Extending Our Understanding of Burnout and Its Associated Factors: Providers and Staff in Primary Care Clinics

Eval Health Prof. 2016 Sep;39(3):282-98. doi: 10.1177/0163278716637900. Epub 2016 Mar 21.

Abstract

Burnout has been identified as an occupational hazard in the helping professions for many years and is often overlooked, as health-care systems strive to improve cost and quality. The Maslach Burnout Inventory (MBI) and the Areas of Worklife Survey (AWS) are tools for assessing burnout prevalence and its associated factors. We describe how we used them in outpatient clinics to assess burnout for multiple job types. Traditional statistical techniques and seemingly unrelated regression were used to describe the sample and evaluate the association between work life domains and burnout. Of 838 eligible participants, 467 (55.7%) were included for analysis. Burnout prevalence varied across three job categories: providers (37.5%), clinical assistants (24.6%), and other staff (28.0%). It was not related to age, gender, or years of tenure but was lower in part-time workers (24.6%) than in full-time workers (33.9%). Analysis of the AWS subscales identified organizational correlates of burnout. Accurately identifying and defining the operative system factors associated with burnout will make it possible to create successful interventions. Using the MBI and the AWS together can highlight the relationship between system work experiences and burnout.

Keywords: ambulatory care; burnout; health services research; primary care; workforce.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Burnout, Professional / diagnosis
  • Burnout, Professional / epidemiology*
  • Burnout, Professional / psychology*
  • Community Health Services / organization & administration
  • Community Health Services / statistics & numerical data
  • Cross-Sectional Studies
  • Female
  • Health Personnel / psychology*
  • Humans
  • Male
  • Middle Aged
  • Primary Health Care / organization & administration*
  • Primary Health Care / statistics & numerical data
  • Surveys and Questionnaires / standards*
  • Time Factors
  • Work-Life Balance