MEASURING BURNOUT

As discussed in Chapter 2, burnout is a multi-dimensional construct that has been studied for nearly 50 years across various occupations (Maslach et al., 2001; Schaufeli et al., 2009). Thorough reviews of the psychometric properties of various instruments used to measure burnout and of the factors to consider in selecting the optimal instrument for local use have recently been published and are publicly available on the National Academy of Medicine's website.²

Briefly, Maslach's theoretical framework considers burnout to be a syndrome consisting of emotional exhaustion, depersonalization (also referred to as cynicism or disengagement), and a low sense of personal accomplishment from work that is driven largely by factors within the work environment. The Maslach Burnout Inventories (MBIs) (Maslach et al., 1996) are the most widely used measures of burnout (Schaufeli et al., 2009). Most of the studies included in this report used the MBI–Human Services Survey, Medical Professionals (MBI–HSS [MP]), which is widely considered the criterion standard, although some studies used the MBI–General Survey (MBI–GS), developed for use in other workers, or the MBI–Student Survey (MBI–SS), developed for use in learners. Other studies have used Oldenburg Burnout Inventory, the Copenhagen Burnout Inventory, or the Stanford Professional Fulfillment Index (Demerouti and Bakker, 2008; Dyrbye et al., 2018; Kristensen et al., 2005; Trockel et al., 2018). The Oldenburg Burnout Inventory evaluates physical, cognitive, and affective exhaustion and disengagement from work (Demerouti and Bakker, 2008). The Copenhagen Burnout Inventory evaluates personal work-related and client-related burnout (Kristensen et al., 2005). The Stanford Professional Fulfillment Index evaluates emotional exhaustion, interpersonal disengagement, and professional fulfillment (NAM, 2018; Trockel et al., 2018). Although single-item measures of burnout are frequently used, the ability of such items to measure the holistic construct of burnout are unclear, their validity data are less robust, and their use cannot be recommended at the present time.

The preferred analytical approach is to treat each dimension (e.g., emotional exhaustion, depersonalization), or sub-scale within the scale, separately as a continuous variable. However, low, average, and high cutoff scores for each sub-scale have been established for the MBI, and these are commonly used instead of continuous variables. Investigators often dichotomize into burnout/no burnout, but there is no accepted standard definition of where burnout begins (Dyrbye et al., 2009). A common approach is to consider individuals as having at least one symptom of burnout if they have high scores in either the emotional exhaustion (≥27) or the depersonalization (≥10) sub-scale of the MBI–HSS. Evidence indicates that high scores on these sub-scales can distinguish the clinically burned out from the non-burned out (Schaufeli et al., 2001), and this approach identifies individuals whose degree of burnout places them at an increased risk of potentially serious personal and professional consequences (Dyrbye et al., 2008, 2010; Shanafelt et al., 2002, 2011, 2016b; West et al., 2006, 2009b). Because there is evidence that higher scores in either the emotional exhaustion or depersonalization domain decrease the quality of care provided by clinicians, high degrees of burnout in either of these domains is cause for concern. An alternative option is to consider individuals to have burnout if they have a high emotional exhaustion score along with either a high depersonalization score or a low personal accomplishment score (Dyrbye et al., 2009) or else high scores in all three domains. There is no established approach to dichotomizing results from the Oldenburg Burnout Inventory or the Copenhagen Burnout Inventory, but threshold scores for dichotomizing results from the Stanford Professional Fulfillment Index have been published (Demerouti and Bakker, 2008; Dyrbye et al., 2018; Kristensen et al., 2005; Trockel et al., 2018).

As mentioned above, the data concerning the validity of various burnout measures have recently been summarized (Dyrbye et al., 2018; NAM, 2018). Briefly, the strongest construct validity data for the 22-item MBI–HSS (MP) are for U.S. physicians and other clinicians. An abbreviated two-item version of the MBI is available and has been shown to correlate strongly with the emotional exhaustion and depersonalization sub-domains of the full-length instrument (West et al., 2009a, 2012a), and there is strong evidence for its validity from large samples of U.S. physicians. There are less robust validity data available for the remaining measures, especially for use in U.S. physicians, nurses, and dentists.

The MBI, the Oldenburg Burnout Inventory, the Copenhagen Burnout Inventory, and the Stanford Professional Fulfillment Index instruments can be used across the health care professions broadly, including with physicians, nurses, advanced practice providers, social workers, and pharmacists. The MBI is proprietary, and individuals or organizations must pay a fee to use it for operational or research purposes. Both the Oldenburg Burnout Inventory and the Copenhagen Burnout Inventory are also proprietary, but they are free to use. The Stanford Professional Fulfillment Index is also available at no cost for use by not-for-profit organizations for research or operational assessment. These instruments are often embedded within anonymous surveys and can be part of a large survey assessing multiple dimensions of professional well-being.

It should be noted that, depending on the time interval being assessed, the various burnout instruments may not be equally sensitive to change. Items on the MBI are rated on a frequency scale with the low end of the continuum anchored by “never” and “a few times per year” and the more frequent end of the continuum anchored by “every day.” Although the MBI is largely designed to detect changes over intervals of at least 12 months, studies have effectively used it to evaluate changes over 6-month intervals (Panagioti et al., 2018; West et al., 2016). In contrast, the items in the Oldenburg Burnout Inventory are assessed on a four-point agreement scale with options ranging from “totally disagree” to “totally agree,” and items in the Copenhagen Burnout Inventory are rated on a frequency scale with options ranging from “never” to “always.” Accordingly, the time interval over which the Oldenburg and Copenhagen Burnout Inventories can be used to measure change may be imprecise, and less is known about their ability to detect meaningful effect size from an intervention. The Stanford Professional Fulfillment Index assesses symptoms over the past 2 weeks, and preliminary data suggest that it may be sensitive to change over short time intervals (Trockel et al., 2018).

There is substantial heterogeneity in the research methods employed by investigators studying burnout, including variability in the measures used to evaluate burnout symptoms and the approaches to dichotomizing burnout. Studies have also varied widely in sample size, the types of clinicians included (e.g., single occupation versus multiple health care disciplines), practice settings, participation rates, and adjustment for potential confounders (Rotenstein et al., 2018). Similar issues exist for other instruments used to subjectively measure aspects of well-being or mental and emotional health, including depression (Mata et al., 2015). These factors have created variability in the reported burnout prevalence. Nonetheless, the definition of burnout, its conceptual framework, and its links to personal and professional consequences are well established (Schaufeli et al., 2009).

PREVALENCE OF CLINICIAN BURNOUT

Numerous studies have evaluated the prevalence of clinician burnout by occupation, specialty, practice setting, career stage, and demographic characteristics. Among clinicians the most extensive data on prevalence comes from studies of physicians and nurses. Rates of burnout among U.S. nurses have typically ranged between 35 and 45 percent (Aiken et al., 2002, 2012; McHugh et al., 2011; Moss et al., 2016), although many studies have employed only the emotional exhaustion sub-scale of the MBI, resulting in an incomplete picture. In national studies of U.S. physicians using the MBI, rates of burnout have ranged from 40 to 54 percent over the past decade (Shanafelt et al., 2009a, 2012a, 2015, 2019). Limited national data are available on rates of burnout among U.S. nurse practitioners, physician assistants, and pharmacists, and many of these studies have not used standardized or validated instruments (Bell et al., 2002; Benson et al., 2016; Coplan et al., 2018; Hoff et al., 2019; Jones et al., 2017; Lahoz and Mason, 1990; Tetzlaff et al., 2018). Contemporary studies of the prevalence of burnout among U.S. dentists are limited; however, data from other countries suggest a substantial burden of burnout among dentists (e.g., Choy, 2015). Given that burnout is due to work-related stressors, the prevalence of burnout among clinicians would be expected to vary substantially among countries and health care delivery systems; thus, we have not included prevalence data from clinicians outside the United States.

Limited data are available on long-term trends in the prevalence of burnout among health care clinicians in the United States. National studies of U.S. physicians in 2011, 2014, and 2017 found a substantial increase in burnout between 2011 and 2014, with a subsequent improvement between 2014 and 2017 (Shanafelt et al., 2012a, 2015, 2019). When assessed using the MBI, 43.9 percent (2,147 of 4,893) of the physicians reported at least one symptom of burnout in 2017, compared with 54.4 percent (3,680 of 6,767) in 2014 and 45.5 percent (3,310 of 7,227) in 2011.

Extensive evidence also shows variation by practice setting and specialty within a given profession (Balch et al., 2011; Shanafelt et al., 2009a, 2012a, 2015, 2019). Among nurses, those practicing in hospitals or nursing homes appear to have higher rates of burnout than those in other practice settings (McHugh et al., 2011). Among physicians, individuals in private practice models appear to be at a roughly 30 percent higher risk for burnout than those in academic practice settings (Shanafelt et al., 2015, 2019). Wide variation in burnout exists by physician specialty, and many of the specialties at highest risk are those with substantial direct patient care responsibilities at the frontline of access to the health care delivery system, such as emergency medicine, family medicine, general internal medicine, and neurology (Balch et al., 2011; Busis et al., 2017; Shanafelt et al., 2009a, 2012a, 2015, 2019). The relationship between specialty area and burnout among nurses is less clear (Hooper et al., 2010).

A number of demographic factors also appear to relate to burnout. Studies both inside and outside of health care have found a greater risk of burnout among younger workers (Dyrbye et al., 2011; El-Ibiary et al., 2017; Kuerer et al., 2007; Lahoz and Mason, 1990; Poncet et al., 2007; Shanafelt et al., 2009a,b, 2012a, 2014a, 2015, 2016a). This is not due to a generational effect as it has been consistently observed from studies both inside and outside of health care workers over the past 20 to 30 years. Younger workers face a number of distinct challenges as they establish themselves in their career and deal with the complex interplay between personal and professional life as they begin relationships and care for children.

Studies also demonstrate that women are at increased risk for burnout relative to their male colleagues after adjusting for other personal and professional factors (El-Ibiary et al., 2017; Lahoz and Mason, 1990; Shanafelt et al., 2012a,b, 2014a, 2015, 2016a; Templeton et al., 2019). There also appear to be subtle differences in the way that burnout is manifest by gender, with burnout in women more likely to manifest as emotional exhaustion than in men and men more likely than women to experience depersonalization. Although these patterns have been observed at the population level, they are not absolute and must be considered to be a group-level generalization. Having children has also been shown to reduce the risk of burnout both inside and outside of the health professions, although the impact likely varies based on the age of the child (Dyrbye et al., 2011; El-Ibiary et al., 2017; Shanafelt et al., 2009a, 2014a). Life events such as a personal illness, an illness in a loved one, the birth of a child, or the death of a close loved one also are related to burnout risk (Dyrbye et al., 2006).

PERSONAL CONSEQUENCES OF BURNOUT

Burnout has a number of personal and professional repercussions. Studies from outside health care have demonstrated that individual workers experiencing burnout are at an increased risk for cardiovascular disease (Appels and Schouten, 1991; Toker et al., 2012; Toppinen-Tanner et al., 2009), as well as a host of other health consequences, including hypercholesterolemia, type 2 diabetes, coronary heart disease, hospitalization due to cardiovascular disorder, musculoskeletal pain, changes in pain experiences, prolonged fatigue, headaches, gastrointestinal issues, respiratory problems, and severe injuries (Salvagioni et al., 2017). Burnout was also found to be associated with shorter overall survival among individuals less than age 45 in a prospective cohort study of more than 7,000 individuals (Ahola et al., 2010) and with an increased risk of severe occupational injuries in a prospective cohort study of more than 10,000 workers who were followed for 8 years (Ahola et al., 2013). Other studies suggest that the increased risk of occupational injury extends to health care workers. For example, resident physicians with burnout are at increased risk for needle sticks, bodily fluid exposures, and motor vehicle accidents (West et al., 2012b).

Multiple studies have found a correlation between burnout and rates of depression (Maslach and Leiter, 2016). Although these two conditions frequently co-exist, not all individuals with symptoms of burnout experience depression, and not all individuals with depression are burned out (Maslach and Leiter, 2016). Prospective longitudinal studies suggest that burnout may predispose one to depression rather than the converse (Hakanen and Schaufeli, 2012).

Burnout may also contribute to the increased risk of suicide that exists among health care workers (Davidson et al., 2018; Feskanich et al., 2002; Hawton et al., 2011; Hem et al., 2005; Katz, 1983; Petersen and Burnett, 2008; Roberts et al., 2013; Schernhammer and Colditz, 2004; Stack, 2001). Cross-sectional studies of physicians have found burnout to be associated with a nearly 200 percent greater chance of suicidal ideation (Shanafelt et al., 2011). A dose–response relationship between burnout and suicidal ideation, independent of depression, has also been found in multiple studies (Dyrbye et al., 2008; Shanafelt et al., 2011; van der Heijden et al., 2008). Longitudinal studies also suggest that suicidal thoughts attenuate when burnout improves, providing some evidence of causality between burnout and suicidal thoughts (Dyrbye et al., 2008). Accordingly, occupational burnout may be one of the reasons for the increased rates of suicide observed in some health care occupations (Center et al., 2003). Other studies have found higher rates of problematic alcohol use among health care clinicians experiencing burnout (Balayssac et al., 2017; Jackson et al., 2016; Oreskovich et al., 2012, 2015; Pedersen et al., 2016; Sargent et al., 2004). Although the direction of effect is unknown, this association may be related to self-medicating as a means of coping with occupational distress.

Box

Connections Heal Patients and Clinicians.

EFFECTS OF BURNOUT ON TURNOVER AND CLINICAL WORK EFFORT

Those with burnout are more likely to be dissatisfied with their current job and to consider leaving. Multiple studies of physicians and nurses have demonstrated that burnout is associated with an increased likelihood of considering a change in position (Aiken et al., 2002; Fida et al., 2018; Pantenburg et al., 2016; Shanafelt et al., 2011, 2014b). Similarly, one study of nurse anesthetists in Europe reported a relationship between burnout and intent to leave the current job (Meeusen et al., 2011). Studies from the Cleveland Clinic, Stanford University, and the University of California, San Francisco, have found that physicians experiencing burnout are approximately twice as likely to actually depart the organization as non-burned-out colleagues (Hamidi et al., 2018; Willard-Grace et al., 2019; Windover et al., 2018). Turnover has a potentially large economic cost to organizations due both to the cost to recruit and replace individuals once they depart and also the lost revenue from caring for patients during the transition (Shanafelt et al., 2017). Health care clinicians with burnout may also be more likely to leave their profession altogether and pursue a non–health care–related career (Sinsky et al., 2017).

Even when clinicians with burnout stay in their current job, there are often adverse individual and organizational job consequences. Prospective longitudinal studies have demonstrated that individuals experiencing burnout are more likely to cut their professional work effort over the next 12 to 24 months (Shanafelt et al., 2016c). Burnout has also been associated with increased absenteeism (sick days) among nurses (Parker and Kulik, 1995). In other studies, individuals with burnout may show up for work but demonstrate sub-optimal performance even though present (so-called presenteeism) (Salvagioni et al., 2017). Collectively, the combination of all these factors has a major impact on the ability of health care organizations to maintain an adequate professional workforce. Burnout may also be decreasing the adequacy of the health care professional workforce precisely at a time when the nation is facing large shortages of some types of health care clinicians, particularly physicians (AAMC, 2017) and nurses (AACN, 2017). The effects of burnout on turnover and productivity also have a tremendous economic cost at the organization and societal levels. A recent estimate of the societal cost of turnover and reduced productivity due to burnout among the physicians in the United States was greater than $4 billion annually (Han et al., 2019). Although the societal cost of burnout in other health care clinicians has not, to the committee's knowledge, been modeled (due to the required underlying data being insufficient to do so accurately), it is no doubt substantial.

EFFECTS OF BURNOUT ON JOB PERFORMANCE AND QUALITY OF CARE

Extensive research across diverse occupations has demonstrated a link between burnout and job performance (Wright and Bonett, 1997). Studies of nurses have demonstrated a correlation between nurse burnout and supervisor ratings of nurse performance (Parker and Kulik, 1995). Other studies involving 198,500 employees across nearly 8,000 work units have demonstrated a relationship between engagement (the positive antithesis of burnout) at the work unit level and customer satisfaction, safety, and productivity (Harter et al., 2002).

Burnout among health care clinicians has also been shown to have potentially profound effects on quality of care. The data from health care are consistent with the broad body of organizational science across disciplines (Salvagioni et al., 2017; Schaufeli et al., 2009; Wright and Bonett, 1997). Studies of nurses have demonstrated a relationship between nurse burnout and nurse rating of the hospital's safety culture (Halbesleben et al., 2008) and quality of care (Poghosyan et al., 2010). The aggregate nurse burnout score at the hospital level has been shown to correlate with publicly reported hospital quality measures, such as surgical site and urinary-catheter-associated infection rates (Cimiotti et al., 2012). Similarly, emotional exhaustion among nurses has been found to increase the likelihood that patients will rate the hospital poorly, will not recommend the hospital for care, and will perceive their communication with nurses unfavorably (Aiken et al., 2012).

Multiple studies of physicians and nurses have demonstrated a relationship between burnout and perceived medical errors (Garrouste-Orgeas et al., 2015; Holden et al., 2011; Leiter and Spence Laschinger, 2006; Lu et al., 2015; Oskrochi et al., 2016; Shanafelt et al., 2002, 2010; Tawfik et al., 2018; West et al., 2006, 2009b; Williams et al., 2007). Except in egregious situations, it can be difficult to establish a link between individual provider actions (or inactions) and ultimate patient outcomes (Garrouste-Orgeas et al., 2015; Linzer et al., 2009; Panagioti et al., 2018). Nonetheless, multiple systematic reviews and meta-analyses have concluded that burnout affects quality of care in a variety of ways (Dewa et al., 2017; Panagioti et al., 2018; Salyers et al., 2017). For example, one meta-analysis of 47 studies (2002–2017) involving 42,473 physicians concluded that

physician burnout was associated with an increased risk of patient safety incidents (OR [odds ratio] 1.96; 95% CI [confidence interval] 1.59–2.40), poorer quality of care due to low professionalism (OR 2.31; 95% CI 1.87–2.40), and reduced patient satisfaction (OR 2.28; 95% CI 1.42–3.68). (Panagioti et al., 2018, p. E1)

A study in nursing homes found that nurses who were experiencing burnout (as measured by the emotional exhaustion sub-scale of the MBI) were five times more likely to omit necessary care (OR = 4.97; 95% CI = 2.56–9.66) (White et al., 2019).

Other studies have found strong links between burnout and unprofessional behavior leading to undesirable patient experiences (Windover et al., 2018). Burnout appears to erode communication between patients and clinicians. Burnout has also been associated with malpractice claims, which is another potential source of economic risk to the organization (Balch et al., 2011; McAbee et al., 2015; Oskrochi et al., 2016). It is possible that this increased risk may be related to sub-optimal communication and lower empathy among individuals with burnout. A dose–response relationship has been observed between burnout and validated scores that predict a physician's risk of future malpractice litigation, suggesting that individuals who are burned out are at increased risk for future litigation (Hamidi et al., 2018). Physicians with burnout are also less likely to espouse a commitment to direct patient care and clinical practice (Tak et al., 2017). Historical studies of satisfaction and distress broadly (as opposed to burnout specifically) have found a correlation with physicians' prescribing practices (Grol et al., 1985; Melville, 1980), which indicates a potential insidious effect of burnout on quality of care. Unfortunately, there are not yet any empirical studies examining the relationship between work-related stress or burnout and dentists' and pharmacists' clinical performance (Plessas et al., 2018).

One study looking at the aggregate level of burnout in all members of the health care team working on a given unit have found a correlation with the adjusted mortality rates of the patients cared for by that team of health care clinicians (Welp et al., 2015). Like many studies of burnout, the explanation for this association could be directional in either (or both) directions and may well be influenced by other unknown factors that may in fact be the driver of the association. For example, it is possible that a poorly resourced unit is bad both for the patients cared for on that unit and the clinicians for them.

Collectively, these effects on quality, patient satisfaction, and litigation risk can also have potential broad effects on health care organizations by affecting referrals, reputation in the community, reimbursement, and contracting. The associated economic costs from these dimensions compound the costs associated with turnover, productivity, quality, and patient satisfaction and further strengthen the business case for health care organizations to address this issue (Shanafelt et al., 2017).

KEY FINDINGS

Burnout is highly prevalent among health care clinicians and has important personal and professional consequences as well as negative effects on the organizations in which they work and on society as a whole. Personal consequences include occupational injury, detrimental alcohol use, and a risk of suicide. Professional consequences include effects on the quality of care, the patient experience, and patient outcomes. Burnout has clear and profound impacts on staffing, including absenteeism, presenteeism, reduced productivity, turnover, and clinicians leaving the profession. These aspects have not only a substantial impact on health care organizations but also profound consequences for the adequacy of the U.S. health care workforce. In addition to the potentially tragic consequences for patients and clinicians, there are substantial economic costs to society and health care organizations. In aggregate, the facts make a compelling case for action to address health care professional burnout at the organization and societal levels.

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