Subscribe to RSS
DOI: 10.1055/s-0041-1736625
Characterizing Multitasking and Workflow Fragmentation in Electronic Health Records among Emergency Department Clinicians: Using Time-Motion Data to Understand Documentation Burden
Funding This study was supported by the U.S. National Library of Medicine of the National Institutes of Health under the training fellowship award 5T15LM007079 and the National Institute of Nursing Research under the training fellowship award 5T32NR007969.Abstract
Background The impact of electronic health records (EHRs) in the emergency department (ED) remains mixed. Dynamic and unpredictable, the ED is highly vulnerable to workflow interruptions.
Objectives The aim of the study is to understand multitasking and task fragmentation in the clinical workflow among ED clinicians using clinical information systems (CIS) through time-motion study (TMS) data, and inform their applications to more robust and generalizable measures of CIS-related documentation burden.
Methods Using TMS data collected among 15 clinicians in the ED, we investigated the role of documentation burden, multitasking (i.e., performing physical and communication tasks concurrently), and workflow fragmentation in the ED. We focused on CIS-related tasks, including EHRs.
Results We captured 5,061 tasks and 877 communications in 741 locations within the ED. Of the 58.7 total hours observed, 44.7% were spent on CIS-related tasks; nearly all CIS-related tasks focused on data-viewing and data-entering. Over one-fifth of CIS-related task time was spent on multitasking. The mean average duration among multitasked CIS-related tasks was shorter than non-multitasked CIS-related tasks (20.7 s vs. 30.1 s). Clinicians experienced 1.4 ± 0.9 task switches/min, which increased by one-third when multitasking. Although multitasking was associated with a significant increase in the average duration among data-entering tasks, there was no significant effect on data-viewing tasks. When engaged in CIS-related task switches, clinicians were more likely to return to the same CIS-related task at higher proportions while multitasking versus not multitasking.
Conclusion Multitasking and workflow fragmentation may play a significant role in EHR documentation among ED clinicians, particularly among data-entering tasks. Understanding where and when multitasking and workflow fragmentation occurs is a crucial step to assessing potentially burdensome clinician tasks and mitigating risks to patient safety. These findings may guide future research on developing more scalable and generalizable measures of CIS-related documentation burden that do not necessitate direct observation techniques (e.g., EHR log files).
Keywords
electronic health records - time-motion studies - physicians - physician assistants - documentation burden - emergency departmentAuthor Contributions
S.C.R. conceptualized the TMS. S.C.R. and A.J.M. defined the scope of the analysis. A.J.M. performed the analysis and wrote the manuscript. L.A. was involved in data collection. J.M.S. and J.E. trained the observers. L.A., K.D.C., R.T., and S.C.R. provided revisions and feedback, and approved the final manuscript.
Protection of Human and Animal Subjects
The study was performed in compliance with the World Medical Association Declaration of Helsinki on Ethical Principles for Medical Research Involving Human Subjects, and was reviewed by the Columbia University Irving Medical Center Institutional Review Board.
Publication History
Received: 23 May 2021
Accepted: 29 September 2021
Article published online:
27 October 2021
© 2021. Thieme. All rights reserved.
Georg Thieme Verlag KG
Rüdigerstraße 14, 70469 Stuttgart, Germany
-
References
- 1 Cohen G, Brown L, Fitzgerald M, Somplasky A. Exploring the feasibility of using audit log data to quantitate burden as providers use electronic health records. Washington DC; 2019 Sep. Accessed July 26, 2021 at: https://aspe.hhs.gov/sites/default/files/private/pdf/263356/jsk-qebhr-final-concept-report.pdf
- 2 Sulmasy LS, López AM, Horwitch CA, Professionalism ACE. American College of Physicians Ethics, Professionalism and Human Rights Committee. Ethical Implications of the electronic health record: in the service of the patient. J Gen Intern Med 2017; 32 (08) 935-939
- 3 Stehman CR, Testo Z, Gershaw RS, Kellogg AR. Burnout, drop out, suicide: physician loss in emergency medicine, Part I. West J Emerg Med 2019; 20 (03) 485-494
- 4 Ben-Assuli O, Sagi D, Leshno M, Ironi A, Ziv A. Improving diagnostic accuracy using EHR in emergency departments: a simulation-based study. J Biomed Inform 2015; 55: 31-40
- 5 Fernandes M, Vieira SM, Leite F, Palos C, Finkelstein S, Sousa JMC. Clinical decision support systems for triage in the emergency department using intelligent systems: a review. Artif Intell Med 2020; 102: 101762
- 6 Park SY, Lee SY, Chen Y. The effects of EMR deployment on doctors' work practices: a qualitative study in the emergency department of a teaching hospital. Int J Med Inform 2012; 81 (03) 204-217
- 7 Moy AJ, Schwartz JM, Chen R. et al. Measurement of clinical documentation burden among physicians and nurses using electronic health records: a scoping review. J Am Med Inform Assoc 2021; 28 (05) 998-1008
- 8 Olson K, Sinsky C, Rinne ST. et al. Cross-sectional survey of workplace stressors associated with physician burnout measured by the Mini-Z and the Maslach Burnout Inventory. Stress Health 2019; 35 (02) 157-175
- 9 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
- 10 Shanafelt TD, Boone S, Tan L. et al. Burnout and satisfaction with work-life balance among US physicians relative to the general US population. Arch Intern Med 2012; 172 (18) 1377-1385
- 11 Chisholm CD, Collison EK, Nelson DR, Cordell WH. Emergency department workplace interruptions: are emergency physicians “interrupt-driven” and “multitasking”?. Acad Emerg Med 2000; 7 (11) 1239-1243
- 12 Chisholm CD, Weaver CS, Whenmouth L, Giles B. A task analysis of emergency physician activities in academic and community settings. Ann Emerg Med 2011; 58 (02) 117-122
- 13 Weigl M, Müller A, Holland S, Wedel S, Woloshynowych M. Work conditions, mental workload and patient care quality: a multisource study in the emergency department. BMJ Qual Saf 2016; 25 (07) 499-508
- 14 Yen PY, Kelley M, Lopetegui M. et al. Understanding and visualizing multitasking and task switching activities: a time motion study to capture nursing workflow. AMIA Annu Symp Proc 2017; 2016: 1264-1273
- 15 Westbrook JI, Coiera E, Dunsmuir WTM. et al. The impact of interruptions on clinical task completion. Qual Saf Health Care 2010; 19 (04) 284-289
- 16 Yen PY, Kellye M, Lopetegui M. et al. Nurses' time allocation and multitasking of nursing activities: a time motion study. AMIA Annu Symp Proc 2018; 2018: 1137-1146
- 17 Eng MS, Fierro K, Abdouche S, Yu D, Schreyer KE. Perceived vs. actual distractions in the emergency department. Am J Emerg Med 2019; 37 (10) 1896-1903
- 18 Crawford S, Kushner I, Wells R, Monks S. Electronic health record documentation times among emergency medicine trainees. Perspect Health Inf Manag 2019; 16 (Winter): 1f
- 19 Kannampallil TG, Denton CA, Shapiro JS, Patel VL. Efficiency of emergency physicians: insights from an observational study using EHR log files. Appl Clin Inform 2018; 9 (01) 99-104
- 20 Coiera EW, Jayasuriya RA, Hardy J, Bannan A, Thorpe ME. Communication loads on clinical staff in the emergency department. Med J Aust 2002; 176 (09) 415-418
- 21 Neri PM, Redden L, Poole S. et al. Emergency medicine resident physicians' perceptions of electronic documentation and workflow: a mixed methods study. Appl Clin Inform 2015; 6 (01) 27-41
- 22 Chisholm CD, Dornfeld AM, Nelson DR, Cordell WH. Work interrupted: a comparison of workplace interruptions in emergency departments and primary care offices. Ann Emerg Med 2001; 38 (02) 146-151
- 23 Moy AJ, Schwartz JM, Elias J. et al. Time-motion examination of electronic health record utilization and clinician workflows indicate frequent task switching and documentation burden. AMIA Annu Symp Proc 2021; 2020: 886-895
- 24 Schwartz J, Elias J, Slater C, Cato K, Rossetti SC. An interprofessional approach to clinical workflow evaluation focused on the electronic health record using time motion study methods. AMIA Annu Symp Proc 2020; 2019: 1187-1196
- 25 Lopetegui M, Yen PY, Lai AM, Embi PJ, Payne PR. Time capture tool (TimeCaT): development of a comprehensive application to support data capture for time motion studies. AMIA Annu Symp Proc 2012; 2012: 596-605
- 26 Zheng K, Haftel HM, Hirschl RB, O'Reilly M, Hanauer DA. Quantifying the impact of health IT implementations on clinical workflow: a new methodological perspective. J Am Med Inform Assoc 2010; 17 (04) 454-461
- 27 Kiran DR. Total Employee Involvement. In: Guerin B, ed. Total Quality Management. : Key Concepts and Case Studies. Amsterdam: Butterworth-Heinemann; 2017: 143-162
- 28 Adler-Milstein J, Adelman JS, Tai-Seale M, Patel VL, Dymek C. EHR audit logs: a new goldmine for health services research?. J Biomed Inform 2020; 101: 103343
- 29 Grzywinski M, Carlisle S, Coleman J. et al. Development of a novel emergency department mapping tool. HERD 2020; 13 (01) 81-93
- 30 Weiler DT, Satterly T, Rehman SU. et al. Ambulatory clinic exam room design with respect to computing devices: a laboratory simulation study. IISE Trans Occup Ergon Hum Factors 2018; 6 (3-4): 165-177
- 31 Bowes III WA. Measuring use of electronic health record functionality using system audit information. Stud Health Technol Inform 2010; 160 (Pt 1): 86-90
- 32 ASTM E2147–18.. Standard Specification for Audit and Disclosure Logs for Use in Health Information Systems. West Conshohocken: ASTM International; 2018
- 33 Rule A, Chiang MF, Hribar MR. Using electronic health record audit logs to study clinical activity: a systematic review of aims, measures, and methods. J Am Med Inform Assoc 2020; 27 (03) 480-490
- 34 Chen B, Alrifai W, Gao C. et al. Mining tasks and task characteristics from electronic health record audit logs with unsupervised machine learning. J Am Med Inform Assoc 2021; 28 (06) 1168-1177
- 35 Office of the National Coordinator for Health Information Technology. Strategy on reducing burden relating to the use of health IT and EHRs. 2020 . [cited 2020 November 5]. Available at: https://www.healthit.gov/topic/usability-and-provider-burden/strategy-reducing-burden-relating-use-health-it-and-ehrs
- 36 Goldstein IH, Hribar MR, Reznick LG, Chiang MF. Analysis of total time requirements of electronic health record use by ophthalmologists using secondary EHR data. AMIA Annu Symp Proc 2018; 2018: 490-497
- 37 Hilliard RW, Haskell J, Gardner RL. Are specific elements of electronic health record use associated with clinician burnout more than others?. J Am Med Inform Assoc 2020; 27 (09) 1401-1410
- 38 Arndt BG, Beasley JW, Watkinson MD. et al. Tethered to the EHR: primary care physician workload assessment using EHR event log data and time-motion observations. Ann Fam Med 2017; 15 (05) 419-426
- 39 Kannampallil T, Abraham J, Lou SS, Payne PRO. Conceptual considerations for using EHR-based activity logs to measure clinician burnout and its effects. J Am Med Inform Assoc 2021; 28 (05) 1032-1037
- 40 Sopan A, Plaisant C, Powsner S, Shneiderman B. Reducing wrong patient selection errors: exploring the design space of user interface techniques. AMIA Annu Symp Proc 2014; 2014: 1056-1065
- 41 Taieb-Maimon M, Plaisant C, Hettinger AZ, Shneiderman B. Increasing recognition of wrong-patient errors through improved interface design of a computerized provider order entry system. Int J Hum Comput Interact 2018; 34 (05) 383-398
- 42 Ash JS, Berg M, Coiera E. Some unintended consequences of information technology in health care: the nature of patient care information system-related errors. J Am Med Inform Assoc 2004; 11 (02) 104-112
- 43 Holden RJ. Cognitive performance-altering effects of electronic medical records: an application of the human factors paradigm for patient safety. Cogn Technol Work 2011; 13 (01) 11-29
- 44 Poon EG, Keohane CA, Yoon CS. et al. Effect of bar-code technology on the safety of medication administration. N Engl J Med 2010; 362 (18) 1698-1707
- 45 Sinsky C, Colligan L, Li L. et al. Allocation of physician time in ambulatory practice: a time and motion study in 4 specialties. Ann Intern Med 2016; 165 (11) 753-760
- 46 Chang BP, Cato KD, Cassai M, Breen L. Clinician burnout and its association with team based care in the emergency department. Am J Emerg Med 2019; 37 (11) 2113-2114
- 47 Patel VL, Denton CA, Soni HC, Kannampallil TG, Traub SJ, Shapiro JS. Physician workflow in two distinctive emergency departments: an observational study. Appl Clin Inform 2021; 12 (01) 141-152
- 48 Davis MA, Cher BAY, Friese CR, Bynum JPW. Association of US nurse and physician occupation with risk of suicide. JAMA Psychiatry 2021; 78 (06) 651-658