Use of Diagnostic Decision Support Systems in Medical Education

Summary

Background: Diagnostic decision support systems are designed to assist physicians with making diagnoses. This article illustrates some of the issues that will be faced as diagnostic decision support systems become used in medical education.

Objectives: The objectives of this article are to examine 1) the skills that are needed to properly use these programs as part of the students’ clinical experiences; 2) the changes that will be necessary in our curricula once these programs are more extensively utilized, including the implications of using these systems as an educational resource or simulation tool, and 3) the research issues that arise when these systems become an established part of our educational programs.

Methods: This is a critical analysis of the literature on diagnostic decision support systems and medical education.

Results: To optimally use diagnostic decision support programs, students will need grounding in the basic knowledge and skills that have always been necessary to become a physician, such as the ability to accurately gather and interpret clinical information from the patient. In addition, students will need specific skills in 1) selecting appropriate system vocabulary and functions, and 2) applying the diagnostic system’s suggestions to their particular patient.

Conclusions: When computer-based decision support systems are incorporated in medical education, they will likely lead to changes in the traditional medical curriculum. Research will be needed on how use of these programs changes the students’ knowledge, problem-solving and information-seeking skills.

Keywords

Clinical competence - computer simulation - computer-assisted diagnosis - medical education - expert systems

• References

• 1 Greiner A, Knebel E. Health Professions Education: A Bridge to Quality. Washington, DC: National Academies Press; 2003
• 2 McGowan JJ, Berner ES. Computers in medical education. In: Norman GR, Van der Vleuten CPM, Newble DI. editors. International Handbook of Research in Medical Education. Dordrecht: Kluwer; 2002. pp 537-579.
• 3 McGowan JJ, Passiment M, Hoffman HM. Educating medical students as competent users of health information technologies: The MSOP data. Stud Health Technol Inform 2007; 129 Pt [phone].
• 4 Neufeld VR, Barrows HS. The “McMaster Philosophy”: an approach to medical education. Acad Med 1974; 49: 1040-1050.
• 5 Dillon GF, Clyman SG, Clauser BE, Margolis MJ. The introduction of computer-based case simulations into the United States medical licensing examination. Acad Med 2002; 77: S94-S96.
• 6 Siegel JD, Parrino TA. Computerized diagnosis: implications for clinical education. Med Educ 1988; 22: 47-54.
• 7 Miller RA, Schaffner KF. The logic of problem-solving in clinical diagnosis: a course for second-year medical students. J Med Educ 1982; 57: 63-65.
• 8 Lincoln ML. Medical Education Applications. In: Berner ES. editor. Clinical Decision Support Systems: Theory and Practice. New York: Springer- Verlag; 1999. pp 105-137.
• 9 Bailey-Geraghty E, Jerant AF, Yeung KW. New research. Value of decision support software shown to be limited for preclinical medical students. Fam Med 2002; 34: 639-640.
• 10 Ramnarayan P, Kapoor RR, Coren M. et al. Measuring the impact of diagnostic decision support on the quality of clinical decision making: development of a reliable and valid composite score. J Am Med Inform Assoc 2003; 10: 563.
• 11 Hoffer EP, Feldman MJ, Kim RJ, Famiglietti KT, Barnett GO. DXplain: patterns of use of a mature expert system. AMIA Annu Symp Proc 2005 pp 321-325.
• 12 Kohn LT, Corrigan J, Donaldson MS. To err is human: building a safer health system. Washington, DC: National Academies Press; 2000
• 12 Crossing the Quality Chasm.. Washington, DC: National Academies Press; 2001
• 14 Berner ES, Detmer DE, Simborg D. Will the wave finally break?. A brief view of the adoption of electronic medical records in the United States. J Am Med Inform Assoc 2005
• 15 Berner ES, LaLande TJ. Overview of Clinical Decision Support Systems. In: Berner ES. editor. Clinical Decision Support Systems: Theory and Practice. 2nd ed. New York: Springer; 2007. pp 3-22.
• 16 Yu VL, Fagan LM, Wraith SM. et al. Antimicrobial selection by a computer. A blinded evaluation by infectious diseases experts. JAMA 1979; 242: 1279-1282.
• 17 Miller PL. Building an expert critiquing system: ESSENTIAL-ATTENDING. Methods Inf Med 1986; 25: 71-78.
• 18 Evans RS, Classen DC, Pestotnik SL, Clemmer TP, Weaver LK, Burke JP. A decision support tool for antibiotic therapy. Proc Annu Symp Comput Appl Med Care 1995 pp 651-655.
• 19 Osheroff JA, Teich JM, Middleton B, Steen EB, Wright A, Detmer DE. A roadmap for national action on clinical decision support. J Am Med Inform Assoc 2007; 14: 141-145.
• 20 Miller RA. Medical diagnostic decision support systems – past, present, and future: a threaded bibliography and brief commentary. J Am Med Inform Assoc 1994; 1: 8-27.
• 21 Greenes RA. Definition, Scope, and Challenges. In: Greenes RA. editor. Clinical Decision Support: The Road Ahead. Burlington, MA: Elsevier, Inc; 2007. pp 3-29.
• 22 Miller RA, Masarie Jr FE. The demise of the “Greek Oracle” model for medical diagnostic systems. Methods Inf Med 1990; 29: 1-2.
• 23 Miller RA. Why the standard view is standard: people, not machines, understand patients’ problems. J Med Philos 1990; 15: 581-591.
• 24 Miller RA, Masarie Jr FE. Use of the Quick Medical Reference (QMR) program as a tool for medical education. Methods Inf Med 1989; 28: 340-345.
• 25 Berner ES. Clinical Decision Support Systems: Theory and Practice. 2nd ed. New York: Springer; 2007
• 26 Parker RC, Miller RA. Creation of realistic appearing simulated patient cases using the INTERNIST-1/QMR knowledge base and interrelationship properties of manifestations. Methods Inf Med 1989; 28: 346-351.
• 27 Berner ES. Testing System Accuracy. In: Berner ES. editor. Clinical Decision Support Systems: Theory and Practice. New York: Springer-Verlag; 1999. pp 62-74.
• 28 Berner ES, Maisiak RS, Cobbs CG, Taunton OD. Effects of a decision support system on physicians’ diagnostic performance. J Am Med Inform Assoc 1999; 6: 420-427.
• 29 Friedman CP, Elstein AS, Wolf FM. et al. Enhancement of clinicians’ diagnostic reasoning by computer-based consultation. A multisite study of 2 systems. JAMA 1999; 282: 1851-1856.
• 30 Apkon M, Mattera JA, Lin Z. et al. A randomized outpatient trial of a decision-support information technology tool. Arch Intern Med 2005; 165: 2388-2394.
• 31 Mazoue JG. Diagnosis without doctors. J Med Philos 1990; 15: 559-579.
• 32 Harris IB. New expectations for professional competence. In: Curry L, Wergin JF. and associates, editors. Educating professionals: responding to new expectations for competence and accountability. San Francisco: Jossey-Bass; 1993. pp 17-52.
• 33 Perkins DN, Salomon G. Are cognitive skills context-bound?. Educ Researcher 1989; 18: 16-24.
• 34 Salomon G, Perkins DN. Rocky roads to transfer: Rethinking mechanisms of a neglected phenomenon. Educ Psychologist 1989; 24: 113-142.
• 35 Schon DA. Educating the reflective practitioner. San Francisco: Jossey-Bass; 1987
• 36 Fletcher RH, Fletcher SW. What is the future of internal medicine?. Ann Intern Med 1993; 119: 144-145.
• 37 Horowitz HW. A piece of my mind. The interpreter of facts. JAMA 2008; 299: 497-498.
• 38 Altman M. The clinical data repository: A challenge to medical student education. J Amer Med Inform Assoc 2007; 6: 697-699.
• 39 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: 473.
• 40 Baxt WG. Application of artificial neural networks to clinical medicine. Lancet 1995; 346: 1135-1138.
• 41 Tolxdorff T, Deserno TM, Handels H, Meinzer HP. Advances in medical image computing. Methods Inf Med 2009; 48: 311-313.
• 42 Schmidt-Richberg A, Handels H, Ehrhardt J. Integrated segmentation and non-linear registration for organ segmentation and motion field estimation in 4D DT data. Methods Inf Med 2009; 48: 344-349.
• 43 Munzenmayer C, Kage A, Wittenberg T, Muhldorfer S. Computer-assisted diagnosis for precancerous lesions in the esophagus. Methods Inf Med 2009; 48: 324-330.
• 44 Handels H, Ehrhardt J. Medical image computing for computer-supported diagnostics and therapy. Advances and perspectives. Methods Inf Med 2009; 48: 11-17.
• 45 Wiltgen M, Gerger A, Wagner C, Smolle J. Automatic identification of diagnositic significant regions in confocal laser scanning microscopy of melanocytic skin tumors. Methods Inf Med 2008; 47: 14-25.
• 46 Chaisaowong K, Aach T, Jager P, Voget S, Knepper A, Kraus T. Computer-assisted diagnosis for early stage pleural mesothelioma: Towards automated detection and quantitative assessment of pleural thickening from thoracic CT images. Methods Inf Med 2007; 46: 324-331.
• 47 Willems JL, Abreu-Lima C, Arnaud P. et al. The diagnostic performance of computer programs for the interpretation of electrocardiograms. N Engl J Med 1991; 325: 1767-1773.
• 48 Berner ES, Maisiak RS, Heudebert GR, Young Jr KR. Clinician performance and prominence of diagnoses displayed by a clinical diagnostic decision support system. AMIA Annu Symp Proc 2003; 2003: 76-80.
• 49 Friedman CP, Gatti GG, Franz TM. et al. Do physicians know when their diagnoses are correct?. J Gen Intern Med 2005; 20: 334-339.
• 50 Berner ES, Boulware DW. Medical informatics for medical students: Not just because it’s there. Medical Education Online. 1996: 1.
• 51 Berner ES, Graber ML. On overconfidence and diagnostic error. Amer J Med 2008; 121: E19.
• 52 Lincoln MJ, Turner CW, Haug PJ. et al. Iliad training enhances medical students’ diagnostic skills. J Med Sys 1991; 15: 93-110.
• 53 Kurihara Y, Kitazoe Y, Okuhara Y, Narita Y, Ozawa T. Development of a diagnostic and therapeutic simulation system based on patient data and specialist’s knowledge. I. Simulation of diagnostic process. J Med Sys 1992; 16: 227-235.
• 54 Berner ES, Dev P, Smith NB, Harding S. Strategy for efficient construction of Multimedia Case Simulations. Proc AMIA Fall Symp. 1998 p 974.
• 55 Salomon G, Perkins DN, Globerson T. Partners in cognition: extending human intelligence with intelligent technologies. Educ Researcher 1991; 20: 2.
• 56 Arene I, Ahmed W, Fox M, Barr CE, Fisher K. Evaluation of quick medical reference (QMR) as a teaching tool. MD Comput 1998; 15: 323-326.
• 57 Brahams D, Wyatt J. Decision aids and the law. Lancet 1989; 2: 632-634.
• 58 Galletta DF, Durcikova A, Everard A, Jones BM. Does spell-checking software need a warning label?. Communications of the ACM 2005; 48: 82-86.
• 59 Tsai TL, Fridsma DB, Gatti G. Computer decision support as a source of interpretation error: the case of electrocardiograms. J Am Med Inform Assoc 2003; 10: 478-483.
• 60 Covell DG, Uman GC, Manning PR. Information needs in office practice: are they being met?. Ann Intern Med 1985; 103: 596-599.
• 61 Forsythe DE, Buchanan BG, Osheroff JA, Miller RA. Expanding the concept of medical information: an observational study of physicians’ information needs. Comput Biomed Res 1992; 25: 181-200.
• 62 Gorman PN, Helfand M. Information seeking in primary care: how physicians choose which clinical questions to pursue and which to leave unanswered. Med Decis Making 1995; 15: 113-119.