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CC BY-NC-ND 4.0 · Appl Clin Inform 2018; 09(02): 336-347
DOI: 10.1055/s-0038-1648222
Research Article
Schattauer GmbH Stuttgart

Focus Section on Health IT Usability: Perceived Burden of EHRs on Physicians at Different Stages of Their Career

Saif Khairat
1   Carolina Health Informatics Program, University of North Carolina, Chapel Hill, North Carolina, United States
2   School of Nursing, University of North Carolina, Chapel Hill, North Carolina, United States
,
Gary Burke
3   Department of Emergency Medicine, University of North Carolina, Chapel Hill, North Carolina, United States
,
Heather Archambault
4   Department of Biostatistics, University of North Carolina, Chapel Hill, North Carolina, United States
,
Todd Schwartz
4   Department of Biostatistics, University of North Carolina, Chapel Hill, North Carolina, United States
,
James Larson
3   Department of Emergency Medicine, University of North Carolina, Chapel Hill, North Carolina, United States
,
Raj M. Ratwani
5   National Center for Human Factors in Healthcare, MedStar Health, Washington, District of Columbia, United States
6   Georgetown University School of Medicine, Washington, District of Columbia, United States
› Author Affiliations
Further Information

Publication History

27 November 2017

26 March 2018

Publication Date:
16 May 2018 (online)

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Abstract

Objective The purpose of this study was to further explore the effect of EHRs on emergency department (ED) attending and resident physicians' perceived workload, satisfaction, and productivity through the completion of six EHR patient scenarios combined with workload, productivity, and satisfaction surveys.

Methods To examine EHR usability, we used a live observational design combined with post observation surveys conducted over 3 days, observing emergency physicians' interactions with the EHR during a 1-hour period. Physicians were asked to complete six patient scenarios in the EHR, and then participants filled two surveys to assess the perceived workload and satisfaction with the EHR interface.

Results Fourteen physicians participated, equally distributed by gender (50% females) and experience (43% residents, 57% attendings). Frustration levels associated to the EHR were significantly higher for attending physicians compared with residents. Among the factors causing high EHR frustrations are: (1) remembering menu and button names and commands use; (2) performing tasks that are not straightforward; (3) system speed; and (4) system reliability. In comparisons between attending and resident physicians, time to complete half of the cases as well as the overall reaction to the EHR were statistically different.

Conclusion ED physicians already have the highest levels of burnout and fourth lowest level of satisfaction among physicians and, hence, particular attention is needed to study the impact of EHR on ED physicians. This study investigated key EHR usability barriers in the ED particularly, the assess frustration levels among physicians based on experience, and identifying factors impacting those levels of frustrations. In our findings, we highlight the most favorable and most frustrating EHR functionalities between both groups of physicians.

Keywords

electronic health records and systems - interfaces and usability - physician - emergency and disaster care - satisfaction

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 and approved by the University of North Carolina at Chapel Hill (UNC) Institutional Review Board.


 

  • References

  • 1 Huerta TR, Thompson MA, Ford EW, Ford WF. Electronic health record implementation and hospitals' total factor productivity. Decis Support Syst 2013; 55 (02) 450-458
    CrossrefPubMedGoogle Scholar
  • 2 Cebul RD, Love TE, Jain AK, Hebert CJ. Electronic health records and quality of diabetes care. N Engl J Med 2011; 365 (09) 825-833
    CrossrefPubMedGoogle Scholar
  • 3 Da've D. Benefits and barriers to EMR implementation. Caring 2004; 23 (11) 50-51
    PubMedGoogle Scholar
  • 4 Walsh SH. The clinician's perspective on electronic health records and how they can affect patient care. BMJ 2004; 328 (7449): 1184-1187
    CrossrefPubMedGoogle Scholar
  • 5 Clayton PD, Naus SP, Bowes III WA. , et al. Physician use of electronic medical records: issues and successes with direct data entry and physician productivity. AMIA Annu Symp Proc 2005; 2005: 141-145
    PubMedGoogle Scholar
  • 6 Linder JA, Schnipper JL, Middleton B. Method of electronic health record documentation and quality of primary care. J Am Med Inform Assoc 2012; 19 (06) 1019-1024
    CrossrefPubMedGoogle Scholar
  • 7 Frisse ME, Johnson KB, Nian H. , et al. The financial impact of health information exchange on emergency department care. J Am Med Inform Assoc 2012; 19 (03) 328-333
    CrossrefPubMedGoogle Scholar
  • 8 Zhang J, Walji MF. TURF: toward a unified framework of EHR usability. J Biomed Inform 2011; 44 (06) 1056-1067
    CrossrefPubMedGoogle Scholar
  • 9 Sittig DF, Belmont E, Singh H. Improving the safety of health information technology requires shared responsibility: it is time we all step up. Healthc (Amst) 2017; S2213-0764(17)30020-9
    PubMedGoogle Scholar
  • 10 Tang PC, Patel VL. Major issues in user interface design for health professional workstations: summary and recommendations. Int J Biomed Comput 1994; 34 (1-4): 139-148
    CrossrefPubMedGoogle Scholar
  • 11 Linder JA, Schnipper JL, Tsurikova R, Melnikas AJ, Volk LA, Middleton B. Barriers to electronic health record use during patient visits. AMIA Annu Symp Proc 2006; 2006: 499-503
    PubMedGoogle Scholar
  • 12 Zhang J. Human-centered computing in health information systems. Part 1: analysis and design. J Biomed Inform 2005; 38 (01) 1-3
    CrossrefPubMedGoogle Scholar
  • 13 Ratwani RM, Fairbanks RJ, Hettinger AZ, Benda NC. Electronic health record usability: analysis of the user-centered design processes of eleven electronic health record vendors. J Am Med Inform Assoc 2015; 22 (06) 1179-1182
    CrossrefPubMedGoogle Scholar
  • 14 Terazzi A, Giordano A, Minuco G. How can usability measurement affect the re-engineering process of clinical software procedures?. Int J Med Inform 1998; 52 (1-3): 229-234
    CrossrefPubMedGoogle Scholar
  • 15 Association AM. Physicians Use of EHR Systems 2014. Research: 2015
    Google Scholar
  • 16 Surgeons AAPa. Physician Results EHR Survey. 2015 8/25/2017. Available at: https://aaps.wufoo.com/reports/physician-results-ehr-survey/ . Accessed August 25, 2017
    PubMedGoogle Scholar
  • 17 Hill Jr RG, Sears LM, Melanson SW. 4000 clicks: a productivity analysis of electronic medical records in a community hospital ED. Am J Emerg Med 2013; 31 (11) 1591-1594
    CrossrefPubMedGoogle Scholar
  • 18 Jamoom E, Patel V, King J, Furukawa MF. Physician experience with electronic health record systems that meet meaningful use criteria: NAMCS physician workflow survey, 2011. NCHS Data Brief 2013; (129) 1-8
    PubMedGoogle Scholar
  • 19 McHugh MD, Kutney-Lee A, Cimiotti JP, Sloane DM, Aiken LH. Nurses' widespread job dissatisfaction, burnout, and frustration with health benefits signal problems for patient care. Health Aff (Millwood) 2011; 30 (02) 202-210
    CrossrefPubMedGoogle Scholar
  • 20 Haas JS, Cook EF, Puopolo AL, Burstin HR, Cleary PD, Brennan TA. Is the professional satisfaction of general internists associated with patient satisfaction?. J Gen Intern Med 2000; 15 (02) 122-128
    CrossrefPubMedGoogle Scholar
  • 21 DiMatteo MR, Sherbourne CD, Hays RD. , et al. Physicians' characteristics influence patients' adherence to medical treatment: results from the Medical Outcomes Study. Health Psychol 1993; 12 (02) 93-102
    CrossrefPubMedGoogle Scholar
  • 22 Friedberg MW, Chen PG, Van Busum KR. , et al. Factors affecting physician professional satisfaction and their implications for patient care, health systems, and health policy. Rand Health Q 2014; 3 (04) 1
    PubMedGoogle Scholar
  • 23 Bodenheimer T, Sinsky C. From triple to quadruple aim: care of the patient requires care of the provider. Ann Fam Med 2014; 12 (06) 573-576
    CrossrefPubMedGoogle Scholar
  • 24 Shanafelt TD, Hasan O, Dyrbye LN. , et al. Changes in burnout and satisfaction with work-life balance in physicians and the general US working population between 2011 and 2014. Mayo Clin Proc 2015; 90 (12) 1600-1613
    CrossrefPubMedGoogle Scholar
  • 25 Hamid F, Cline TW. Providers' Acceptance Factors and Their Perceived Barriers to Electronic Health Record (EHR) Adoption. Online Journal of Nursing Informatics 2013;17(3). Doi: Available at: http://ojni.org/issues/?p=2837 . Accessed May 1, 2018
    PubMedGoogle Scholar
  • 26 Hart SG, Staveland LE. Development of NASA-TLX (Task Load Index): results of empirical and theoretical research. In: Hancock PA, Meshkati N. , eds. Advances in Psychology. Los Angeles, California: North-Holland; 1988: 139-183
    Google Scholar
  • 27 Hart SG. NASA-Task Load Index (NASA-TLX); 20 years later. Proceedings of the Human Factors and Ergonomic Society Annual Meeting, 2006;50(9): 904–908
    PubMedGoogle Scholar
  • 28 Chin JP, Diehl VA, Norman KL. Development of an instrument measuring user satisfaction of the human-computer interface. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems; 1988, ACM: Washington, D.C., USA:213–218
    PubMedGoogle Scholar
  • 29 AHRQ. Questionnaire for User Interface Satisfaction; 2017. Available at: https://healthit.ahrq.gov/health-it-tools-and-resources/evaluation-resources/workflow-assessment-health-it-toolkit/all-workflow-tools/questionnaire . Accessed September 25, 2017
    PubMedGoogle Scholar
  • 30 Kern LM, Barrón Y, Dhopeshwarkar RV, Edwards A, Kaushal R. ; HITEC Investigators. Electronic health records and ambulatory quality of care. J Gen Intern Med 2013; 28 (04) 496-503
    CrossrefPubMedGoogle Scholar
  • 31 Wachter R. The Digital Doctor: Hope, Hype, and Harm at the Dawn of Medicine's Computer Age. New York, NY: McGraw-Hill Education; 2015
    Google Scholar
  • 32 Nelson W. . The Gimli Glider, in Soaring Magazine; 1997
    PubMed
  • 33 Ng AKT. Cognitive psychology and human factors engineering of virtual reality. 2017 IEEE Virtual Reality (VR); 2017
    PubMedGoogle Scholar
  • 34 Singun AP. The usability evaluation of a web-based test blueprint system. 2016 International Conference on Industrial Informatics and Computer Systems (CIICS); 2016
    PubMedGoogle Scholar
  • 35 Weyers B, Burkolter D, Kluge A, Luther W. User-centered interface reconfiguration for error reduction in human-computer interaction. Presented at: Third International Conference on Advances in Human-Oriented and Personalized Mechanisms. Technologies and Services; August 22-27, 2010; Nice, France
    PubMedGoogle Scholar
  • 36 Harris D. Human Factors for Civil Flight Deck Design. New York, NY: Taylor & Francis; 2017
    Google Scholar
  • 37 Brown DM. Communicating Design: Developing Web Site Documentation for Design and Planning. San Francisco, CA: Pearson Education; 2010
    Google Scholar
  • 38 O'Connor K. Personas: The Foundation of a Great User Experience; 2011. Available at: http://uxmag.com/articles/personas-the-foundation-of-a-great-user-experience . Accessed March 2, 2018
    PubMedGoogle Scholar
  • 39 Friess E. Personas in heuristic evaluation: an exploratory study. IEEE Trans Prof Commun 2015; 58 (02) 176-191
    CrossrefPubMedGoogle Scholar
  • 40 Gothelf J. Using Proto-Personas for Executive Alignment. UX Magazine; 2012
    Google Scholar
  • 41 Nielsen J, Landauer TK. A mathematical model of the finding of usability problems. Proceedings of the INTERACT '93 and CHI '93 Conference on Human Factors in Computing Systems. Amsterdam, The Netherlands: ACM; 1993:206–213
    PubMedGoogle Scholar
  • 42 Duque A, Vázquez C. Double attention bias for positive and negative emotional faces in clinical depression: evidence from an eye-tracking study. J Behav Ther Exp Psychiatry 2015; 46: 107-114
    CrossrefPubMedGoogle Scholar
  • 43 Pierce K, Marinero S, Hazin R, McKenna B, Barnes CC, Malige A. Eye tracking reveals abnormal visual preference for geometric images as an early biomarker of an autism spectrum disorder subtype associated with increased symptom severity. Biol Psychiatry 2016; 79 (08) 657-666
    CrossrefPubMedGoogle Scholar
  • 44 Kassner M, Patera W, Bulling A. Pupil: an open source platform for pervasive eye tracking and mobile gaze-based interaction. Proceedings of the 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing: Adjunct Publication. Seattle, WA: ACM; 2014:1151–1160
    PubMedGoogle Scholar
  • 45 Hersh W. Who are the informaticians? What we know and should know. J Am Med Inform Assoc 2006; 13 (02) 166-170
    CrossrefPubMedGoogle Scholar
  • 46 Khairat S. , et al. A review of biomedical and health informatics education: a workforce training framework. J Hosp Adm 2016; 5 (05) 10
    PubMedGoogle Scholar
  • 47 Ajami S, Bagheri-Tadi T. Barriers for adopting electronic health records (EHRs) by physicians. Acta Inform Med 2013; 21 (02) 129-134
    CrossrefPubMedGoogle Scholar