Defining the Problem: Clinician Burnout

Physician burnout is a major public health crisis (Jha et al., 2018). It is estimated that 300 – 400 physicians commit suicide every year (Center et al., 2003). Suicide rates among physicians are higher than the general population with rates of 1.41 and 2.27 for males and females, respectively (Schernhammer & Colditz, 2004). This is even more concerning for female physicians considering the suicide rates in the general population in males is more than four times that of females (Schernhammer & Colditz, 2004). Burnout can be characterized by three key dimensions: emotional exhaustion, depersonalization, and a lack of sense of personal accomplishment that is the result of work-related stress (Hauer, Waukau, & Welch, 2018; Lee, Seo, Hladkyj, Lovell, & Schwartzmann, 2013). With the advent and widespread adoption of electronic health records (EHRs) in the last decade, EHRs and health information technology (HIT) has been consistently identified as a major contributor to physician burnout (Gardner et al., 2018). Given our current trajectories and the promise of improved patient care, reduced healthcare costs, and overall improvement in healthcare quality, EHRs and HIT are likely here to stay (T. D. Shanafelt et al., 2016). The prevalence of physician burnout jeopardizes the triple aim to improve health care outcomes in the United States (Berwick, Nolan, & Whittington, 2008; Rathert, Williams, & Linhart, 2018). Physician burnout is inherently linked to each of these three aims, and thus, a call for improving the work conditions for our healthcare providers, and consequently, a fourth aim (i.e. the quadruple aim) is gaining traction (Rathert et al., 2018). Most importantly, physician burnout is getting worse. While it is currently estimated that half of all physicians experience burnout (Kumar, 2016), a recent survey in 2018 of US physicians estimated that 78% (up from 74% in 2016) of physicians had feelings of burnout (Merritt Hawkins, 2018). Lastly, burnout is not limited to physicians and transcends to all clinicians (Fred, Scheid, & Heart, 2018).

A literature search was conducted using pubmed for articles published in the last five years using two search strategies. The primary search was conducted using the following burnout keywords of “physician burnout” OR “clinician burnout” OR “provider burnout” OR “pharmacist burnout” OR “nurse burnout” OR “moral injury” in the article title and any of the following health information technology keywords in the article text: “health information technology” OR “health information systems” OR “electronic health records” OR “electronic medical records” OR “usability” OR “interoperability” OR “standards” OR “digital health”. This returned a total of 26 articles. The secondary search was conducted using the same burnout keywords from the primary search, but excluded all of the health information technology keywords. This returned a total of 308 articles. References from articles were scanned for further inclusion of additional articles. Articles that contained any of the following were included: causes of burnout, magnitude of the issue, policy initiatives, HIT, EHR, and possible solutions to burnout. A total of 20 articles were included for this paper. Three principle findings can be gleaned: 1) sparse literature for non-physician burnout, 2) literature were predominantly cross-sectional surveys, and 3) mixed conclusions on attribution of EHRs and HIT to burnout.

There were two primary areas of agreement within the literature: measurement of burnout and increased administrative burden. To effectively quantify burnout, the most commonly utilized and validated tool was the Maslach Burnout Inventory (Jager, Tutty, & Kao, 2017; Kumar, 2016; T. Shanafelt & Swensen, 2017). It is a 22-item survey and is considered the gold standard for measuring burnout (Kumar, 2016; Rathert et al., 2018). Increased administrative burden has also been consistently cited as a major predictor in burnout (Downing, Bates, & Longhurst, 2018). It is estimated that for every hour a physician spends with a patient an additional one to two hours will be required for documentation of clinical notes (Hauer et al., 2018). In fact, ever since the enactment of the Health Information Technology for Economic and Clinical Health (HITECH) Act, clinical notes in the US has doubled in length (Downing et al., 2018). Unfortunately, the movement towards value-based care through the Meaningful Use legislation has unintentionally created low-value documentation required for reimbursement (Downing et al., 2018). This is further illustrated when comparing the length of US clinical notes to other countries using the same EHR: they are four times as long (Downing et al., 2018; Sinsky et al., 2016).

While there has been a tremendous amount of literature that has been published in the last decade associating burnout and patient outcomes or burnout and EHRs (De Stefano et al., 2018; Fred et al., 2018; Hauer et al., 2018; Jha et al., 2018), there has also been studies that have refuted those associations (Bakken, 2019; Rathert et al., 2018; Zsenits, Alcantara, & Mayo, 2019). One of the most compelling arguments came from a systematic review that looked at the association between burnout and patient outcomes (Rathert et al., 2018). Their most surprising finding was that associations between burnout and patient outcomes came predominantly from studies that incorporated physician perception (Rathert et al., 2018). Studies that included the clinical chart, however, found no such relationship (Rathert et al., 2018). While this systematic review didn’t completely refute that there is no association, the authors did conclude that the relationship between burnout and patient outcomes may not be as overt as originally speculated (Rathert et al., 2018). Moreover, studies that have attempted to characterize the amount of burnout attributable directly to EHRs (Gardner et al., 2018) have also been directly refuted due to underlying methodological concerns (Zsenits et al., 2019). 

Evidence-based policy should be used to derive solutions in tackling the issue of clinician burnout. The lack of well-constructed, prospective studies is quite concerning (Rathert et al., 2018). Moreover, the number of cross-sectional studies that make up the bulk of the burnout literature further adds to the complexity as there are many temporal components to burnout that may be better evaluated in a longitudinal study (Rathert et al., 2018). Lastly, while studies on physician burnout are quite abundant, studies on non-physician clinicians are not.

Overall, physician burnout is a major public health issue. Given the widespread adoption of EHRs and HIT in our healthcare system and its presumed association with burnout and patient outcomes, solutions should be crafted to mitigate any EHR or HIT-related burnout. The lack of well-constructed and reliable studies associating burnout with patient outcomes, EHRs, and HIT, presents a major opportunity to assist the Office of the National Coordinator (ONC) for HIT as the finalize their legislation that addresses EHR and HIT-related burnout(The Office of the National Coordinator for Health Information Technology, 2018).

References

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