EHR and Physician Burnout

By Tristan Dooley 

Health organizations in the United States rapidly adopted Electronic Health Records (EHR) after the Health Information Technology for Economic and Clinical Health (HITECH) Act was passed as part of the American Recovery and Reinvestment Act of 2009 (National Academies, 2019). EHR is widely used, and as of 2017, almost all hospitals and about 80% of clinics were using EHR technologies (National Academies, 2019).  

EHR was intended to be more than just a replacement for paper charts. They were created to improve efficiency, interoperability, and the quality of patient care. The systematic nature of EHR was supposed to allow healthcare professionals to share patient information with other professionals in a timely matter to provide optimal care. EHR also allowed for better collection of data for large groups of people, which could be valuable for large-scale research. However, EHR has faced many criticisms after its widespread implementation.   

Poor interoperability, lack of standardization, and difficulty inputting and withdrawing data from charts are common criticisms of EHR (Matthews, 2019). Poor interoperability makes it more difficult to share patient information, and problems with interface and usability frustrate health professionals. Technology changes rapidly, meaning that what seems like recent EHR technology can quickly become outdated. Out-of-date technology and software create privacy concerns and may make the technology work slower, leading to increased frustration by providers and patients alike (Matthew, 2019).  

Burnout 

Burnout is a type of work-related stress that leads to physical or emotional exhaustion and involves a loss of personal identity and a reduced sense of accomplishment (Mayo Clinic Staff, 2021). Burnout significantly impacts healthcare workers, with more than half of U.S. physicians reporting at least one symptom of burnout (DeChant et al., 2019). Burnout also affects between 35%-54% of U.S. nurses and 45%-60% of medical students and residents (Poon et al., 2021).  

Burnout is problematic for patients and physicians. Physician burnout impacts the quality of patient care (DeChant et al., 2019). Burnout also impacts physician well-being and relationships. Burned-out physicians experience mental health issues, may abuse alcohol and drugs, and have suicide rates 1.2-2.4 times higher than the general population (DeChant et al., 2019). Physicians need better systemic support that addresses the causes of burnout to fix this problem.  

Burnout also has serious financial consequences. Researchers estimate that when a physician leaves a practice, the practice loses $500,000-$1,000,000 in revenue, and even more for high-paying specialties (Fred & Scheid, 2019). In the United States, it is estimated that approximately $4.6 billion in costs each year is attributable to physician burnout due to physician turnover and reduced productivity (Han et al., 2019). This is a significant amount of money that could be better spent improving the lives of healthcare workers and the quality of patient care.  

Burnout and EHR

A study by Tajirian et al. (2020) found that of respondents that reported having one or more symptoms of burnout, 74.5% identified EHR as a major contributing factor to their burnout. The study had a moderate sample size, which suggests more accurate survey results, as outliers have less influence on the data. While this study has strong support of EHR as a contributing factor to burnout, there are some limitations. The study was conducted at one mental health hospital, which means the participants live in one geographic area, use the same EHR system, and have similar specialties, making the study less generalizable. Additionally, the study did not measure individual EHR use and compare it to burnout as the study was done anonymously, so the data was compared to perceived EHR use and an average of actual hospital EHR use. This suggests that the perception of time spent on EHR could also be contributing to burnout as opposed to the actual time itself.  

Shanafelt et al. (2016) found that physicians who used EHR were at a higher risk of burnout regardless of their satisfaction with their EHR. This study had a high number of participants across various demographic backgrounds, specialties, and locations within the United States, so it has high generalizability. The survey used the Maslach Burnout Inventory, considered the gold standard for measuring burnout, indicating the survey has high validity. Despite a large number of participants, the survey had a low response rate, which may indicate bias. The study also did not delve into which parts of EHR were associated with burnout but looked at burnout and EHR more generally. 

Gardner et al. (2018) surveyed all practicing physicians in Rhode Island and found that physicians identified EHR as contributing to their burnout, with almost 70% of physicians who use EHR reporting technology-related stress. This suggests that the technology is adding stress but does not specify what parts of EHR are most stress-inducing. Additionally, they found that dissatisfaction with EHR is associated with intent for physicians to reduce their hours or leave their practice (Gardner et al., 2018). This study has good generalizability because participants worked in a variety of practice settings and had a variety of specialties and demographic characteristics. The study also used a highly validated burnout measure. One of the limitations is that this study was not anonymous, which may have impacted how physicians responded to the questions and suggests the survey underestimates burnout. 

Technological Aspects of EHR Associated with Burnout 

A few studies delved further to look at what technical aspects of EHR are associated with stress and burnout. One study found that the usability of technology and how it is incorporated into practices can contribute to clinician stress (Lovell, 2021). Implementing technology rapidly or during stressful times, such as COVID-19, significantly added to clinician’s stress (Lovell, 2021). Despite these findings, many clinicians in the study felt that better technology could reduce their workload and improve patient safety (Lovell, 2021). This suggests that implementing EHR without being given proper time or training to understand how to use it, or the poor usability that makes extra time and training necessary, adds to physician stress and eventually burnout. This study had a moderate to large sample size of physicians and nurses in numerous countries, increasing its generalizability. However, the initial survey was done online, which may skew results as those more familiar with technology may have been more likely to take the survey. 

Another study found that every one-point increase in EHR usability on a 100-point scale was associated with a 3% lower likelihood of physician burnout (O’Reilly, 2019). Overall, the physicians sampled gave EHR an F on the usability scale, with the average score being just 45.9 points out of 100 (O’Reilly, 2019). This study supports that the usability of EHR technology impacts burnout, and that the current usability is unacceptable. This study has good generalizability, with a large and diverse sample. It also used the Maslach Burnout Inventory to measure burnout, giving it good validity. One limitation of the study is that it did not look at the different EHR systems doctors used to see if different types or brands of EHR impacted results. 

Technology vs Administrative Load 

Some research suggests that the administrative and time burden of EHR may be associated with burnout. A study of 282 clinicians found that for every one minute spent with patients, physicians spent two minutes at the computer (Jason, 2019). This calls into question whether it is the technology itself that is causing burnout, or the amount of work required. In fact, clinicians within the study mentioned numerous benefits of EHR, such as added protection from medical malpractice, ease of billing, and ease of getting data for quality initiatives (Jason, 2019). The original research paper was not available, and therefore this report lacked information about participants and study methods that makes it difficult to estimate the generalizability, validity, and bias of the study. 

A study by Robertson et al. (2017) found that of the 37% of primary care physicians that reported burnout, 75% said EHR impacted their burnout some or a lot. Additionally, the study found that 85% of respondents said EHR impacted their work-life balance, and that work-life balance was significantly associated with burnout (Robertson et al., 2017). These findings suggest that the amount of time spent on EHR, which negatively impacts physician’s work-life balance, may be the cause of EHR-related burnout. The study had a high response rate and included over 500 respondents from multiple clinics. The high response rate suggests there is low non-response bias, and using multiple clinics means there is greater generalizability. However, the study only looked at primary care physicians within one portion of the United States, meaning the generalizability is still limited. Additionally, the survey asking about burnout and work-life balance was not officially tested for validity, giving the study less validity overall. 

Poon et al. (2021) reviewed numerous burnout studies to determine what parts of EHR and EHR-related factors impact burnout. They found that documentation requirements, high volume of inbox messages, and negative views of EHR functionality and usability were most consistently related to objective measures of burnout (Poon et al., 2021). The review suggests that there are both technological and administrative aspects of EHR that contribute to burnout. This review is a strong resource with low bias due to the high number of studies involved in the review. However, the authors of this study note that because technology and policy can both change so quickly, their impact on EHR and related burnout may also change rapidly, meaning that studies completed even within the last few years can become outdated compared to current clinic statuses.  

Interventions for Reducing EHR-Associated Burnout  

Collier (2018) reviewed numerous research studies to highlight technological interventions that can improve efficiency, reduce the workload, and reduce burnout for providers. Using voice-recognition software instead of keyboards with EHR reduced the time it took to finish charting patient encounters in half (Collier, 2018). There is also currently a project being done collaboratively with Google and Stanford Medicine where they are combining voice recognition with artificial intelligence to create a digital scribe that would listen to patient visits and automatically record relevant information into the EHR (Collier, 2018).  

While these are innovative ideas, these studies did not look at the large-scale implementation of these solutions. There are many questions surrounding these technologies, including when these technologies would be available, how many would be available, the time and cost of implementation, and more. It also draws a question about inequity due to cost. Will clinics and hospitals that care for a lot of Medicaid and Medicare patients be unable to access these technologies due to cost, putting their providers at higher risk of burnout and potentially impacting patient care?  

Mitek (2021) agrees that machine learning and artificial intelligence could be applied to EHR and other health technology now and in the near future. However, Mitek (2021) also offers other suggestions to improve current EHR technology, such as automating processes within the EHR, leveraging data management software to keep information concise and accessible, and using cloud hosting to store data and increase interoperability across the organization. These suggestions are more feasible to do presently but require capable Information Technology personnel and may bring up privacy concerns about using the cloud to store data.  

Subaiya & Hagerman (2020) suggest multiple technological interventions to reduce burnout for nurses, such as online diagnostics and symptom checkers, virtual nurses, and voice recognition and automation for data entry. These technological interventions are specific and go beyond broad suggestions of using artificial intelligence or machine learning tools. These suggestions are also unique in that they look to reduce burnout for nurses, while most studies focus on physicians. However, the authors are both senior leaders for health technology companies, which means they may have pro-technology bias. Also, they do not discuss if these technologies are currently available or still being tested, and do not discuss the cost. Interventions like these are promising, but without more information it is hard to determine the feasibility of implementing these solutions into health organizations over the next few years.  

Wood et al. (2017) tested a provider resilience app for phones and found that after using the app, providers showed a significant decrease in burnout and compassion fatigue. This study is promising for showing how everyday technological innovations can reduce burnout. The researchers tested the technology with providers, and because it is a phone app, this intervention is low cost and easy to implement once more research has been done. The study made sure that all measures used within their research were highly valid to improve the validity of the study. The study is limited because of the small sample size and lack of a control group, as the results were taken by the same providers before and after using the app. Despite these limitations, the study promisingly provides an intervention that could be widely implemented in the very near future.  

Why This Needs to be Addressed Now 

Healthcare burnout needs to be prioritized from a healthcare administration perspective. Provider burnout negatively impacts provider safety and well-being. Physician burnout also has tremendous financial costs. In addition to these issues, another reason burnout needs to be addressed is the current and projected healthcare worker shortage. In the United States alone, it is projected that by 2033 there will be a physician shortage of between 54,100 and 139,000 physicians (Boyle, 2020). These projections were estimated prior to the pandemic  

Burnout can cause physicians and other healthcare workers to leave medicine, and the pandemic has only exacerbated this. One survey found that 62% of healthcare workers reported that stress from COVID-19 had a negative impact on their mental health (Clement et al., 2021). This negative impact on mental health is causing healthcare workers to rethink their careers. Results from a Washington Post-Kaiser Family Foundation poll showed that almost 30% of healthcare workers are considering leaving healthcare from pandemic-related burnout (Wan, 2021). This increase in stress and burnout may significantly exacerbate the healthcare worker shortage and delay necessary care.  

EHR is widely adopted throughout the United States, and its association with burnout has been well-supported. While the true cause of EHR-associated burnout is still inconclusive, EHR needs to be improved to help reduce physician burnout and keep physicians healthy and practicing. If burnout is not addressed, the ramifications could impact healthcare systems and population health for decades to come.  

**This post was modified from the author’s original school paper** 

References 

Boyle, P. (2020, June 26). U.S. physician shortage growing. AAMC. https://www.aamc.org/news-insights/us-physician-shortage-growing.  

Clement, S., Pascual, C., & Ulmanu, M. (2021, April 6). Stress on the front lines of covid-19. The Washington Post. https://www.washingtonpost.com/health/2021/04/06/stress-front-lines-health-care-workers-share-hardest-parts-working-during-pandemic/. 

Collier, R. (2018). Rethinking EHR interfaces to reduce click fatigue and physician burnout. Canadian Medical Association Journal, 190(33). https://doi.org/10.1503/cmaj.109-5644 

DeChant, P. F., Acs, A., Rhee, K. B., Boulanger, T. S., Snowdon, J. L., Tutty, M. A., Sinsky, C. A., & Thomas Craig, K. J. (2019). Effect of Organization-Directed Workplace Interventions on Physician Burnout: A Systematic Review. Mayo Clinic Proceedings: Innovations, Quality & Outcomes, 3(4), 384–408. https://doi.org/10.1016/j.mayocpiqo.2019.07.006 

Fred, H. L., & Scheid, M. S. (2018). Physician Burnout: Causes, Consequences, and (?) Cures. Texas Heart Institute Journal, 45(4), 198–202. https://doi.org/10.14503/thij-18-6842 

Gardner, R. L., Cooper, E., Haskell, J., Harris, D. A., Poplau, S., Kroth, P. J., & Linzer, M. (2018). Physician stress and burnout: the impact of health information technology. Journal of the American Medical Informatics Association, 26(2), 106–114. https://doi.org/10.1093/jamia/ocy145 

Han, S., Shanafelt, T. D., Sinsky, C. A., Awad, K. M., Dyrbye, L. N., Fiscus, L. C., Trockel, M., & Goh, J. (2019). Estimating the Attributable Cost of Physician Burnout in the United States. Annals of Internal Medicine, 170(11), 784. https://doi.org/10.7326/m18-1422 

Jason, C. (2019, September 26). Study Shows Physician Burnout Directly Related to EHRs. EHRIntelligence. https://ehrintelligence.com/news/study-shows-physician-burnout-directly-related-to-ehrs. 

Lovell, T. (2021, May 19). Technology must meet clinician needs to manage burnout. Healthcare IT News. https://www.healthcareitnews.com/news/emea/technology-must-meet-clinician-needs-manage-burnout. 

Matthews, K. (2019, December 19). 6 Challenges Tech Has Brought To Healthcare (And How To Avoid Them). Health IT Outcomes. https://www.healthitoutcomes.com/doc/challenges-tech-has-brought-to-healthcare-and-how-to-avoid-them-0001. 

Mayo Clinic Staff. (2021, June 5). Know the signs of job burnout. Mayo Clinic. https://www.mayoclinic.org/healthy-lifestyle/adult-health/in-depth/burnout/art-20046642.  

Mitek, A. (2021, May 5). Tech innovation can mitigate physician burnout. Medical Economics. https://www.medicaleconomics.com/view/tech-innovation-can-mitigate-physician-burnout. 

National Academies of Sciences, Engineering, and Medicine; National Academy of Medicine; Committee on Systems Approaches to Improve Patient Care by Supporting Clinician Well-Being. (2019). Health Information Technology. In Taking action against clinician burnout: a systems approach to professional well-being. essay, The National Academies Press. 

O'Reilly, K. B. (2019, November 14). New research links hard-to-use EHRs and physician burnout. American Medical Association. https://www.ama-assn.org/practice-management/digital/new-research-links-hard-use-ehrs-and-physician-burnout. 

Poon, E. G., Rosenbloom, S. T., & Zheng, K. (2021). Health information technology and clinician burnout: Current understanding, emerging solutions, and future directions. Journal of the American Medical Informatics Association, 28(5), 895–898. https://doi.org/10.1093/jamia/ocab058 

Robertson, S. L., Robinson, M. D., & Reid, A. (2017). Electronic Health Record Effects on Work-Life Balance and Burnout Within the I3 Population Collaborative. Journal of Graduate Medical Education, 9(4), 479–484. https://doi.org/10.4300/jgme-d-16-00123.1 

Shanafelt, T. D., Dyrbye, L. N., Sinsky, C., Hasan, O., Satele, D., Sloan, J., & West, C. P. (2016). Relationship Between Clerical Burden and Characteristics of the Electronic Environment With Physician Burnout and Professional Satisfaction. Mayo Clinic Proceedings, 91(7), 836–848. https://doi.org/10.1016/j.mayocp.2016.05.007 

Subaiya, I., & Hagerman, E. (2020, April 7). Alleviating Nurse Burnout with Digital Health Tools. HIMSS. https://www.himss.org/resources/alleviating-nurse-burnout-digital-health-tools. 

Tajirian, T., Stergiopoulos, V., Strudwick, G., Sequeira, L., Sanches, M., Kemp, J., Ramamoorthi, K., Zhang, T., & Jankowicz, D. (2020). The Influence of Electronic Health Record Use on Physician Burnout: Cross-Sectional Survey. Journal of Medical Internet Research, 22(7). https://doi.org/10.2196/19274 

Wan, W. (2021, April 23). Burned out by the pandemic, 3 in 10 health-care workers consider leaving the profession. The Washington Post. https://www.washingtonpost.com/health/2021/04/22/health-workers-covid-quit/. 

Wood, A. E., Prins, A., Bush, N. E., Hsia, J. F., Bourn, L. E., Earley, M. D., Walser, R. D., & Ruzek, J. (2017). Reduction of Burnout in Mental Health Care Providers Using the Provider Resilience Mobile Application. Community Mental Health Journal, 53(4), 452–459. https://doi.org/10.1007/s10597-016-0076-5