Appl Clin Inform 2022; 13(04): 785-793
DOI: 10.1055/a-1877-2745
Research Article

Physician Electronic Health Record Usage as Affected by the COVID-19 Pandemic

Elise Ruan
1   Department of Medicine, Albert Einstein College of Medicine/Montefiore Medical Center, Bronx, New York, United States
,
Moshe Beiser
1   Department of Medicine, Albert Einstein College of Medicine/Montefiore Medical Center, Bronx, New York, United States
,
Vivian Lu
1   Department of Medicine, Albert Einstein College of Medicine/Montefiore Medical Center, Bronx, New York, United States
,
Soaptarshi Paul
1   Department of Medicine, Albert Einstein College of Medicine/Montefiore Medical Center, Bronx, New York, United States
,
Jason Ni
1   Department of Medicine, Albert Einstein College of Medicine/Montefiore Medical Center, Bronx, New York, United States
,
Nijas Nazar
1   Department of Medicine, Albert Einstein College of Medicine/Montefiore Medical Center, Bronx, New York, United States
,
Jianyou Liu
2   Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, New York, United States
,
Mimi Kim
2   Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, New York, United States
,
Eric Epstein
1   Department of Medicine, Albert Einstein College of Medicine/Montefiore Medical Center, Bronx, New York, United States
,
Marla Keller
1   Department of Medicine, Albert Einstein College of Medicine/Montefiore Medical Center, Bronx, New York, United States
3   Division of Infectious Disease, Albert Einstein College of Medicine, Montefiore Medical Center, Bronx, New York, United States
,
Elizabeth Kitsis
1   Department of Medicine, Albert Einstein College of Medicine/Montefiore Medical Center, Bronx, New York, United States
4   Division of Rheumatology, Albert Einstein College of Medicine, Montefiore Medical Center, Bronx, New York, United States
,
Yaron Tomer
1   Department of Medicine, Albert Einstein College of Medicine/Montefiore Medical Center, Bronx, New York, United States
,
Sunit P. Jariwala
1   Department of Medicine, Albert Einstein College of Medicine/Montefiore Medical Center, Bronx, New York, United States
5   Division of Allergy/Immunology, Albert Einstein College of Medicine, Montefiore Medical Center, Bronx, New York, United States
› Author Affiliations
Funding None.

Abstract

Objectives To utilize metrics from physician action logs to analyze volume, physician efficiency and burden as impacted by telemedicine implementation during the COVID-19 (coronavirus disease 2019) pandemic, and physician characteristics such as gender, years since graduation, and specialty category.

Methods We selected 11 metrics from Epic Signal, a functionality of the Epic electronic health record (EHR). Metrics measuring time spent in the EHR outside working hours were used as a correlate for burden. We performed an analysis of these metrics among active physicians at our institution across three time periods—prepandemic and telehealth implementation (August 2019), postimplementation of telehealth (May 2020), and follow-up (July 2020)—and correlated them with physician characteristics.

Results Analysis of 495 physicians showed that after the start of the pandemic, physicians overall had fewer appointments per day, higher same day visit closure rates, and spent less time writing notes in the EHR outside 7 a.m. to 7 p.m. on patient scheduled days. Across all three time periods, male physicians had better EHR-defined “efficiency” measures and spent less time in the EHR outside working hours. Years since graduation only had modest associations with higher same day visit closure rates and appointments per day in May 2020. Specialty category was significantly associated with appointments per day and same day closure visit rates and also was a significant factor in the observed changes seen across the three time periods.

Conclusion Utilizing EHR-generated reports may provide a scalable and nonintrusive way to monitor trends in physician usage and experience to help guide health systems in increasing productivity and reducing burnout.



Publication History

Received: 02 March 2022

Accepted: 12 June 2022

Accepted Manuscript online:
15 June 2022

Article published online:
25 August 2022

© 2022. Thieme. All rights reserved.

Georg Thieme Verlag KG
Rüdigerstraße 14, 70469 Stuttgart, Germany

 
  • References

  • 1 Chatterji P, Li Y. Effects of the COVID-19 pandemic on outpatient providers in the United States. Med Care 2021; 59 (01) 58-61
  • 2 Watts KL, Abraham N. “Virtually Perfect” for some but perhaps not for all: launching telemedicine in the bronx during the COVID-19 pandemic. J Urol 2020; 204 (05) 903-904
  • 3 Beiser M, Lu V, Paul S. et al. Electronic health record usage patterns: assessing telemedicine's impact on the provider experience during the COVID-19 pandemic. Telemed J E Health 2021; 27 (08) 934-938
  • 4 Baptista S, Teixeira A, Castro L. et al. Physician burnout in primary care during the COVID-19 pandemic: a cross-sectional study in Portugal. J Prim Care Community Health 2021;12:21501327211008437
  • 5 Amanullah S, Ramesh Shankar R. The impact of COVID-19 on physician burnout globally: a review. Healthcare (Basel) 2020; 8 (04) 421
  • 6 Linzer M, Stillman M, Brown R. et al; American Medical Association–Hennepin Healthcare System Coping With COVID Investigators. Preliminary report: US physician stress during the early days of the COVID-19 pandemic. Mayo Clin Proc Innov Qual Outcomes 2021; 5 (01) 127-136
  • 7 Shanafelt TD, West CP, Sinsky C. et al. Changes in burnout and satisfaction with work-life integration in physicians and the general us working population between 2011 and 2020. Mayo Clin Proc 2022; 97 (03) 491-506
  • 8 Nath B, Williams B, Jeffery MM. et al. Trends in electronic health record inbox messaging during the COVID-19 pandemic in an ambulatory practice network in New England. JAMA Netw Open 2021; 4 (10) e2131490
  • 9 Moore C, Valenti A, Robinson E, Perkins R. Using log data to measure provider EHR activity at a cancer center during rapid telemedicine deployment. Appl Clin Inform 2021; 12 (03) 629-636
  • 10 Jeppson K. What can Epic's signal data tell us about EHR satisfaction and burnout. KLAS Impact Report; 2020. Accessed July 1, 2022 at: https://klasresearch.com/archcollaborative/report/what-can-epics-signal-data-tell-us-about-ehr-satisfaction-and-burnout/324
  • 11 Livingston K, Bovi J. Department-focused electronic health record thrive training. JAMIA Open 2022; 5 (02) c025
  • 12 Khairat S, Zalla L, Gartland A, Seashore C. Association between proficiency and efficiency in electronic health records among pediatricians at a major academic health system. Front Digit Health 2021; 3: 689646
  • 13 Hollister-Meadows L, Richesson RL, De Gagne J, Rawlins N. Association between evidence-based training and clinician proficiency in electronic health record use. J Am Med Inform Assoc 2021; 28 (04) 824-831
  • 14 Gardner RL, Cooper E, Haskell J. et al. Physician stress and burnout: the impact of health information technology. J Am Med Inform Assoc 2019; 26 (02) 106-114
  • 15 Eschenroeder HC, Manzione LC, Adler-Milstein J. et al. Associations of physician burnout with organizational electronic health record support and after-hours charting. J Am Med Inform Assoc 2021; 28 (05) 960-966
  • 16 Robertson SL, Robinson MD, Reid A. Electronic health record effects on work-life balance and burnout within the I3 Population Collaborative. J Grad Med Educ 2017; 9 (04) 479-484
  • 17 Adler-Milstein J, Zhao W, Willard-Grace R, Knox M, Grumbach K. Electronic health records and burnout: time spent on the electronic health record after hours and message volume associated with exhaustion but not with cynicism among primary care clinicians. J Am Med Inform Assoc 2020; 27 (04) 531-538
  • 18 Woolson RF. Wilcoxon signed-rank test. In: D'Agostino RB, Sullivan L, Massaro J. eds. Wiley Encyclopedia of Clinical Trials. Hoboken, NJ: Wiley; 2008. . Accessed July 1, 2022 at: https://doi.org/10.1002/9780471462422.eoct979
  • 19 Hazra A, Gogtay N. Biostatistics Series Module 3: comparing groups: numerical variables. Indian J Dermatol 2016; 61 (03) 251-260
  • 20 Bishara AJ, Hittner JB. Testing the significance of a correlation with nonnormal data: comparison of Pearson, Spearman, transformation, and resampling approaches. Psychol Methods 2012; 17 (03) 399-417
  • 21 Koh D, Lim MK, Chia SE. et al. Risk perception and impact of severe acute respiratory syndrome (SARS) on work and personal lives of healthcare workers in Singapore: what can we learn?. Med Care 2005; 43 (07) 676-682
  • 22 Wu Y, Wang J, Luo C. et al. A comparison of burnout frequency among oncology physicians and nurses working on the frontline and usual wards during the COVID-19 epidemic in Wuhan, China. J Pain Symptom Manage 2020; 60 (01) e60-e65
  • 23 Giusti EM, Pedroli E, D'Aniello GE. et al. The psychological impact of the COVID-19 outbreak on health professionals: a cross-sectional study. Front Psychol 2020; 11: 1684
  • 24 Melnick ER, Ong SY, Fong A. et al. Characterizing physician EHR use with vendor derived data: a feasibility study and cross-sectional analysis. J Am Med Inform Assoc 2021; 28 (07) 1383-1392
  • 25 Patel SY, Mehrotra A, Huskamp HA, Uscher-Pines L, Ganguli I, Barnett ML. Trends in outpatient care delivery and telemedicine during the COVID-19 pandemic in the US. JAMA Intern Med 2021; 181 (03) 388-391
  • 26 Williams DC, Warren RW, Ebeling M, Andrews AL, Teufel Ii RJ. Physician use of electronic health records: survey study assessing factors associated with provider reported satisfaction and perceived patient impact. JMIR Med Inform 2019; 7 (02) e10949
  • 27 McPeek-Hinz E, Boazak M, Sexton JB. et al. Clinician burnout associated with sex, clinician type, work culture, and use of electronic health records. JAMA Netw Open 2021; 4 (04) e215686
  • 28 Kaufman M. Telehealth visits dip as New Yorkers return to doctors' offices. Crain's New York Business. May 11, 2021. Accessed July 9, 2021 at: https://www.crainsnewyork.com/health-care/telehealth-visits-dip-new-yorkers-return-doctors-offices