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Importance: Time on the electronic health record (EHR) is associated with burnout among physicians. Newer virtual scribe models, which enable support from either a real-time or asynchronous scribe, have the potential to reduce the burden of the EHR and EHR-related documentation., Objective: To characterize the association of use of virtual scribes with changes in physicians' EHR time and note and order composition and to identify the physician, scribe, and scribe response factors associated with changes in EHR time upon virtual scribe use., Design, Setting, and Participants: Retrospective, pre-post quality improvement study of 144 physicians across specialties who had used a scribe for at least 3 months from January 2020 to September 2022, were affiliated with Brigham and Women's Hospital and Massachusetts General Hospital, and cared for patients in the outpatient setting. Data were analyzed from November 2022 to January 2024., Exposure: Use of either a real-time or asynchronous virtual scribe., Main Outcomes: Total EHR time, time on notes, and pajama time (5:30 pm to 7:00 am on weekdays and nonscheduled weekends and holidays), all per appointment; proportion of the note written by the physician and team contribution to orders., Results: The main study sample included 144 unique physicians who had used a virtual scribe for at least 3 months in 152 unique scribe participation episodes (134 [88.2%] had used an asynchronous scribe service). Nearly two-thirds of the physicians (91 physicians [63.2%]) were female and more than half (86 physicians [59.7%]) were in primary care specialties. Use of a virtual scribe was associated with significant decreases in total EHR time per appointment (mean [SD] of 5.6 [16.4] minutes; P < .001) in the 3 months after vs the 3 months prior to scribe use. Scribe use was also associated with significant decreases in note time per appointment and pajama time per appointment (mean [SD] of 1.3 [3.3] minutes; P < .001 and 1.1 [4.0] minutes; P = .004). In a multivariable linear regression model, the following factors were associated with significant decreases in total EHR time per appointment with a scribe use at 3 months: practicing in a medical specialty (-7.8; 95% CI, -13.4 to -2.2 minutes), greater baseline EHR time per appointment (-0.3; 95% CI, -0.4 to -0.2 minutes per additional minute of baseline EHR time), and decrease in the percentage of the note contributed by the physician (-9.1; 95% CI, -17.3 to -0.8 minutes for every percentage point decrease)., Conclusions and Relevance: In 2 academic medical centers, use of virtual scribes was associated with significant decreases in total EHR time, time spent on notes, and pajama time, all per appointment. Virtual scribes may be particularly effective among medical specialists and those physicians with greater baseline EHR time.

Background: Physician departure causes considerable disruption for patients, colleagues, and staff. The cost of finding a new physician to replace the loss coupled with lost productivity as they build their practice can cost as much as $1 million per departure. Therefore, we sought to characterize drivers of departure from practice with the goal of informing retention efforts (with a special emphasis on the connection between electronic health record (EHR)-related stress and physician departure)., Methods: This qualitative study of semistructured interviews was conducted between October 2021 and April 2022 among 13 attending physicians who had voluntarily departed their position from 2018 to 2021 in a large multispecialty, productivity-based, ambulatory practice network in the Northeast with a 5% annual turnover rate to understand their reasons for departing practice., Results: Among the 13 participants, 8 were women (61.5%), 3 retired (23.1%), and 6 (46.2%) left for new positions. Major domains surrounding the decision to depart included current features of the health care delivery landscape, leadership/local practice culture, and personal considerations. Major factors within these domains included the EHR, compensation model, emphasis on metrics, leadership support, teamwork/staffing, burnout, and work-life integration., Conclusions: Opportunities for medical practices to prevent ambulatory physicians' turnover include: (1) addressing workflow by distributing responsibility across team members to better address patient expectations and documentation requirements, (2) ensuring adequate staffing across disciplines and roles, and (3) considering alternative care or payment models., Competing Interests: Conflict of interest: The authors have no conflicts of interest to disclose., (© Copyright by the American Board of Family Medicine.)

Physician turnover places a heavy burden on the healthcare industry, patients, physicians, and their families. Having a mechanism in place to identify physicians at risk for departure could help target appropriate interventions that prevent departure. We have collected physician characteristics, electronic health record (EHR) use patterns, and clinical productivity data from a large ambulatory based practice of non-teaching physicians to build a predictive model. We use several techniques to identify possible intervenable variables. Specifically, we used gradient boosted trees to predict the probability of a physician departing within an interval of 6 months. Several variables significantly contributed to predicting physician departure including tenure (time since hiring date), panel complexity, physician demand, physician age, inbox, and documentation time. These variables were identified by training, validating, and testing the model followed by computing SHAP (SHapley Additive exPlanation) values to investigate which variables influence the model's prediction the most. We found these top variables to have large interactions with other variables indicating their importance. Since these variables may be predictive of physician departure, they could prove useful to identify at risk physicians such who would benefit from targeted interventions., Competing Interests: The authors have declared that no competing interests exist., (Copyright: This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.)

Objective: The aim of this article is to compare the aims, measures, methods, limitations, and scope of studies that employ vendor-derived and investigator-derived measures of electronic health record (EHR) use, and to assess measure consistency across studies., Materials and Methods: We searched PubMed for articles published between July 2019 and December 2021 that employed measures of EHR use derived from EHR event logs. We coded the aims, measures, methods, limitations, and scope of each article and compared articles employing vendor-derived and investigator-derived measures., Results: One hundred and two articles met inclusion criteria; 40 employed vendor-derived measures, 61 employed investigator-derived measures, and 1 employed both. Studies employing vendor-derived measures were more likely than those employing investigator-derived measures to observe EHR use only in ambulatory settings (83% vs 48%, P = .002) and only by physicians or advanced practice providers (100% vs 54% of studies, P < .001). Studies employing vendor-derived measures were also more likely to measure durations of EHR use (P < .001 for 6 different activities), but definitions of measures such as time outside scheduled hours varied widely. Eight articles reported measure validation. The reported limitations of vendor-derived measures included measure transparency and availability for certain clinical settings and roles., Discussion: Vendor-derived measures are increasingly used to study EHR use, but only by certain clinical roles. Although poorly validated and variously defined, both vendor- and investigator-derived measures of EHR time are widely reported., Conclusion: The number of studies using event logs to observe EHR use continues to grow, but with inconsistent measure definitions and significant differences between studies that employ vendor-derived and investigator-derived measures., (© The Author(s) 2022. Published by Oxford University Press on behalf of the American Medical Informatics Association.)

Importance: Physician turnover takes a heavy toll on patients, physicians, and health care organizations. Survey research has established associations of electronic health record (EHR) use with professional burnout and reduction in professional effort, but these findings are subject to response fatigue and bias., Objective: To evaluate the association of physician productivity and EHR use patterns, as determined by vendor-derived EHR use data platforms, with physician turnover., Design, Setting, and Participants: This retrospective cohort study was conducted among nonteaching ambulatory physicians at a large ambulatory practice network based in New England. Data were collected from March 2018 to February 2020., Main Outcomes and Measures: Physician departure from the practice network; 4 time-based core measures of EHR use, normalized to 8 hours of scheduled clinical time; teamwork, percentage of a physician's orders that are placed by other members of the care team; and productivity measures of patient volume, intensity, and demand., Results: Among 335 physicians assessed for eligibility, 314 unique physicians (89.2%) were included in the analysis (123 [39%] women; 100 [32%] aged 45-54 years), with 5663 physician-months of data. The turnover rate was 5.1%/year (32 of 314 physicians). Physicians completed a mean 2.6 appointments/hour (95% CI, 2.5-2.6 appointments/hour) and 206 appointments/month (95% CI, 197-215 appointments/month) with 5.5 hours (95% CI, 5.3-5.8 hours) of EHR time for every 8 hours of scheduled patient time. After controlling for gender, medical specialty, and time, the following variables were associated with turnover: inbox time (odds ratio [OR], 0.70; 95% CI, 0.61-0.82; P < .001), teamwork (OR, 0.68; 95% CI, 0.52-0.87; P = .003), demand (ie, proportion of available appointments filled: OR, 0.49; 95% CI, 0.35-0.70; P < .001), and age 45 to 54 years vs 25 to 34 years (OR, 0.19; 95% CI, 0.04-0.93; P = .04)., Conclusions and Relevance: In this study, physician productivity and EHR use metrics were associated with physician departure. Prospectively tracking these metrics could identify physicians at high risk of departure who would benefit from early, team-based, targeted interventions. The counterintuitive finding that less time spent on the EHR (in particular inbox management) was associated with physician departure warrants further investigation.

Objective: To derive 7 proposed core electronic health record (EHR) use metrics across 2 healthcare systems with different EHR vendor product installations and examine factors associated with EHR time., Materials and Methods: A cross-sectional analysis of ambulatory physicians EHR use across the Yale-New Haven and MedStar Health systems was performed for August 2019 using 7 proposed core EHR use metrics normalized to 8 hours of patient scheduled time., Results: Five out of 7 proposed metrics could be measured in a population of nonteaching, exclusively ambulatory physicians. Among 573 physicians (Yale-New Haven N = 290, MedStar N = 283) in the analysis, median EHR-Time8 was 5.23 hours. Gender, additional clinical hours scheduled, and certain medical specialties were associated with EHR-Time8 after adjusting for age and health system on multivariable analysis. For every 8 hours of scheduled patient time, the model predicted these differences in EHR time (P < .001, unless otherwise indicated): female physicians +0.58 hours; each additional clinical hour scheduled per month -0.01 hours; practicing cardiology -1.30 hours; medical subspecialties -0.89 hours (except gastroenterology, P = .002); neurology/psychiatry -2.60 hours; obstetrics/gynecology -1.88 hours; pediatrics -1.05 hours (P = .001); sports/physical medicine and rehabilitation -3.25 hours; and surgical specialties -3.65 hours., Conclusions: For every 8 hours of scheduled patient time, ambulatory physicians spend more than 5 hours on the EHR. Physician gender, specialty, and number of clinical hours practicing are associated with differences in EHR time. While audit logs remain a powerful tool for understanding physician EHR use, additional transparency, granularity, and standardization of vendor-derived EHR use data definitions are still necessary to standardize EHR use measurement., (© The Author(s) 2021. Published by Oxford University Press on behalf of the American Medical Informatics Association.)

Objective: To describe and benchmark physician-perceived electronic health record (EHR) usability as defined by a standardized metric of technology usability and evaluate the association with professional burnout among physicians., Participants and Methods: This cross-sectional survey of US physicians from all specialty disciplines was conducted between October 12, 2017, and March 15, 2018, using the American Medical Association Physician Masterfile. Among the 30,456 invited physicians, 5197 (17.1%) completed surveys. A random 25% (n=1250) of respondents in the primary survey received a subsurvey evaluating EHR usability, and 870 (69.6%) completed it. EHR usability was assessed using the System Usability Scale (SUS; range 0-100). SUS scores were normalized to percentile rankings across more than 1300 previous studies from other industries. Burnout was measured using the Maslach Burnout Inventory., Results: Mean ± SD SUS score was 45.9±21.9. A score of 45.9 is in the bottom 9% of scores across previous studies and categorized in the "not acceptable" range or with a grade of F. On multivariate analysis adjusting for age, sex, medical specialty, practice setting, hours worked, and number of nights on call weekly, physician-rated EHR usability was independently associated with the odds of burnout with each 1 point more favorable SUS score associated with a 3% lower odds of burnout (odds ratio, 0.97; 95% CI, 0.97-0.98; P<.001)., Conclusion: The usability of current EHR systems received a grade of F by physician users when evaluated using a standardized metric of technology usability. A strong dose-response relationship between EHR usability and the odds of burnout was observed., (Copyright © 2019 Mayo Foundation for Medical Education and Research. Published by Elsevier Inc. All rights reserved.)

Objective: The aim of this study was to evaluate the association between physician and nurse self-reported empathy and burnout and the number of annual primary care visits per patient under their care., Methods: Design: A cross-sectional survey study was conducted from January 2013 to July 2014. Site: The 22 primary care centres of the Lleida Health Region in Spain., Main Outcome Measures: The Jefferson Scale of Physician Empathy and the Maslach Burnout Inventory were used to measure empathy and burnout, respectively. The number of visits and the number of diagnoses coded per visit were obtained through the Region's electronic health record., Results: Two hundred and sixty-seven healthcare professionals (physicians and nurses, 52.6% participation of the total in the region) with 301 657 patients under their care. Healthcare professionals' degree of burnout and empathy was associated with the number of annual visits per patient under their care. Burned out nurses and physicians received fewer visits (4.5vs3.7 in nurses and 18.1vs18.9 in physicians), whereas more empathic physicians received more visits per patient (19.4vs17.2, p<0.05) and documented more diagnoses per visit (10.2vs9.7, p=0.001). Less burned out and less empathic nurses documented more diagnoses per visit (10.2vs10.0 and 8.2vs9.9, p<0.05)., Conclusions: The number of annual primary care visits per patient that healthcare professionals receive is closely associated with healthcare professionals' empathy and burnout. These results should serve to promote empathic skills and establish organisational changes that promote efficiency in the practice and, in turn, reduce the degree of burnout of healthcare professionals., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2018. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Study Objective: The Open Payments program requires reporting of payments by medical product companies to teaching hospitals and licensed physicians. We seek to describe nonresearch, nonroyalty payments made to emergency physicians in the United States., Methods: We performed a descriptive analysis of the most recent Open Payments data released to the public by the Centers for Medicare & Medicaid Services covering the 2014 calendar year. We calculated the median payment, the total pay per physician, the types of payments, and the drugs and devices associated with payments to emergency physicians. For context, we also calculated total pay per physician and the percentage of active physicians receiving payments for all specialties., Results: There were 46,405 payments totaling $10,693,310 to 12,883 emergency physicians, representing 30% of active emergency physicians in 2013. The percentage of active physicians within a specialty who received a payment ranged from 14.6% in preventive medicine to 91% in orthopedic surgery. The median payment and median total pay to emergency physicians were $16 (interquartile range $12 to $68) and $44 (interquartile range $16 to $123), respectively. The majority of payments (83%) were less than $100. Food and beverage (86%) was the most frequent type of payment. The most common products associated with payments to emergency physicians were rivaroxaban, apixaban, ticagrelor, ceftaroline, canagliflozin, dabigatran, and alteplase., Conclusion: Nearly a third of emergency physicians received nonresearch, nonroyalty payments from industry in 2014. Most payments were of small monetary value and for activities related to the marketing of antithrombotic drugs., (Copyright © 2016 American College of Emergency Physicians. Published by Elsevier Inc. All rights reserved.)