GP and patient predictions of sick-listing duration: how well do they correspond? A prospective observational study

Scand J Prim Health Care. 2014 Jun;32(2):73-7. doi: 10.3109/02813432.2014.915132.

Abstract

Objective: To explore how well physicians and patients predict sick-listing duration and the correspondence between their respective predictions. To study possible gender differences concerning prediction accuracy.

Design: Prospective observational study.

Setting: Two medium-sized primary care centres (PCC) in western Sweden.

Subjects: GPs at the PCCs and attending patients sick-listed for > 14 days.

Main outcome measures: Sick-listing duration; patients' and GPs' predictions of the total duration of the individual patient's sick-listing.

Results: A total of 127 patients (93 women, 34 men, mean age 45 years) and 10 GPs participated in the study. Neither the GPs nor the patients were able to predict the interval until return to work with high accuracy. The GPs' and the patients' perceptions concurred in only 26% of cases. There was a significant difference in the correspondence between the GPs' and patients' respective predictions of sick-listing duration compared with the actual duration. GPs' predictions were more accurate for medium-length duration (1.5-6 months), while patients' predictions were more accurate for long-duration (> 6 months) sick-listing. Patients with less education predicted long duration of sick-listing more accurately than those with more education. There was no significant difference between male and female patients' accuracy of prediction, or between GPs' accuracy of prediction of male vs. female patients' sick-listing duration.

Conclusions: Prediction of total sick-listing duration was hard for both GP and patient; their respective predictions corresponded in only one-quarter of the cases. No gender differences were observed in the accuracy of prediction.

Keywords: General practice; Sweden; prediction; primary care; sick-listing; sickness absence; sickness certification.

Publication types

  • Observational Study

MeSH terms

  • Adult
  • Attitude of Health Personnel
  • Attitude to Health*
  • Educational Status
  • Female
  • Forecasting*
  • General Practice / statistics & numerical data*
  • General Practitioners / psychology
  • Humans
  • Male
  • Middle Aged
  • Physician-Patient Relations
  • Prospective Studies
  • Sick Leave / statistics & numerical data*
  • Sweden
  • Time Factors
  • Work Capacity Evaluation
  • Young Adult