality, one based on the number of addresses per square kilometre, and a second defined by the expected decline in population.

Methods: We collected time use data over 1 year by sending SMS text messages to Dutch GPs who each participated during a period of 1 week. This data was matched with those from GPs' registration and practice location. Data from 596 self-employed GPs were analysed using descriptive statistics and multiple regression analyses.

Results: In group practices, the patient list size of rural GPs was, on average, 231 patients more than those of urban GPs. They worked 3.5 more hours per week, with 2.6 more hours directly related to patients. A small significant relation was found between degree of urbanisation and the dependent variables list size and working hours. Working in a depopulation area had no significant effect on the workload indicators. Furthermore, GPs in group practices worked significantly fewer hours, and had smaller list sizes, than GPs in single-handed practices.

Conclusion: The results show that the assumption of a higher workload in rural practices does not completely match the objective workload of GPs in these areas. Rural GPs have a higher workload in certain cases, but the type of a practice seems a more important determinant.

Keywords: GP; health workforce planning; rural areas; shortages; workload.

Publication types

  • Comparative Study

MeSH terms

  • General Practitioners*
  • Humans
  • Medically Underserved Area*
  • Netherlands
  • Rural Health Services*
  • Text Messaging
  • Urban Health Services*
  • Workload* / statistics & numerical data