Burnout Rate and Risk Factors among Anesthesiologists in the United States

This study was determined to be exempt by the institutional review boards of Memorial Sloan Kettering Cancer Center (New York, New York) and Boston Children’s Hospital (Boston, Massachusetts) in July 2019 and January 2020, respectively.

Invitations to participate with objectives of the study and a survey link were distributed by the ASA via email to all ASA member attending anesthesiologists in the United States. Participation was not mandatory, there were no incentives to participate, and all responses were anonymous. The initial email was sent on March 6, 2020, and was followed by two weekly reminders (March 14 and 21). A third reminder was planned for March 28, but this was canceled out of concern for the escalating COVID-19 pandemic and after ASA member feedback to the investigators raising concern for the overall email burden physicians were experiencing. The principal investigators did not believe it was ethical to continue to send reminder emails given the cognitive overload many individuals were beginning to experience during the initial phases of the pandemic.

Burnout was assessed using the validated Maslach Burnout Inventory Human Services Survey.⁵  Our additional survey questions focused on both personal and occupational risk factors for burnout. The study survey was designed on the basis of guidance from the American Association for Public Opinion Research (Lenexa, Kansas).^19–21  The demographic and practice information questions were developed primarily by the authors after performing a literature review and receiving input from the ASA Committee on Physician Well-being and approval from the ASA Executive Committee for distribution to the membership. Survey development and pretesting, which included online interface, usability, and technical functionality of the electronic questionnaire, were tested on a targeted group of approximately 15 professional colleagues. Intended survey logic was retained throughout with all responses obtained during this testing phase erased before survey distribution to the ASA membership and not included in statistical analysis. Participants were first asked via email to participate in the voluntary study, with explicit assurance of confidentiality; this email contained a link to the 35-question survey tool (appendix). Explicit consent was not required by either institution’s institutional review board for participation in this survey study. Questions were presented in a forced-response format, with optional demographic responses, without any incentives offered.

Participants were asked to provide information on demographic characteristics (including age, gender identity, inclusion in a vulnerable or underrepresented group, and English as a second language), primary practice environment, availability of a professional mentor at work, length of time since completion of training, recent staffing shortages at work, level of support in their professional and personal lives, and magnitude of caregiving responsibility at home.

The survey also included the full version of the Maslach Burnout Inventory Human Services Survey, which is the predominant metric for assessment of burnout among physicians.^1,22,23  The Maslach Burnout Inventory Human Services Survey uses 22 items to assess levels of three dimensions: emotional exhaustion (nine items), depersonalization (five items), and feelings of personal accomplishment (eight items). Each item is scored using a 7-level scale ranging from 0 to 6 (from never to every day), allowing for subscale assessment in all three dimensions.⁵  To facilitate potential comparisons to large previous studies of burnout in U.S. physicians, in a manner similar to these studies,^3,4,24  we considered a high score on emotional exhaustion (greater than or equal to 27) and/or depersonalization (greater than or equal to 10) to indicate a high risk of burnout.¹  Whereas the Maslach Burnout Inventory Human Services Survey assesses burnout over a continuum, to identify those with more significant degrees of burnout, we also classified the combination of a high score on emotional exhaustion and depersonalization and a low score on personal accomplishment (less than or equal to 33; i.e., all three dimensions present, using the same scoring thresholds as previously described for “high risk for burnout”) as burnout syndrome, consistent with definitions by the World Health Organization²⁵  and Maslach et al.⁵  Responses were automatically captured into SurveyMonkey without any participant identifiers for further analyses.

Descriptive statistics of responses are presented as frequencies and percentages (for categorical variables) and medians and interquartile ranges (for continuous variables). Missing data in the final analysis sample were negligible; denominators are presented to indicate instances of missing data. Burnout rates are presented as frequencies and percentages, and means and SDs are presented for each continuous subscale (emotional exhaustion, depersonalization, and personal accomplishment). Assessment of the generalizability of the study respondents was performed by comparing age, gender identity, and time since completion of training between the analysis sample and the overall ASA population. Age and time since training completion were modeled as outcome variables in two separate median regression models with group indicator (survey respondents vs. ASA population) as a covariate, and the coefficient and 95% CIs are reported to estimate the difference in medians with corresponding 95% CI.²⁰  Differences between proportions were calculated for gender identity using exact 95% CIs.

For statistical analysis, work support questions were considered in three categories (Not at all/A little, A moderate amount, A lot/A great deal), and other Likert scale questions were dichotomized as (Not at all/A little/A moderate amount vs. A lot/A great deal). Practice environment, gender identity, and caregiving responsibilities were coded as a categorical variable, age was dichotomized as younger than 50 yr, and all other variables were considered as dichotomous predictors.

Univariate comparisons were performed by comparing respondents with and without one manifestation of burnout (high score on the scales for emotional exhaustion and/or depersonalization) and by comparing respondents with and without burnout syndrome. Demographic and practice characteristics and support perceptions were analyzed using the Wilcoxon rank-sum test for continuous variables and the chi-square test for categorical variables. After univariate associations were determined for screening, all variables with P < 0.05 on univariate testing were included in the multivariable logistic regression modeling. A final multivariable model was fit after backwards elimination model building to obtain the adjusted associations between each potential risk factor and burnout, with the purpose of identifying independent risk factors associated with burnout. Results from multivariable modeling are presented as adjusted odds ratios with corresponding 95% CIs and P values. A post hoc supplemental analysis was performed to determine the significant risk factors for emotional exhaustion, depersonalization, and personal accomplishment, using univariate and multivariable linear regression modeling, with results presented as adjusted coefficients with 95% CIs and P values.

No statistical power calculation was conducted before the study, because the sample size was based on the number of complete survey responses. For all statistical analyses, a two-tailed P < 0.05 was considered to be statistically significant. All statistical analyses were performed using Stata (version 16.0, StataCorp, USA).

Of 28,677 anesthesiologists contacted via email, 4,147 (14.5%) opened the provided link and were considered to have participated. Of the survey respondents, 3,898 (94.0%) completed the survey in its entirety and were included in the statistical analyses, yielding an effective 13.6% response rate. We received 2,357 complete responses (60.5%) before March 14, 887 (22.8%) between March 14 and 20, and 654 (16.8%) after March 20, 2020. Only 19 responses (0.5%) were received after March 24. The survey link was officially closed on March 30.

Participant characteristics and rates of burnout are presented in table 1. The ASA provided the investigators with basic demographic data for the membership contemporaneous with the study period for the purpose of establishing how representative the study cohort was to the whole. The median age of respondents was 52 yr (interquartile range, 42 to 60 yr), compared with 48 yr (interquartile range, 40 to 58 yr) for the overall ASA population (difference, 4 yr; 95% CI, 3.2 to 4.8 yr). Of the respondents, 33.6% were women, compared with 29.2% of the ASA population (difference, 4.4%; 95% CI, 2.8 to 6%). The most common practice environments among respondents were hospital-based private practice (34%), community hospital (28%), and university hospital or academic appointment (26.2%). The median time since completion of training was 18 yr (interquartile range, 10 to 28 yr), compared with 14.8 yr (interquartile range, 7.8 to 25.8 yr) for the ASA population (difference, 3.2 yr; 95% CI, 2.7 to 3.8 yr). Of the respondents, 86.4% worked at least 40 h/week, 35.1% experienced staffing shortages, 46.6% felt little support in work-life, and 20.2% felt little support in home life. The majority of respondents had caregiving responsibilities of at least one person (85.4%). Respondents identified as underrepresented on the basis of race (10.2%); religion (4.9%); lesbian, gay, bisexual, transgender/transsexual, queer/questioning, intersex, and asexual status (2.7%); and English as a second language (6.1%).

On the basis of the Maslach Burnout Inventory Human Services Survey, the rate of high risk of burnout among anesthesiologists was 59.2% (2,307 of 3,898). Emotional exhaustion, depersonalization, and reduced feelings of personal accomplishment were experienced by 53.3%, 37.2%, and 25.9% of respondents, respectively. The mean ± SD scores in the cohort were 27 ± 13 for emotional exhaustion, 8 ± 6 for depersonalization, and 38 ± 8 for personal accomplishment. The rate of burnout syndrome was 13.8% (fig. 2). The rates of high risk for burnout were not significantly different across the three survey waves (59.8%, 59.9%, and 56%, respectively; P = 0.185), and neither were the rates of burnout syndrome (14.7%, 12.4%, and 12.5%, respectively; P = 0.135).

Results of the univariate analysis for high risk of burnout and burnout syndrome are presented in table 2. After univariate testing for screening of variables, multivariable logistic regression analyses were performed. After adjustment for all other variables in the model, the following were identified as independent risk factors for high risk of burnout: working more than 40 h/week (odds ratio, 2.22; 95% CI, 1.80 to 2.75; P < 0.001), experiencing staffing shortages (odds ratio, 2.06; 95% CI, 1.76 to 2.42; P < 0.001), perception of a low level of support in work-life (a lot or a great deal; not at all or a little support: odds ratio, 6.7; 95% CI, 5.3 to 8.5; P < 0.001; a moderate amount of support: odds ratio, 2.29; 95% CI, 1.85 to 2.83; P < 0.001), perception of a low level of support at home (a lot or a great deal; not at all or a little support: odds ratio, 1.77; 95% CI, 1.44 to 2.18; P < 0.001; a moderate amount of support: odds ratio, 1.37; 95% CI, 1.15 to 1.64; P < 0.001), not having someone to talk to about concerns at work (odds ratio, 1.56; 95% CI, 1.31 to 1.84; P < 0.001), age younger than 50 yr (odds ratio, 1.48; 95% CI, 1.27 to 1.72; P < 0.001), and identifying as underrepresented on the basis of lesbian, gay, bisexual, transgender/transsexual, queer/questioning, intersex, and asexual status (odds ratio, 2.21; 95% CI, 1.35 to 3.63; P = 0.002; fig. 3; Supplemental Digital Content 1 [https://links.lww.com/ALN/C560] and 2 [https://links.lww.com/ALN/C561]).

The following were identified as independent risk factors for burnout syndrome: hospital-based private practice environment (odds ratio, 1.88; 95% CI, 1.21 to 2.93; P = 0.005; private practice outpatient based), experiencing staffing shortages (odds ratio, 1.61; 95% CI, 1.32 to 1.96; P < 0.001), perception of a low level of support in work-life (a lot or a great deal; not at all or a little support: odds ratio, 10.0; 95% CI, 5.4 to 18.3; P < 0.001; a moderate amount of support: odds ratio, 3.63; 95% CI, 1.96 to 6.7; P < 0.001), perception of a low level of support at home (a lot or a great deal; not at all or a little support: odds ratio, 2.13; 95% CI, 1.69 to 2.69; P < 0.001; a moderate amount of support: odds ratio, 1.55; 95% CI, 1.22 to 1.97; P < 0.001), not having someone to talk to about concerns at work (odds ratio, 1.66; 95% CI, 1.26 to 2.37; P < 0.001), and age younger than 50 yr (odds ratio, 1.94; 95% CI, 1.59 to 2.37; P < 0.001; fig. 3, Supplemental Digital Content 1 [https://links.lww.com/ALN/C560] and 2 [https://links.lww.com/ALN/C561]). Supplemental multivariable linear regression analyses for each subscale (emotional exhaustion, depersonalization, and personal accomplishment) are summarized in Supplemental Digital Content 3 (https://links.lww.com/ALN/C562) and 4 (https://links.lww.com/ALN/C563), and 5 (https://links.lww.com/ALN/C564).

Our findings show that anesthesiologists are at high risk of burnout in the United States. Burnout is linked to decreased quality of care,²⁶  professionalism,²⁷  patient safety,⁸  and physician quality of life.²⁸  Shanafelt et al.¹  estimated that 45.8% of physicians are at risk of burnout, a high percentage that persists even after accounting for higher rates of resilience among physicians.²⁴  That study also found that the prevalence of burnout among anesthesiologists (48%), a small fraction of their sample (n = 309 [4.2%]), was higher than the mean. The higher rate of burnout in our study (59.2%) may be explained by differences in sample size, shifts in social climate, or increasing rates of burnout over time.

We also explored the rate of burnout syndrome, which we defined as the presence of all three dimensions of burnout, in accordance with the World Health Organization.²⁵  The presence of all three dimensions at once is less presented in the literature than “high risk for burnout.” However, given the reported rates of major morbidities in anesthesiology, such as substance use disorder and suicide, we felt it important to report.^29,30  The rate of burnout syndrome was predictably lower than that of burnout (13.8% vs. 59.2%), but burnout syndrome still affected a meaningful proportion of anesthesiologists in our dataset. Similar to the case for high risk for burnout, risk factors for burnout syndrome were strongly associated with workplace factors, especially perceived support of work-life. Age was the only personal factor that was significantly associated with burnout syndrome.

Although studies have analyzed burnout among trainees or attendings in anesthesia internationally,^13–16  they did not capture specific risk factors that are pervasive in the population of anesthesiologists. Sun et al.¹²  observed a rate of burnout of 52% among anesthesiology residents and first-year graduates that was unrelated to hours worked or student debt. However, our study suggests that workplace factors, rather than personal factors, are the primary factors associated with being at high risk for burnout among practicing anesthesiologists. In particular, lack of workplace support, working greater than or equal to 40 h/week, staffing shortages, and lack of a workplace confidant were all associated with burnout, which is consistent with recent data.³¹  Higher-risk characteristics of burnout in other studies included long work hours, excessive alcohol consumption, female gender identity, not being married, non-Hispanic White race, U.S. medical school graduate, younger age, poor learning environment, inadequate sleep quality, and lower income.^{7,17,18,32–34}  Although our analysis sample, as compared with ASA members, was slightly older and had a higher percentage of females, we do not feel that this small difference affected our prevalence of burnout. Many other studies did not find sex as an independent predictor of burnout, yet the prevalence of depersonalization and emotional exhaustion is higher among men and women, respectively.^31,34,35  In our study, contrary to previous investigations³⁶  but in line with the National Academy of Medicine consensus study,¹⁸  personal factors seemed to be of lower importance than workplace factors. These results hold true in sensitivity analyses within each of the individual subscales (emotional exhaustion, depersonalization, and personal accomplishment; Supplemental Digital Content 3 [https://links.lww.com/ALN/C562], 4 [https://links.lww.com/ALN/C563], and 5 [https://links.lww.com/ALN/C564]).

To date, groups that are underrepresented in medicine have not been as regularly measured in physician burnout studies. In their initial report on the Maslach Burnout Inventory Human Services Survey, Maslach and Jackson³⁷  noted that respondents who identified as being part of a racial minority did not have higher rates of burnout, and our results confirm this. Interestingly, we also found that anesthesiologists with English as a second language tended to have a lower risk of burnout, which echoes previous findings that international medical students had lower rates of burnout than U.S. medical graduates.³³  These findings highlight the importance of workplace factors, although it remains unclear why these populations have lower rates of burnout.

Among personal factors, lesbian, gay, bisexual, transgender/transsexual, queer/questioning, intersex, and asexual status had the strongest association with burnout in underrepresented participants. Because lesbian, gay, bisexual, transgender/transsexual, queer/questioning, intersex, and asexual people represent an increasing proportion of medical students and future physicians,³⁸  this finding warrants further investigation. Identifying as a sexual minority has been associated with greater psychologic distress in the workplace³⁹  and higher burnout.⁴⁰  In fact, Przedworski et al.⁴¹  investigated 4,673 medical students with self-reported sexual orientation data in a national longitudinal cohort study. Compared with heterosexual students, first-year sexual minority medical students (who identified as nonheterosexual) experience significantly greater risk of depression, anxiety, and low self-rated health. Another cohort study of 27,504 U.S. medical students showed that lesbian, gay, or bisexual students reported mistreatment and discrimination based on sexual orientation.⁴²  Members of this community may lack inherent familial support because they do not necessarily share their sexual or gender identity with their family of origin. Additionally, members of the lesbian, gay, bisexual, transgender/transsexual, queer/questioning, intersex, and asexual population may not be fully protected from workplace discrimination; this lack of protection may lead individuals to hide their lesbian, gay, bisexual, transgender/transsexual, queer/questioning, intersex, and asexual status, potentially amplifying the effect of workplace factors on burnout.

Our results suggest that feelings of support (in mentorship, at work, and at home) are the most critical factors in anesthesiologist well-being. Our results substantiate that lack of support in work-life contributed to anesthesiologist burnout and can provide a baseline assessment of anesthesiologist well-being and burnout. After quantifying the magnitude of different risk factors that contribute to burnout, we can intervene most effectively from the perspective of how to make anesthesiologists feel more support at work. Indeed, not feeling supported in work-life was strongly associated with high risk for burnout and even more strongly with burnout syndrome.

There are a number of effective strategies to reduce burnout, as demonstrated in a 2016 systematic review and meta-analysis of burnout reduction strategies, showing a burnout reduction from 54% to 44% in the intervention groups.⁴³  A recent publication describes interventions for well-being with descriptions of policy-level, institutional, and personal strategies to ameliorate burnout and improve physician well-being. With actionable recommendations that can be adopted by policy-makers (systematic destigmatizing of mental health care, educational debt reform, limiting discoverability of peer support), institutions (peer support programs, electronic health optimization, emphasis on mentorship), and physicians (mindfulness, stress reduction training, optimum nutrition, and physical activity), we can take practical steps toward decreasing burnout and improving overall well-being.⁴⁴ 

Workplace culture is directly linked to leadership,⁴⁵  in particular executive leadership.⁴⁶  However, all physicians assume leadership roles, whether in the operating room or at the department level, and therefore have an opportunity to foster a culture of support. We have shown that a culture of support is associated with a lower risk of burnout, and data suggest that burnout may have a negative effect on patient satisfaction and safety.^8,47  Put simply, leadership drives culture, culture drives burnout, and burnout affects patient care. Solutions focused on leadership skills, self-care, balance between demands and resources, and alignment in the working environment are likely to have downstream effects, multiplying investments made.²⁹ 

Multiple models of supportive cultures exist,^46,48  but, in essence, a culture of support must reach all aspects of life and practice, integrating principles of healthy well-being and care into each. The creation of such a culture should follow an iterative path, requiring repeated feedback from people at every organizational level. Care must be taken to ensure that giving feedback is safe, without fear of reprisal. After any changes, assessments must be made to ensure that the changes are effective—these assessments can be in the form of formal survey instruments, focus groups, or surrogate markers of engagement, such as employee retention or involvement in voluntary organizational activities. Mentorship meetings should incorporate both work and life factors into goal setting, taking care to strategize ways in which balance can be attained on an individual basis.

Finally, given the continued burden of depression, suicide, and substance use disorders in medicine and anesthesiology,^29,30  a goal of any well-being initiative should be to create a culture in which anyone who needs help, gets help, with no barriers attributable to stigma, fear of career impact, time constraints, or ability to pay. Institutions and leadership should ensure access to mental health resources. Seeking help must be seen as a laudable act of professionalism and the expected course when in need.

Our survey was disseminated in March 2020, just before the escalation of the COVID-19 pandemic in the United States. This pandemic has disproportionately affected anesthesiologists on the front line.⁴⁹  However, because of the timing of our responses, the pandemic likely had a minimal effect on the data. The pandemic began to escalate in the last week of March 2020 and did not initially peak in the United States until April 2020.⁵⁰  As noted, 83.3% and 99.5% of the responses to our surveys occurred before March 20 and 24, respectively. Therefore, the responses represent rates of burnout just before the pandemic and may not represent levels of burnout and stress currently. Our effective response rate was low at 13.6%, likely because of the increased email burden and the truncated schedule of email reminders. Given the volume of email communication experienced throughout March 2020 regarding the emerging COVID-19 pandemic, cognitive bandwidth to participate in extraneous tasks like voluntary survey studies was likely impacted. Even so, the response rate in this study is not much lower than those in recent large-scale studies of burnout, which were slightly more than 17%.^4,24  Other factors possibly contributed to the low response rate, such as survey fatigue or burnout itself. Furthermore, our sample being similar to the overall population of ASA member anesthesiologists suggests that our results are generalizable to the larger population. Finally, we used the complete Maslach Burnout Inventory Human Services Survey questionnaire, which contains 22 items; although use of a well-validated survey instrument is certainly not a limitation, the length limited the number of additional questions feasible to ask. Therefore, only select personal and practice factors could be queried, and additional risk factors, such as geographic location, were not collected.

Given the inherent stress of anesthesiology, burnout is not an unexpected occupational hazard. No clear trend of burnout rates over time has been established among anesthesiologists, although the landscape continues to evolve dynamically. In this large, national, survey-based study of anesthesiologists, the prevalence of high risk for burnout and burnout syndrome were high (59.2% and 13.8%, respectively). Burnout was primarily associated with workplace factors, particularly the lack of feeling supported in work-life. The high rates of high risk for burnout and burnout syndrome identified here demand attention in the form of well-designed interventions that factor in the drivers of burnout in this population. These factors include lack of support at work and home, long work hours, staffing shortages, and issues related to sexual and gender identity. These risk factors can be used to identify anesthesiologists at risk for burnout and to design initiatives to reduce the risk of burnout and manage existing burnout among anesthesiologists.

The authors acknowledge the American Society of Anesthesiologists (Schaumburg, Illinois) for study endorsement and distribution to the membership, as well as provision of general membership demographic data; the American Society of Anesthesiologists’ Committee on Physician Well-being, for study endorsement and general guidance on survey components; Julian Post, B.S., research assistant at Boston Children’s Hospital (Boston, Massachusetts), for assistance with the institutional review board; Christopher J. Kaeser, B.F.A., Strategy and Innovation, Memorial Sloan Kettering Cancer Center (New York, New York), for assistance with data visualization; and David B. Sewell, M.A., M.F.A., of the Department of Surgery, Memorial Sloan Kettering Cancer Center, for editorial assistance.

This study was supported, in part, by the National Institutes of Health/National Cancer Institute (Bethesda, Maryland) Cancer Support Grant P30 CA008748.

Dr. Afonso is a consultant for Pacira (Parsippany, New Jersey) and Merck (Kenilworth, New Jersey). The other authors declare no competing interests.