Relationships between work-environment characteristics and behavioral health provider burnout in the Veterans Health Administration.

Kara Zivin, Ming-Un Myron Chang, Tony Van, Katerine Osatuke, Matt Boden, Rebecca K Sripada, Kristen M Abraham, Paul N Pfeiffer, Hyungjin Myra Kim
Author Information
  1. Kara Zivin: Center for Clinical Management Research, VA Ann Arbor Healthcare System, Ann Arbor, Michigan, USA. ORCID
  2. Ming-Un Myron Chang: Center for Clinical Management Research, VA Ann Arbor Healthcare System, Ann Arbor, Michigan, USA.
  3. Tony Van: Center for Clinical Management Research, VA Ann Arbor Healthcare System, Ann Arbor, Michigan, USA.
  4. Katerine Osatuke: VHA National Center for Organization Development, Cincinnati, Ohio, USA.
  5. Matt Boden: Program Evaluation and Resource Center and VA Office of Mental Health Operations, VA Palo Alto Health Care System, Palo Alto, California, USA.
  6. Rebecca K Sripada: Center for Clinical Management Research, VA Ann Arbor Healthcare System, Ann Arbor, Michigan, USA.
  7. Kristen M Abraham: Center for Clinical Management Research, VA Ann Arbor Healthcare System, Ann Arbor, Michigan, USA.
  8. Paul N Pfeiffer: Center for Clinical Management Research, VA Ann Arbor Healthcare System, Ann Arbor, Michigan, USA.
  9. Hyungjin Myra Kim: Center for Clinical Management Research, VA Ann Arbor Healthcare System, Ann Arbor, Michigan, USA.

Abstract

OBJECTIVE: To identify work-environment characteristics associated with Veterans Health Administration (VHA) behavioral health provider (BHP) burnout among psychiatrists, psychologists, and social workers.
DATA SOURCES: The 2015-2018 data from Annual All Employee Survey (AES); Mental Health Provider Survey (MHPS); N = 57,397 respondents; facility-level Mental Health Onboard Clinical (MHOC) staffing and productivity data, N = 140 facilities.
STUDY DESIGN: For AES and MHPS separately, we used mixed-effects logistic regression to predict BHP burnout using surveys from year pairs (2015-2016, 2016-2017, 2017-2018; six models). Within each year-pair, we used the earlier year of data to train models and tested the model in the later year, with burnout (emotional exhaustion and/or depersonalization) as the outcome for each survey. We used potentially modifiable work-environment characteristics as predictors, controlling for employee demographic characteristics as covariates, and employment facility as random intercepts.
DATA COLLECTION/EXTRACTION METHODS: We included work-environment predictors that appeared in all 4 years (11 in AES; 17 in MHPS).
PRINCIPAL FINDINGS: In 2015-2018, 31.0%-38.0% of BHPs reported burnout in AES or MHPS. Work characteristics consistently associated with significantly lower burnout were included for AES: reasonable workload; having appropriate resources to perform a job well; supervisors address concerns; given an opportunity to improve skills. For MHPS, characteristics included: reasonable workload; work improves veterans' lives; mental health care provided is well-coordinated; and three reverse-coded items: staffing vacancies; daily work that clerical/support staff could complete; and collateral duties reduce availability for patient care. Facility-level staffing ratios and productivity did not significantly predict individual-level burnout. Workload represented the strongest predictor of burnout in both surveys.
CONCLUSIONS: This study demonstrated substantial, ongoing impacts that having appropriate resources including staff, workload, and supervisor support had on VHA BHP burnout. VHA may consider investing in approaches to mitigate the impact of BHP burnout on employees and their patients through providing staff supports, managing workload, and goal setting.

Keywords

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Grants

  1. I01 HX002553/HSRD VA
  2. IK6 HX003397/HSRD VA

MeSH Term

Burnout, Professional
Humans
Job Satisfaction
Psychiatry
Surveys and Questionnaires
Veterans Health
Workload
Workplace

Word Cloud

Created with Highcharts 10.0.0burnoutcharacteristicsMHPSworkloadwork-environmentHealthhealthBHPAESVHAdatastaffingusedyearstaffassociatedVeteransAdministrationbehavioralproviderDATA2015-2018SurveyMentalproductivitypredictsurveysmodelspredictorsincludedsignificantlyreasonableappropriateresourcesworkmentalcaresupervisorsupportOBJECTIVE:identifyamongpsychiatristspsychologistssocialworkersSOURCES:AnnualEmployeeProviderN = 57397respondentsfacility-levelOnboardClinicalMHOCN = 140facilitiesSTUDYDESIGN:separatelymixed-effectslogisticregressionusingpairs2015-20162016-20172017-2018sixWithinyear-pairearliertraintestedmodellateremotionalexhaustionand/ordepersonalizationoutcomesurveypotentiallymodifiablecontrollingemployeedemographiccovariatesemploymentfacilityrandominterceptsCOLLECTION/EXTRACTIONMETHODS:appeared4 years1117PRINCIPALFINDINGS:310%-380%BHPsreportedWorkconsistentlylowerAES:performjobwellsupervisorsaddressconcernsgivenopportunityimproveskillsincluded:improvesveterans'livesprovidedwell-coordinatedthreereverse-codeditems:vacanciesdailyclerical/supportcompletecollateraldutiesreduceavailabilitypatientFacility-levelratiosindividual-levelWorkloadrepresentedstrongestpredictorCONCLUSIONS:studydemonstratedsubstantialongoingimpactsincludingmayconsiderinvestingapproachesmitigateimpactemployeespatientsprovidingsupportsmanaginggoalsettingRelationshipsproviders

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