Tierney, Michael J. MD; Pageler, Natalie M. MD; Kahana, Madelyn MD; Pantaleoni, Julie L. MD; Longhurst, Christopher A. MD, MS
Both undergraduate and graduate medical education are undergoing significant transformation, partly reflecting the rapid evolution of technology in health care delivery.1,2 Medical learners at both the graduate and undergraduate levels are increasingly required to use an electronic medical record (EMR) to manage patient care. Although use of the EMR has been shown to have numerous clinical benefits,3–5 comparatively little is known about the effect this technology has on medical education, and few authors have attempted to review both the potential benefits and unintended consequences.6,7
Over a decade ago, the Accreditation Council for Graduate Medical Education (ACGME) introduced six domains of clinical competency, and more recently the ACGME began to restructure the graduate medical accreditation system to reflect educational outcomes of these competencies.2 In this Perspective, we use the ACGME competencies (Medical Knowledge, Practice-Based Learning and Improvement, Patient Care, Communication Skills, Professionalism, and Systems-Based Practice) to review what is known about the effect of the EMR on achievement of these core competencies, and make recommendations for how educational institutions can leverage the EMR to support the achievement and measurement of these educational milestones and entrustable professional activities (EPAs).
Medical Knowledge and Practice-Based Learning and Improvement
With an ever-expanding body of biomedical literature, development of an adequate fund of medical knowledge is a mounting challenge for medical trainees. Clinical decision support (CDS) systems within the EMR have the potential to enhance trainees’ fund of knowledge and to guide learning efforts. Point-of-care education accessed via CDS allows for easy access to relevant and up-to-date medical literature from which students and residents can draw to formulate diagnosis and management plans.8 A thoughtfully implemented EMR can facilitate “just-in-time” education and can allow physicians to apply evidence-based medicine in the clinical context.7 CDS can also provide opportunities to teach best practices by advising learners to take actions consistent with accepted clinical algorithms and recommendations.9–14 Population management tracking and EMR-integrated clinical registries can also help teach learners important concepts in quality improvement.6
Despite the benefits of CDS, several authors have documented its unintended consequences, which may adversely affect medical education. An early review of CDS found that it was overwhelming and inappropriate to workflow and, thus, was underused and ineffective in practice.15 More recent studies have shown that implementing an EMR with unmodified settings determined by the vendor can result in an unacceptably high volume of clinically insignificant alerts, thereby promoting alert fatigue.16,17 Although refinements in technology have gradually increased the usefulness of these systems to medical learners,18 and well-implemented CDS systems have been shown to yield positive educational outcomes for the learner’s quality of clinical care,13 there is still limited understanding of how CDS affects the acquisition of knowledge by trainees. Future research efforts should evaluate the influence of CDS not only on medical trainee behaviors but also on their underlying fund of knowledge. Further, the specific elements of CDS that most strongly affect both knowledge and behavior need to be elucidated.
EMRs affect how trainees learn to care for patients in a variety of ways, from shifting workflows to altering opportunities for critical clinical thinking. Optimizing trainee workflow is essential for protecting their time for patient interactions and educational activities. The EMR has the potential to positively affect medical trainee workflow through several different mechanisms, including reduced time spent in accessing medical histories, ease of data retrieval, greater remote access, and automated creation of sign-out documents to support handoff workflow.6,19–21 However, detrimental effects of EMRs on the workflow have been documented secondary to inefficiencies in data entry, hardware downtime issues, and shifting of work from ancillary staff to physicians.17,19,22
With thoughtful planning, decision makers can ensure that the EMR favorably affects trainees’ workflow by, for example, ensuring adequate and strategic placement of computer hardware, developing robust downtime procedures, and making key decisions about the most appropriate personnel to be responsible for various types of data entry. During the process of implementing the EMR, medical educators and program directors should be advocates for decisions that optimize trainee workflow.
EMRs can also optimize workflow for both individual trainees and training programs by facilitating the process of monitoring trainees’ clinical experience. Graduate medical education is transitioning to an accreditation structure based on the achievement of outcomes detailed by educational milestones and EPAs.23,24 To this end, the EMR can facilitate tracking and reporting of trainees’ exposure to patient diagnoses and procedures. Reports of the trainees’ clinical activity and review of their clinical notes via the EMR can provide written documentation of the trainees’ achievement of patient care milestones and EPAs and can help identify areas of deficiency more efficiently than in a paper-based system.25,26
Although improved workflows have the potential to increase opportunities for trainees to engage in critical clinical thinking, some medical educators have noted concern that the EMR may negatively affect development of critical thinking skills.27,28 Few studies examine how standardized order sets, CDS error-checking interventions, and prepopulated notes in the EMR may affect the development of critical thinking and clinical decision-making skills. In a recent study comparing medical students in computerized provider order entry (CPOE) environments with those in paper-based environments, Knight and colleagues29 found no significant differences in self-reported quality of admission orders, but more rigorous and objective measures are needed to determine the true effect of CPOE with CDS on trainees’ decision making and ordering.
An additional factor that may negatively affect the self-directed learning efforts of trainees is automation bias. Previously described in the aviation industry, automation bias refers to overreliance on automated systems leading to complacency of clinicians in evaluating their own decisions.30 For example, if trainees feel like the EMR system will alert them of potential serious side effects or drug interactions, they may be less likely to research these possibilities before ordering a medication. Further research is needed to delineate how the tools provided by the EMR contribute to the development of automation bias and affect the development of critical clinical thinking and medical decision making in trainees.
Interpersonal and Communication Skills
EMRs have the potential either to enhance or impair the development of effective written communication skills, which medical students are expected to begin developing during undergraduate medical education. However, in some settings medical students are prohibited from adding clinical documentation to the EMR.31 Moreover, using note templates and copy-and-paste capabilities in charting dramatically decrease the effectiveness of physician notes as a communication tool.7,32,33 Some authors have suggested that this issue not only degrades the accuracy and utility of the clinical care record but may also impair the development of critical reasoning skills by medical learners and reduce the amount of original charting available for attending feedback.7,31,34
Strategies for mitigating some of the concerns associated with allowing trainees to contribute clinical documentation to the EMR include the creation of customized note templates for medical learners. Such templates may contain more free-text fields, minimize auto-fill and auto-text options, and prompt the documentation of certain features, such as a problem list or differential diagnosis, thereby actually promoting critical thinking.35,36 Stephens and colleagues37 have proposed a specific educational approach to clinical documentation called the Reporter–Interpreter–Manager–Educator (RIME)/EMR scheme, which structures the introduction, expectations, and assessment of EMR skills throughout the medical education process.
EMRs may also affect the development of oral presentation and communication skills. Traditionally, details of the patient’s history and clinical status were transmitted from the presenting trainee to the team during rounds. In a highly automated patient care setting, attending physicians may be more likely to receive their patient information in advance of rounds and may no longer rely on or engage trainees during case presentations.37 Peled and colleagues7 argue that this shift impairs the trainee’s practice of translating and synthesizing clinical information both before and during rounds. Furthermore, if the attending has already viewed the data and formulated a plan independently, the benefits of intellectual exchange and modeling clinical decision making during the rounding process may be lost. Despite these concerns, others might argue that with raw data more readily available, learners can spend more time synthesizing, rather than gathering, information, as well as demonstrating clinical reasoning in real time. Likewise, the EMR can be used as a tool for answering clinical questions that arise during rounds, allowing the active demonstration of the manager/educator skills emphasized in frameworks like the RIME/EMR scheme.37
Future research and curricular development should focus on formalizing EMR-specific written and oral communication competencies by training level and integrating them into the education and evaluation of medical learners. In addition, national educational organizations can help academic medical centers with best practice guidelines for integration of medical learners into EMR environments.
As EMR implementation reshapes the way that physicians interact with their patients and with other medical professionals, new issues arise for fostering the development of professionalism in trainees. Many clinicians have expressed concern over reduction in the quality of patient–learner interaction. Verghese et al38,39 eloquently described the “iPatient” who has been evaluated, diagnosed, and treated at the computer screen alone prior to bedside examination and is the product of an informal, unintended curriculum in academic settings. Furthermore, some studies show that both residents and medical students perceived a decrease in patient–physician interaction when learning in an EMR-based outpatient clinic.19,40 In spite of these concerns, others suggest that provider experience and facility with the EMR can improve the physician–patient interaction,40–42 and a lack of computer navigation skills may contribute to limited provider–patient communication.41 Indeed, Peled and colleagues7 suggest that learners should begin developing EMR-specific skills for patient encounters early in their educational process, and Morrow and colleagues43 showed that medical students within their first year of training can demonstrate EMR-specific communication skills after a brief educational intervention. Further research and curricular development are clearly needed to determine how and when EMR-specific skills for the patient encounter should be introduced to medical learners.
Within the ACGME framework of core competencies, systems-based practice refers not only to the use and optimization of the entire health care system in caring for patients but also to teamwork within that system. Comprehensive EMR systems can educate all medical learners to appreciate the complexity of the care provider network required to provide a medical home.44 Use of the EMR can also lead to significant educational yield from the review of outcomes of populations under care. Importantly, population health management has received select emphasis in the Meaningful Use criteria, which propose generation of lists by specific medical conditions to be used for quality improvement, research, outreach, and reduction of disparities.45
The concept of systems-based practice also encompasses cost-effective care for populations. To this end, integration of cost information in CPOE systems can clearly influence physician-ordering behavior.46 Influential thought leaders have recently described the fundamental properties of a highly participatory, rapid-learning health care system—one that is agile and flexible and can provide learners with feedback—that can be developed in part from the meaningful use of electronic health records,47 but these processes are challenged by the use of multiple electronic systems across different venues of care that do not seamlessly interoperate. In fact, Bates and Bitton44 concluded that two of the least developed areas of current EMR systems are support for team-based care and integrated registry analytics. As EMR systems continue to evolve, future innovations in collaborative technologies may allow for enhanced opportunities for medical learners to meet educational goals in systems-based practice.
Leveraging the EMR for the Optimal Educational Experience
In this first review of the effect of the EMR on medical learners, using the ACGME core competency structure, we have discussed many factors that affect all six domains. Best practices for integrating the EMR in medical education are beginning to emerge in the literature, and future directions for study are materializing (see Table 1). For example, during EMR implementation, medical educators should advocate for design features that optimize trainee workflow. Medical educators can and should take an active role in shaping hospital CDS interventions that support educational goals without overwhelming trainees and contributing to alert fatigue. If the technology supports it, educators should use automatic reports from EMRs to track trainees’ experience with various diagnoses and procedures.
Leaders in clinical informatics have proposed that the EMR has the potential to unlock methods of teaching on even grander scales that have not yet been possible. Future iterations may foster achievement of a nationwide “learning” health system which supports the use of large networks48,49 and the integration of local systems into a national or even global construct to ultimately promote effective medical education and patient care.47
As other aspects of industry and society embrace information technology, patient care and medical education have been uniquely enhanced—and challenged—by the transition from paper-based medical records to EMR-based tools. Certainly, the EMR is among the most significant changes to health care practice in the 21st century, and it has been met with both enthusiasm and healthy skepticism. As educators strive to transition medical trainees into lifelong learners, everything we have described is equally applicable to continuing medical education. We believe appropriate use of the EMR and related technologies in medicine can offer clinical educators and trainees a rich and promising platform to use in pursuit of a positive and effective educational experience.
Acknowledgments: The work was performed in partial fulfillment of the graduate certificate program of the Department of Medical Informatics and Clinical Epidemiology at Oregon Health & Science University. The authors would like to give special thanks to Dr. Elif Seda Selamet Tierney for her editing work on the manuscript.
Other disclosures: None.
Ethical approval: Not applicable.
1. Prober CG, Heath C. Lecture halls without lectures—A proposal for medical education. N Engl J Med. 2012;366:1657–1659
2. Nasca TJ, Philibert I, Brigham T, Flynn TC. The next GME accreditation system—Rationale and benefits. N Engl J Med. 2012;366:1051–1056
3. Hillestad R, Bigelow J, Bower A, et al. Can electronic medical record systems transform health care? Potential health benefits, savings, and costs. Health Aff (Millwood). 2005;24:1103–1117
4. Schnipper JL, Linder JA, Palchuk MB, et al. “Smart forms” in an electronic medical record: Documentation-based clinical decision support to improve disease management. J Am Med Inform Assoc. 2008;15:513–523
5. Longhurst CA, Parast L, Sandborg CI, et al. Decrease in hospital-wide mortality rate after implementation of a commercially sold computerized physician order entry system. Pediatrics. 2010;126:14–21
6. Keenan CR, Nguyen HH, Srinivasan M. Electronic medical records and their impact on resident and medical student education. Acad Psychiatry. 2006;30:522–527
7. Peled JU, Sagher O, Morrow JB, Dobbie AE. Do electronic health records help or hinder medical education? PLoS Med. 2009;6:e1000069
8. Elkin PL, Liebow M, Bauer BA, et al. The introduction of a diagnostic decision support system (DXplain™) into the workflow of a teaching hospital service can decrease the cost of service for diagnostically challenging diagnostic related groups (DRGs). Int J Med Inform. 2010;79:772–777
9. McDonald CJ. Protocol-based computer reminders, the quality of care and the non-perfectability of man. N Engl J Med. 1976;295:1351–1355
10. Hunt DL, Haynes RB, Hanna SE, Smith K. Effects of computer-based clinical decision support systems on physician performance and patient outcomes: A systematic review. JAMA. 1998;280:1339–1346
11. Galanter WL, Didomenico RJ, Polikaitis A. A trial of automated decision support alerts for contraindicated medications using computerized physician order entry. J Am Med Inform Assoc. 2005;12:269–274
12. Garg AX, Adhikari NK, McDonald H, et al. Effects of computerized clinical decision support systems on practitioner performance and patient outcomes: A systematic review. JAMA. 2005;293:1223–1238
13. Riggio JM, Sorokin R, Moxey ED, Mather P, Gould S, Kane GC. Effectiveness of a clinical-decision-support system in improving compliance with cardiac-care quality measures and supporting resident training. Acad Med. 2009;84:1719–1726
14. Adams ES, Longhurst CA, Pageler N, Widen E, Franzon D, Cornfield DN. Computerized physician order entry with decision support decreases blood transfusions in children. Pediatrics. 2011;127:e1112–e1119
15. McDonald CJ, Wilson GA, McCabe GP Jr. Physician response to computer reminders. JAMA. 1980;244:1579–1581
16. Reichley RM, Seaton TL, Resetar E, et al. Implementing a commercial rule base as a medication order safety net. J Am Med Inform Assoc. 2005;12:383–389
17. Campbell EM, Sittig DF, Ash JS, Guappone KP, Dykstra RH. Types of unintended consequences related to computerized provider order entry. J Am Med Inform Assoc. 2006;13:547–556
18. Rosenbloom ST, Geissbuhler AJ, Dupont WD, et al. Effect of CPOE user interface design on user-initiated access to educational and patient information during clinical care. J Am Med Inform Assoc. 2005;12:458–473
19. Aaronson JW, Murphy-Cullen CL, Chop WM, Frey RD. Electronic medical records: The family practice resident perspective. Fam Med. 2001;33:128–132
20. Van Eaton EG, Horvath KD, Lober WB, Rossini AJ, Pellegrini CA. A randomized, controlled trial evaluating the impact of a computerized rounding and sign-out system on continuity of care and resident work hours. J Am Coll Surg. 2005;200:538–545
21. Bernstein JA, Imler DL, Sharek P, Longhurst CA. Improved physician work flow after integrating sign-out notes into the electronic medical record. Jt Comm J Qual Patient Saf. 2010;36:72–78
22. Scott JT, Rundall TG, Vogt TM, Hsu J. Kaiser Permanente’s experience of implementing an electronic medical record: A qualitative study. BMJ. 2005;331:1313–1316
23. Green ML, Aagaard EM, Caverzagie KJ, et al. Charting the road to competence: Developmental milestones for internal medicine residency training. J Grad Med Educ. 2009;1:5–20
24. ten Cate O, Scheele F. Competency-based postgraduate training: Can we bridge the gap between theory and clinical practice? Acad Med. 2007;82:542–547
25. Sequist TD, Singh S, Pereira AG, Rusinak D, Pearson SD. Use of an electronic medical record to profile the continuity clinic experiences of primary care residents. Acad Med. 2005;80:390–394
26. Johnson VK, Michener JL. Tracking medical students’ clinical experiences with a computerized medical records system. Fam Med. 1994;26:425–427
27. Knight AM, Kravet SJ, Harper GM, Leff B. The effect of computerized provider order entry on medical student clerkship experiences. J Am Med Inform Assoc. 2005;12:554–560
28. Schenarts PJ, Schenarts KD. Educational impact of the electronic medical record. J Surg Educ. 2012;69:105–112
29. Knight AM, Kravet SJ, Kiyatkin D, Leff B. The effect of computerized provider order entry on medical students’ ability to write orders. Teach Learn Med. 2012;24:63–70
30. Goddard K, Roudsari A, Wyatt JC. Automation bias: A systematic review of frequency, effect mediators, and mitigators. J Am Med Inform Assoc. 2012;19:121–127
31. Mintz M, Narvarte HJ, O’Brien KE, Papp KK, Thomas M, Durning SJ. Use of electronic medical records by physicians and students in academic internal medicine settings. Acad Med. 2009;84:1698–1704
32. Gliatto P, Masters P, Karani R. Medical student documentation in the medical record: Is it a liability? Mt Sinai J Med. 2009;76:357–364
33. Hirschtick RE. A piece of my mind. Copy-and-paste. JAMA. 2006;295:2335–2336
34. Hammoud MM, Dalymple JL, Christner JG, et al. Medical student documentation in electronic health records: A collaborative statement from the Alliance for Clinical Education. Teach Learn Med. 2012;24:257–266
35. Hartzband P, Groopman J. Off the record—Avoiding the pitfalls of going electronic. N Engl J Med. 2008;358:1656–1658
36. Hahn JS, Bernstein JA, McKenzie RB, King BJ, Longhurst CA. Rapid implementation of inpatient electronic physician documentation at an academic hospital. Appl Clin Inf. 2012;3:175–185
37. Stephens MB, Gimbel RW, Pangaro L. Commentary: The RIME/EMR scheme: An educational approach to clinical documentation in electronic medical records. Acad Med. 2011;86:11–14
38. Verghese A. Culture shock—Patient as icon, icon as patient. N Engl J Med. 2008;359:2748–2751
39. Verghese A, Brady E, Kapur CC, Horwitz RI. The bedside evaluation: Ritual and reason. Ann Intern Med. 2011;155:550–553
40. Rouf E, Whittle J, Lu N, Schwartz MD. Computers in the exam room: Differences in physician–patient interaction may be due to physician experience. J Gen Intern Med. 2007;22:43–48
41. Frankel R, Altschuler A, George S, et al. Effects of exam-room computing on clinician–patient communication: A longitudinal qualitative study. J Gen Intern Med. 2005;20:677–682
42. Doyle RJ, Wang N, Anthony D, Borkan J, Shield RR, Goldman RE. Computers in the examination room and the electronic health record: Physicians’ perceived impact on clinical encounters before and after full installation and implementation. Fam Pract. 2012;29:601–608
43. Morrow JB, Dobbie AE, Jenkins C, Long R, Mihalic A, Wagner J. First-year medical students can demonstrate EHR-specific communication skills: A control-group study. Fam Med. 2009;41:28–33
44. Bates DW, Bitton A. The future of health information technology in the patient-centered medical home. Health Aff (Millwood). 2010;29:614–621
45. Blumenthal D, Tavenner M. The “meaningful use” regulation for electronic health records. N Engl J Med. 2010;363:501–504
46. Tierney WM, Miller ME, McDonald CJ. The effect on test ordering of informing physicians of the charges for outpatient diagnostic tests. N Engl J Med. 1990;322:1499–1504
47. Friedman CP, Wong AK, Blumenthal D. Achieving a nationwide learning health system. Sci Transl Med. 2010;2:57cm29
48. Stead WW, Searle JR, Fessler HE, Smith JW, Shortliffe EH. Biomedical informatics: Changing what physicians need to know and how they learn. Acad Med. 2011;86:429–434
49. Frankovich J, Longhurst CA, Sutherland SM. Evidence-based medicine in the EMR era. N Engl J Med. 2011;365:1758–1759