This paper is in the following e-collection/theme issue:

Electronic Health Records (1034) Clinical Informatics (989) Design and Usability of Clinical Software and EHRs (262) Wearable Devices and Sensors (876) Anxiety and Stress Disorders (1038) Occupational Health and Ergonomics/Prevention at the Workplace (231) Physician and Healthcare Worker Burnout (108) Human Factors and Usability Case Studies (773)
Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/24014, first published .
Physician Stress During Electronic Health Record Inbox Work: In Situ Measurement With Wearable Sensors

Physician Stress During Electronic Health Record Inbox Work: In Situ Measurement With Wearable Sensors

Physician Stress During Electronic Health Record Inbox Work: In Situ Measurement With Wearable Sensors

Authors of this article:

Fatema Akbar1 Author Orcid Image ;   Gloria Mark1 Author Orcid Image ;   Stephanie Prausnitz2 Author Orcid Image ;   E Margaret Warton2 Author Orcid Image ;   Jeffrey A East3, 4, 5 Author Orcid Image ;   Mark F Moeller3, 6 Author Orcid Image ;   Mary E Reed2 Author Orcid Image ;   Tracy A Lieu2, 3 Author Orcid Image
Article Authors Cited by (23) Tweetations (16) Metrics

Journals

  1. Nguyen O, Turner K, Apathy N, Magoc T, Hanna K, Merlo L, Harle C, Thompson L, Berner E, Feldman S. Primary care physicians’ electronic health record proficiency and efficiency behaviors and time interacting with electronic health records: a quantile regression analysis. Journal of the American Medical Informatics Association 2022;29(3):461 View
  2. Lonsdale H, Gray G, Ahumada L, Yates H, Varughese A, Rehman M. The Perioperative Human Digital Twin. Anesthesia & Analgesia 2022;134(4):885 View
  3. Rule A, Melnick E, Apathy N. Using event logs to observe interactions with electronic health records: an updated scoping review shows increasing use of vendor-derived measures. Journal of the American Medical Informatics Association 2022;30(1):144 View
  4. Akbar F. Using sensors to measure inbox stress. XRDS: Crossroads, The ACM Magazine for Students 2021;28(1):19 View
  5. Baxter S, Saseendrakumar B, Cheung M, Savides T, Longhurst C, Sinsky C, Millen M, Tai-Seale M. Association of Electronic Health Record Inbasket Message Characteristics With Physician Burnout. JAMA Network Open 2022;5(11):e2244363 View
  6. Neeman E, Lyon L, Sun H, Conell C, Reed M, Kumar D, Kolevska T, Kotak D, Sundaresan T, Liu R. Future of Teleoncology: Trends and Disparities in Telehealth and Secure Message Utilization in the COVID-19 Era. JCO Clinical Cancer Informatics 2022;(6) View
  7. Lopes L, Rodrigues A, Cabral D, Campos P. From Monitoring to Assisting: A Systematic Review towards Healthier Workplaces. International Journal of Environmental Research and Public Health 2022;19(23):16197 View
  8. Goldman A, Kathrins M. Optimized Use of the Electronic Health Record and Other Clinical Resources to Enhance the Management of Hypogonadal Men. Endocrinology and Metabolism Clinics of North America 2022;51(1):217 View
  9. Rittenberg E, Liebman J, Rexrode K. Primary Care Physician Gender and Electronic Health Record Workload. Journal of General Internal Medicine 2022;37(13):3295 View
  10. Sinsky C, Shanafelt T, Ristow A. Radical Reorientation of the US Health Care System Around Relationships. Mayo Clinic Proceedings 2022;97(12):2194 View
  11. Apathy N, Hare A, Fendrich S, Cross D. I had not time to make it shorter: an exploratory analysis of how physicians reduce note length and time in notes. Journal of the American Medical Informatics Association 2023;30(2):355 View
  12. Blijleven V, Hoxha F, Jaspers M. Workarounds in Electronic Health Record Systems and the Revised Sociotechnical Electronic Health Record Workaround Analysis Framework: Scoping Review. Journal of Medical Internet Research 2022;24(3):e33046 View
  13. Budd J. Burnout Related to Electronic Health Record Use in Primary Care. Journal of Primary Care & Community Health 2023;14 View
  14. Bali A, Hashash J, Picco M, Kinnucan J, Farraye F. Electronic Health Record Burden Among Gastroenterology Providers Associated With Subspecialty and Training. American Journal of Gastroenterology 2023;118(7):1282 View
  15. Avdagovska M, Kuziemsky C, Koosha H, Hadizadeh M, Pauly R, Graham T, Stafinski T, Bigam D, Kassam N, Menon D. Exploring the Impact of In Basket Metrics on the Adoption of a New Electronic Health Record System Among Specialists in a Tertiary Hospital in Alberta: Descriptive Study. Journal of Medical Internet Research 2024;26:e53122 View
  16. Baxter S, Longhurst C, Millen M, Sitapati A, Tai-Seale M. Generative artificial intelligence responses to patient messages in the electronic health record: early lessons learned. JAMIA Open 2024;7(2) View
  17. Tai-Seale M, Baxter S, Vaida F, Walker A, Sitapati A, Osborne C, Diaz J, Desai N, Webb S, Polston G, Helsten T, Gross E, Thackaberry J, Mandvi A, Lillie D, Li S, Gin G, Achar S, Hofflich H, Sharp C, Millen M, Longhurst C. AI-Generated Draft Replies Integrated Into Health Records and Physicians’ Electronic Communication. JAMA Network Open 2024;7(4):e246565 View
  18. Bundy R, Moses A, Stambaugh E, Stewart P, Witek L, Carlasare L, Rosenthal G, Sinsky C, Dharod A. Assessment of EHR Efficiency Tools and Resources Associated with Physician Time Spent on the Inbox. Journal of General Internal Medicine 2024;39(13):2432 View
  19. Liddell S, Tomasi A, Halvorsen A, Stelling B, Leasure E. Gender Disparities in Electronic Health Record Usage and Inbasket Burden for Internal Medicine Residents. Journal of General Internal Medicine 2024 View
  20. Tai‐Seale M, Walker A, Cheng Y, Yung N, Webb S, Lunde O, Bazzo D, Mandvi A, Doran N, Kallenberg G, Longhurst C, Zisook S, Savides T, Millen M, Liu L. Learning health system research as a catalyst for promoting physician wellness: EHR InBasket Spring cleaning and team‐based compassion practice. Learning Health Systems 2024 View
  21. Small W, Wiesenfeld B, Brandfield-Harvey B, Jonassen Z, Mandal S, Stevens E, Major V, Lostraglio E, Szerencsy A, Jones S, Aphinyanaphongs Y, Johnson S, Nov O, Mann D. Large Language Model–Based Responses to Patients’ In-Basket Messages. JAMA Network Open 2024;7(7):e2422399 View