Challenges and Opportunities to Improve the Clinician Experience Reviewing Electronic Progress NotesFunding This work was supported by the Agency for Healthcare Research and Quality Award R01HS022085 (to G.M.) and National Science Foundation Award CMMI-1150057 (to J.M.).
25. Januar 2019
26. April 2019
19. Juni 2019 (online)
Background High-quality clinical notes are essential to effective clinical communication. However, electronic clinical notes are often long, difficult to review, and contain information that is potentially extraneous or out of date. Additionally, many clinicians write electronic clinical notes using customized templates, resulting in notes with significant variability in structure. There is a need to understand better how clinicians review electronic notes and how note structure variability may impact clinicians' note-reviewing experiences.
Objective This article aims to understand how physicians review electronic clinical notes and what impact section order has on note-reviewing patterns.
Materials and Methods We conducted an experiment utilizing an electronic health record (EHR) system prototype containing four anonymized patient cases, each composed of nine progress notes that were presented with note sections organized in different orders to different subjects (i.e., Subjective, Objective, Assessment, and Plan, Assessment, Plan, Subjective, and Objective, Subjective, Assessment, Objective, and Plan, and Mixed). Participants, who were mid-level residents and fellows, reviewed the cases and provided a brief summary after reviewing each case. Time-related data were collected and analyzed using descriptive statistics. Surveys were administered and interviews regarding experiences reviewing notes were collected and analyzed qualitatively.
Results Qualitatively, participants reported challenges related to reviewing electronic clinical notes. Experimentally, time spent reviewing notes varied based on the note section organization. Consistency in note section organization improved performance (e.g., less scrolling and searching) compared with Mixed section organization when reviewing progress notes.
Discussion Clinicians face significant challenges reviewing electronic clinical notes. Our findings support minimizing extraneous information in notes, removing information that can be found in other parts of the EHR, and standardizing the display and order of note sections to improve clinicians' note review experience.
Conclusion Our findings support the need to improve EHR note design and presentation to support optimal note review patterns for clinicians.
Keywordselectronic health records and systems - clinical documentation and communication - qualitative methods - workflow - sociotechnical aspects of information technology
Protection of Human and Animal Subjects
This study was performed in compliance with World Medical Association Declaration of Helsinki on Ethical Principles for Medical Research Involving Human Subjects. This work was reviewed by the University of Minnesota Institutional Review Board.
- 1 Lowry SZ, Ramaiah M, Patterson ES. , et al. Integrating electronic health records into clinical workflow: an application of human factors modeling methods to ambulatory care. Proceedings of the International Symposium on Human Factors and Ergonomics in Health Care 2014; 3 (01) 170-177
- 2 Friedberg MW, Chen PG, Aunon FM. , et al. Factors Affecting Physician Professional Satisfaction and Their Implications for Patient Care, Health Systems, and Health Policy. Santa Monica, CA: Rand Corporation; 2013
- 3 Rosenbloom ST, Denny JC, Xu H, Lorenzi N, Stead WW, Johnson KB. Data from clinical notes: a perspective on the tension between structure and flexible documentation. J Am Med Inform Assoc 2011; 18 (02) 181-186
- 4 Cimino JJ, Patel VL, Kushniruk AW. Studying the human-computer-terminology interface. J Am Med Inform Assoc 2001; 8 (02) 163-173
- 5 Poon AD, Fagan LM, Shortliffe EH. The PEN-Ivory project: exploring user-interface design for the selection of items from large controlled vocabularies of medicine. J Am Med Inform Assoc 1996; 3 (02) 168-183
- 6 Koopman RJ, Steege LM, Moore JL. , et al. Physician information needs and electronic health records (EHRs): time to reengineer the clinic note. J Am Board Fam Med 2015; 28 (03) 316-323
- 7 Han H, Lopp L. Writing and reading in the electronic health record: an entirely new world. Med Educ Online 2013; 18: 1-7
- 8 Shoolin J, Ozeran L, Hamann C, Bria II W. Association of Medical Directors of Information Systems consensus on inpatient electronic health record documentation. Appl Clin Inform 2013; 4 (02) 293-303
- 9 Nelson SD, LaFleur J, Fiol RGD, Weir CR. Reading and writing: qualitative analysis of pharmacists' use of the EHR when preparing for team rounds. In: AMIA Annual Symposium Proceedings. Vol. 2015. American Medical Informatics Association 2015: 943
- 10 Kaipio J, Lääveri T, Hyppönen H. , et al. Usability problems do not heal by themselves: national survey on physicians' experiences with EHRs in Finland. Int J Med Inform 2017; 97: 266-281
- 11 Cillessen FHJM, de Vries Robbé PF, Biermans MCJ. A hospital-wide transition from paper to digital problem-oriented clinical notes. A descriptive history and cross-sectional survey of use, usability, and satisfaction. Appl Clin Inform 2017; 8 (02) 502-514
- 12 Meystre SM, Savova GK, Kipper-Schuler KC, Hurdle JF. Extracting information from textual documents in the electronic health record: a review of recent research. Yearb Med Inform 2008; 35: 128-144
- 13 Weed LL. The problem oriented record as a basic tool in medical education, patient care and clinical research. Ann Clin Res 1971; 3 (03) 131-134
- 14 Lin C-T, McKenzie M, Pell J, Caplan L. Health care provider satisfaction with a new electronic progress note format: SOAP vs APSO format. JAMA Intern Med 2013; 173 (02) 160-162
- 15 Brown PJ, Marquard JL, Amster B. , et al. What do physicians read (and ignore) in electronic progress notes?. Appl Clin Inform 2014; 5 (02) 430-444
- 16 Andre AD, Wickens CD. When users want what's not best for them. Ergon Des 1995; 3 (04) 10-14
- 17 Wickens CD. Engineering Psychology and Human Performance. 4th ed. Boston: Pearson; 2013
- 18 Farri O, Rahman A, Monsen KA. , et al. Impact of a prototype visualization tool for new information in EHR clinical documents. Appl Clin Inform 2012; 3 (04) 404-418
- 19 Farri O, Pieckiewicz DS, Rahman AS, Adam TJ, Pakhomov SV, Melton GB. A qualitative analysis of EHR clinical document synthesis by clinicians. AMIA Annu Symp Proc 2012; 2012: 1211-1220
- 20 Farri O, Monsen KA, Pakhomov SV, Pieczkiewicz DS, Speedie SM, Melton GB. Effects of time constraints on clinician-computer interaction: a study on information synthesis from EHR clinical notes. J Biomed Inform 2013; 46 (06) 1136-1144
- 21 Hart SG. NASA-task load index (NASA-TLX); 20 years later. In: Proceedings of the Human Factors and Ergonomics Society Annual Meeting. Vol. 50. Sage Publications 2006: 904-908
- 22 Turf Usability Software [Compute Program]. Version 4.0. Huston, Texas. University of Texas Health Science Center at Huston; 2015
- 23 Doberne JW, He Z, Mohan V, Gold JA, Marquard J, Chiang MF. Using high-fidelity simulation and eye tracking to characterize EHR workflow patterns among hospital physicians. In: AMIA Annual Symposium Proceedings. Vol. 2015. American Medical Informatics Association; 2015: 1881
- 24 Thornton JD, Schold JD, Venkateshaiah L, Lander B. Prevalence of copied information by attendings and residents in critical care progress notes. Crit Care Med 2013; 41 (02) 382-388
- 25 Weis JM, Levy PC. Copy, paste, and cloned notes in electronic health records. Chest 2014; 145 (03) 632-638
- 26 Fanucchi L, Yan D, Conigliaro RL. Duly noted: lessons from a two-site intervention to assess and improve the quality of clinical documentation in the electronic health record. Appl Clin Inform 2016; 7 (03) 653-659
- 27 Belden JL, Koopman RJ, Patil SJ, Lowrance NJ, Petroski GF, Smith JB. Dynamic electronic health record note prototype: seeing more by showing less. J Am Board Fam Med 2017; 30 (06) 691-700
- 28 Hultman G, Marquard J, Arsoniadis E. , et al. Usability testing of two ambulatory EHR navigators. Appl Clin Inform 2016; 7 (02) 502-515