SMS text messaging to measure working time: the design of a time use study among general practitioners

BMC Health Serv Res. 2018 Feb 20;18(1):131. doi: 10.1186/s12913-018-2926-z.

Abstract

Background: Measuring the working hours of general practitioners (GPs) is an important but complex task due to the effects of bias related to self-reporting, recall, and stress. In this paper we describe the deployment, feasibility, and implementation of an innovative method for measuring, in real time, GPs' working time, plus the response to the study.

Methods: A Short Message Service (SMS) application was developed which sent messages at random to GPs during their working week. Approximately nineteen GPs participated each week during a period of 57 weeks. The text messages asked if GPs were doing activities related to patients, directly, indirectly, or not at all, at the moment of sending. Participants were requested to reply by SMS.

Results: Approximately 27,000 messages were sent to 1051 GPs over more than one year. The SMS system was functioning 99.9% of the time. GPs replied to 94% of all the messages sent. Only a few participants dropped out of the study. The data was available in real time enabling the researchers to monitor the response and overall quality of the data each day.

Conclusions: The SMS method offers advantages over other instruments of measurement because it allows a better response, ease of use and avoids recall bias. This makes it a feasible method to collect valid data about GPs working time.

Keywords: Data collection; General practitioners; Health workforce planning; Text message (SMS); Use of time; Working time; Workload data.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Data Collection / methods*
  • Feasibility Studies
  • Female
  • General Practitioners* / psychology
  • General Practitioners* / statistics & numerical data
  • Health Services Research / methods
  • Humans
  • Male
  • Middle Aged
  • Reproducibility of Results
  • Text Messaging*
  • Time Factors
  • Workload / statistics & numerical data*