key: cord-0883660-zvuhx3ta
authors: Zivin, Kara; Chang, Ming‐Un Myron; Van, Tony; Osatuke, Katerine; Boden, Matt; Sripada, Rebecca K.; Abraham, Kristen M.; Pfeiffer, Paul N.; Kim, Hyungjin Myra
title: Relationships between work–environment characteristics and behavioral health provider burnout in the Veterans Health Administration
date: 2022-03-15
journal: Health Serv Res
DOI: 10.1111/1475-6773.13964
sha: e282b96e054c5a9827a728d520fc397abed9322f
doc_id: 883660
cord_uid: zvuhx3ta

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.

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.

burnout, mental health providers, supervisor support, workload

What is known on this topic

• Veterans Health Administration (VHA) behavioral health providers (BHPs) face high risk of burnout due to large organizational demands, and a vulnerable, complex patient population.

• BHPs have the highest risk of burnout after primary care providers in VHA.

• The field has made limited progress to date on mitigating BHP burnout, and clinician turnover can prove expensive and exacerbate burnout among clinicians who remain within VHA.

• Using multiple years of data from two national health system surveys, we conducted the largest study to date of characteristics associated with BHP burnout.

• In addition to having a reasonable workload, having appropriate resources, opportunities to improve, and managerial support had consistent and significant associations with lower BHP burnout.

• This study indicates potentially modifiable targets for policy makers and stakeholders to address persistent characteristics that contribute to burnout among essential providers in the nation's largest integrated health system.

Behavioral health providers (BHPs)-"mission critical" psychiatrists, psychologists, and social workers in the Veterans Health Administration (VHA)-report the second highest level of burnout after primary care physicians. 1 VHA oversees the largest mental health system in the United States, and VHA BHPs may face high risks of burnout due to VHA's unique patient population and bureaucratic demands. 2 In VHA, as elsewhere, insufficient BHP staffing relative to patient need can lead to burnout, turnover, lasting job vacancies, and decreased patient access to care. 3, 4 BHP burnout is associated with negative conditions at the individual and organizational levels, however, many existing studies are small and/or correlational. Limited attention has focused on reducing or preventing burnout among these clinical professionals. 5 This limited evidence suggests a need for multivariable models to better understand factors consistently associated with BHP burnout, including relative strengths of associations between such characteristics relative to one another to inform targeted strategies to prevent and mitigate burnout.

Internal organizational policies, such as changing clinical requirements and productivity targets, and external stressors, such as external audits, can increase burnout. 6, 7 Increasing the number of qualified providers could decrease burnout. 8 The global pandemic due to the novel coronavirus disease (COVID- 19) likely exacerbated burnout among VHA BHPs as shown in recent studies of BHP experiences outside VHA. [9] [10] [11] We sought to identify potentially modifiable work-environment characteristics associated with BHP burnout in VHA, the largest integrated health care system in the United States. 12 With few exceptions, 13, 14 prior VHA studies on burnout have focused on other provider types, such as primary care physicians or all clinicians and/or conducted facility-level analyses that could not incorporate individuals' experiences in the workplace. [15] [16] [17] This study provided a unique opportunity to take advantage of rich individual-level data from two large annual national surveys that included BHPs: All Employee Survey (AES) 18 and Mental Health Provider Survey (MHPS). 19 We supplemented analyses with facility-level Mental Health Onboard Clinical (MHOC) staffing and productivity data, which identify and track provider productivity across settings, including mental health outpatient. [20] [21] [22] [23] Published findings of VHA surveys have tended to use facility-level data and thus could not address potentially modifiable individual-level work-environment characteristics associated with burnout. No prior study features this combination of empirical analysis of longitudinal data, multiple data sources, and characteristics potentially associated with BHP burnout in a large health system.

We hypothesized that unfavorable work-environment characteristics would be associated with higher levels of BHP burnout. This study's findings can inform policy and practice on how best for a large health system to identify and attempt to mitigate and address BHP burnout.

The present study comprises one component of a larger mixedmethods study assessing predictors and consequences of mental health provider burnout in VHA, which aims to understand barriers and facilitators to address this vexing and costly public health issue. 24 Work-environment characteristics from the two surveys comprised the following domains: organizational climate, high performing workplace, managing risk, workgroup perceptions, and supervisory behaviors in AES and timely access to mental health care, quality of mental health care, and collaborative mental health care in MHPS. These domains can be conceptualized as actions and behaviors (what we do), workplace climate (where we are), and employee attitudes (how we feel). 25 Given the strong overlap with burnout, we did not include items focused on overall job satisfaction. 19 For the present analyses, we used individual-level, de-identified data from AES and MHPS from 2015 to 2018 and conducted all analyses separately for AES and MHPS. Since participants provided anonymous responses, we could not link data by respondent over time within each survey or between the two surveys. For robust and consistent findings, we split data from AES and MHPS into year pairs (2015-2016, 2016-2017, 2017-2018 ; six models) and repeated the analyses for each set. We used the earlier year data to train the model (e.g., 2015) and tested the model in the later year (e.g., 2016) in every analysis. We used burnout as the outcome and potentially modifiable work-environment characteristics as predictors, controlling for employee demographic characteristics as covariates.

We obtained data and included respondents who self-identified as psychiatrists, psychologists, or social workers on the AES and included all respondents in the MHPS during 2015-2018. We obtained facility-level data on MHOC staffing and productivity data during the same period. The Institutional Review Board in the VA Ann Arbor Healthcare System approved this study.

The National Center for Organizational Development (NCOD) administers the AES to all VHA employees as an annual organizational census of workplace perceptions and satisfaction. Further information on creation of AES, its measures, and how they inform organizational developments in VHA appears elsewhere. 18 From its inception in 2001 through the present, AES data provide organizational feedback and lead to workplace improvement, published as best practices among large organization survey efforts. 26 All AES responses remain anonymous. During the study period, the average AES response rate among all employees reached 60%: 54% of psychiatrists, 66% of psychologists, and 67% of social workers responded.

The Office of Mental Health and Suicide Prevention (OMHSP) invites all VHA licensed and non-licensed independent mental health providers to complete the online MHPS annually to assess mental health provider perceptions about access to and quality of mental health care, and job satisfaction. 27 Analyses found MHPS data reliable, valid, and consistent. 19 The MHPS response rate during the study period exceeded 50%.

OMHSP developed a staffing model that estimates the number of full-time equivalent mental health staff per 1000 veterans treated in outpatient mental health settings, a population-based measure (staffing ratio). 21 MHOC includes an efficiency-based measure of provider productivity calculated as the sum of work relative value units divided by time spent providing direct clinical care in outpatient mental health settings (productivity). 20 

For both AES and MHPS surveys, we defined burnout as a dichotomous variable using a validated approach to define burnout for AES, 15 and sought a comparable interpretation for findings across the two surveys.

We classified whether respondents indicated experiencing burnout according to methods used by other VHA researchers. 15 This approach used two burnout questions: emotional exhaustion ("I feel burned out from my work") and depersonalization ("I worry that this job is hardening me emotionally"). Each of these two burnout questions had a seven-point response scale (1 = Never; 2 = A few times a year or less; 3 = Once a month or less; 4 = A few times a month; 5 = Once a week; 6 = A few times a week; 7 = Every day). We generated a dichotomous variable such that if the respondent answered either question with 5 or higher (once a week or higher frequency), we classified the response as endorsing burnout; otherwise, we classified the respondent as not endorsing burnout.

To test validity of the burnout variable cutoff, we compared it with another AES variable: turnover plans ("I plan to leave my job within the next six months"). Of various threshold values (e.g., ≥3, ≥4, ≥5, ≥6), we found the threshold value of ≥5 to have the highest Facility has effective programs for veterans sensitivity among thresholds with false positive rate less than 30%.

We found this variable highly correlated with burnout in every study year.

We generated a dichotomous variable to classify respondent burnout our analyses. We used VHA-provided documentation that grouped together questions with similar but not identical wording to preserve as many items as possible for our analyses. 28 All work-environment items appear in Table 1 and used a scale of 1-5, following either an agreement scale ("strongly disagree" to "strongly agree") or a feeling scale ("very poor" to "very good"), where higher scores reflect the preferred environment. For example, for the item "disputes or conflicts are resolved fairly," 1 corresponds to "strongly disagree," and 5 corresponds to "strongly agree."

Like the AES, we included 17 items that appeared in all four study years. MHPS questions appear in Table 1 and used a scale from 1 to 5 reflecting agreement, satisfaction, or frequency, with higher scores reflecting better, preferable conditions.

We used two facility-level variables (staffing ratio and productivity) in sensitivity analyses as possible predictors of the relationship between self-reported work-environment characteristics and burnout. Further details outlining the purpose-origins and definitions-of these two metrics appear elsewhere. 20 

We calculated the overall burnout rates and summarized the demographic characteristics (e.g., sex, race, VHA) for VHA BHPs over the study period separately for AES and for MHPS. To avoid multicollinearity across predictors, for each yearly survey, we first 

We conducted three sensitivity analyses. We combined all the 

Our study sample of AES and MHPS respondents without missing data included 57,397 respondents. Study cohorts for each survey and

year appear in Figure 1 . Stated another way, the more respondents felt that staffing vacancies did not affect patient care, the less likely they were to report burnout.

As in AES, compared with the five other work characteristics, having a reasonable workload had by far the strongest negative association with burnout across all years (AME: À0.11, 95% CIs:

À0.11, À0.11).

Work-environment characteristics that did not appear significantly associated with burnout in AES included performance recognition and ability to bring up difficult issues, and in MHPS included working at the highest level of licensure and planning improvements in patient access.

Noteworthy demographic characteristics (Table S2) consistently indicated in AES: higher burnout among those with 1-20 years of tenure compared with those with more than 20 years; in MHPS, consistently higher burnout appeared among those with less than 1 year of tenure compared with those with over 20 years. (Table 2 , VHA tenure, prior VHA training, licensed independent provider, type of mental health services provided, discipline, and BHIP member as fixed effects) as fixed effects, and facilities as random intercepts.

Interpretation: An AME associated with reasonable workload of À0.11 corresponds to an 11 percentage point reduction associated with a one unit increase in the reasonable workload item. MH, mental health; MHPS, Mental Health Provider Survey; VHA, Veterans Health Administration. X-axis: adjusted burnout average marginal effect; Y-axis: work-environment characteristics

In sensitivity analyses using pooled data, we found similar workenvironment characteristics as seen in the analyses across consecutive pairs of years to be associated with decreased or increased probability of burnout and found similar AUROC values and Brier scores on test sets. In the separate analyses that added the staffing ratio and productivity variables, neither of those two variables were significant predictors of burnout, nor did they notably change the magnitude or direction of other self-reported work-environment predictors.

In a large study of burnout among BHPs over time within an integrated health system, and one of the largest mental health systems nationally, we found several key components associated with burnout. At this time, our comment on these questions reflects a purely conceptual standpoint; we believe the job demands-resources model 46 offers a useful framework to examine relationships between workload and other work process aspects on one hand, and burnout on the other hand. Job demands represent a sum of psychological, physical, or emotional efforts required by the job. Job resources include aspects instrumental to accomplishing the job successfully, buffer the workers from job demands, or support personal and professional growth on the job. 46 This distinction between demands and resources remains critical: work's impact on the employee conceptually creates a difference between demands and resources, not the work itself. It follows that, for a demanding job motivate employees, a high level of resources must accompany it. 46 Motivating jobs (i.e., high demands and high resources) may be less likely to create burnout and more likely to create positive work outcomes, such as organizational commitment. 47 Jobs that cause strain, however, have both high demands and also lack necessary resources to buffer those demands. 46 Demanding work leads to employee burnout. 48 Workload may represent a job demand, which proves detrimental when not balanced by appropriate job resources. Importantly, job resources include not only objective and monetizable aspects, such as more equipment and staff, but also the intangible workplace climate aspects, such as coworker support, positive organizational climate, and teamwork. The latter has an important role in balancing high workload demands and reducing workplace burnout. We acknowledge that our models in this study could not account for all possible variables that could appear in a job demands-resources model.

This study will guide our future work. We will assess moderators of burnout and the potentially bidirectional relationship between burnout and turnover. Finally, we will compare VHA BHPs with other VHA providers to assess similarities and differences in relative strengths of associations between work-environment characteristics and burnout.

This large study of two national surveys in the VHA health system pointed to work-environment characteristics consistently associated with BHP burnout. Health systems and other stakeholders may wish to consider the relative opportunities and challenges associated with addressing factors associated with burnout to weigh the costs and benefits of organizational and structural approaches to ensuring employee engagement, well-being, and preventing costly turnover.

The VA Health Services Research and Development Service provided funding for this study (VA IIR 17-262; VA RCS 21-138).

https://orcid.org/0000-0001-8246-6864

What we know about burnout in VHA: quick facts. US Department of Veterans Affairs

Burnout among psychiatrists in the veterans health administration

VHA Office of Mental Health Operations. How does the facility's mental health staffing relate to other characteristics of the mental health treatment program?

Burnout in the mental health workforce: a review

Burnout in mental health services: a review of the problem and its remediation

Trends in burnout and related measures of organizational stress among leaders of Department of Veterans Affairs medical centers

Audit of VHA's efforts to improve Veterans' access to outpatient psychiatrists

Department of Veterans Affairs. Productivity and staffing in outpatient clinical encounters for mental health providers. Department of Veterans Affairs, Veterans Health Administration

COVID-related work changes, burnout, and turnover intentions in mental health providers: a moderated mediation analysis

Burnout: a risk factor amongst mental health professionals during COVID-19

Burnout and depression among psychiatry residents during COVID-19 pandemic

Extreme makeover: transformation of the veterans health care system

Examining burnout profiles in the Veterans Administration: All Employee Survey narrative comments

Predictors of job satisfaction and turnover intention in VHA mental health employees: a comparison between psychiatrists, psychologists, social workers, and mental health nurses

National burnout trends among physicians working in the Department of Veterans Affairs

Examining burnout profiles in relation to health and well-being in the veterans health administration employee population

Task delegation and burnout trade-offs among primary care providers and nurses in veterans affairs patient aligned care teams (VA PACTs)

Organization development in the Department of Veterans Affairs. The Praeger Handbook of Veteran's Health: History, Challenges, Issues, and Developments Volume IV: Future Directions in Veterans Healthcare

Measurement-based management of mental health quality and access in VHA: SAIL mental health domain

Investigation of population-based mental health staffing and efficiency-based mental health productivity using an information-theoretic approach

Mental health treatment quality, access, and satisfaction: optimizing staffing in an era of fiscal accountability

Mental health productivity monitoring in the veterans health administration: challenges and lessons learned

VHA Directive 1161, Productivity and staffing in clinical encounters for mental health providers

Predictors and consequences of veterans affairs mental health provider burnout: protocol for a mixed methods study

Department of Veterans Affairs All Employee Survey Federal Employee Viewpoint Survey Technical Report

Department of Veterans Affairs. 2017 VA All Employee Survey

Using organizational and clinical performance data to increase the value of mental health care

Department of Veterans Affairs. Crosswalk of VA All Employee Survey (AES) items by year. National Center for Organizational Development

The experience of patient aligned care team (PACT) members. Health Care Manag Rev

Innovating team-based outpatient mental health care in the veterans health administration: staff-perceived benefits and challenges to pilot implementation of the behavioral health interdisciplinary program (BHIP)

Log odds and the interpretation of logit models

Odds ratios-current best practice and use

Verification of forecasts expressed in terms of probability

Use of Brier score to assess binary predictions

The mediating relationship of self-awareness on supervisor burnout and workgroup civility & psychological safety: a multilevel path analysis

Evolving the JD-R model: the moderating effects of job resources and burnout taxonomies

Effects of 2-vs 4-week attending physician inpatient rotations on unplanned patient revisits, evaluations by trainees, and attending physician burnout: a randomized trial

Patient safety, resident well-being and continuity of care with different resident duty schedules in the intensive care unit: a randomized trial

The effects of work-hour limitations on resident well-being, patient care, and education in an internal medicine residency program

Comparison of burnout among medical residents before and after the implementation of work hours limits

Effects of the accreditation council for graduate medical education duty hour limits on sleep, work hours, and safety

Intervention to promote physician well-being, job satisfaction, and professionalism a randomized clinical trial

A randomized controlled trial to decrease job burnout in first-year internal medicine residents using a facilitated discussion group intervention

Reducing burnout in primary care: a step toward solutions

A cluster randomized trial of interventions to improve work conditions and clinician burnout in primary care: results from the healthy work place (HWP) study

The job demands-resources model: state of the art

Beyond the demandcontrol model

How changes in job demands and resources predict burnout, work engagement, and sickness absenteeism

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