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Medical Education Applications

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Clinical Decision Support Systems

Part of the book series: Health Informatics ((HI))

Abstract

This chapter reviews the use of clinical diagnostic decision support systems (CDDSS) for educating physicians, nurses, physician-assistants, and other medical professionals. The discussion of this topic is quite timely. Informatics technologies and decision support systems are now widely considered to be an important component of medical curricula and the medical education journal Academic Medicine now includes a regular informatics column.1 Professional societies have also recognized this trend. The Society of General Internal Medicine and the American Board of Internal Medicine have recently established training standards for internists which include literature searching, use of decision making tools, and other informatics technologies. CDDSS can provide domain specific, case-based, clinical experiences for students to supplement actual patient experiences, which can be highly variable.

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References

  1. Masys DR. Medical Informatics: glimpses of the promised land. Acad Med 1989; 64:13–14.

    Article  PubMed  CAS  Google Scholar 

  2. Williamson JW, Goldschmit PG, Colton T. The quality of medical literature: an analysis of validation assessments. In: Bailar, JC 3rd, Mosteller, F, eds. Medical Uses of Statistics. Walton, MA: NEJM Books, 1986:370–391.

    Google Scholar 

  3. Schoolman HM. The impact of electronic computers and other technologies on information resources for the physician. Bull N Y Acad Med 1985; 61:283–289.

    PubMed  CAS  Google Scholar 

  4. Williamson JW, German PS, Weiss R et al. Health science information management and continuing education of physicians—a survey of U.S. primary care practitioners and their opinion leaders. Ann Intern Med 1989; 110:151–160.

    Article  PubMed  CAS  Google Scholar 

  5. Miller RA, Giuse NB. Medical knowledge bases. Acad Med 1991; 66:15–17.

    Article  PubMed  CAS  Google Scholar 

  6. Nilasena DS, Lincoln MJ. A computer-generated reminder system improves physician compliance with diabetes preventive care guidelines. Proc Annu Symp Comput Appl Med Care 1995:640–645.

    Google Scholar 

  7. Lomas J; Enkin M; Anderson GM et al. Opinion leaders vs. audit and feedback to implement practice guidelines. JAMA 1991; 265:2202–2207.

    Article  PubMed  CAS  Google Scholar 

  8. Lomas MA, Anderson GM et al. Do practice guidelines guide practice? The effect of a consensus statement on the practice of physicians. N Engl J Med 1989; 321:1306–1311.

    Article  PubMed  CAS  Google Scholar 

  9. Tierney WM, Overhage JM, McDonald CJ. Computerizing guidelines: factors for success. Proc AMIA Fall Symp 1996:459–462.

    Google Scholar 

  10. Overhage JM, Tierney WM, McDonald CJ. Computer reminders to implement preventive care guidelines for hospitalized patients. Arch Intern Med 1996; 156:1551–1556.

    Article  PubMed  CAS  Google Scholar 

  11. Pestotnik SL, Classen DC, Evans RS et al. Implementing antibiotic practice guidelines through computer-assisted decision support: clinical and financial outcomes. Ann Int Med 1996; 124:884–890.

    Article  PubMed  CAS  Google Scholar 

  12. de Dombal FT. Computer-aided diagnosis and decision-making in the acute abdomen. J R Coll Physicians 1975; 9:211–218.

    Google Scholar 

  13. Elstein AS, Shulman LS, Sprafka SA. Medical problem solving: an analysis of clinical reasoning. Cambridge, MA: Harvard University Press, 1978.

    Google Scholar 

  14. Elstein AS, Shulman LS, Sprafka SA. Medical problem solving: a ten-year retrospective. Eval Health Prof 1990; 13:5–36.

    Article  Google Scholar 

  15. Norman GR, Tugwell P, Feightner JW et al. Knowledge and clinical problem-solving ability. Med Educ 1985; 19:344–356.

    Article  PubMed  CAS  Google Scholar 

  16. Schmidt HG, Norman GR, Boshuizen HPA. A cognitive perspective on medical expertise: theory and implications. Acad Med 1990; 65:611–621.

    Article  PubMed  CAS  Google Scholar 

  17. Fu LS, Huff S, Bouhaddou O et al. Estimating frequency of disease findings from combined hospital databases: a UMLS project. Proc Annu Symp Comput Appl Med Care 1991:373–377.

    Google Scholar 

  18. Haug PJ, Gardner RM, Tate KE et al. Decision support in medicine: examples from the HELP system. Comput Biomed Res 1994; 27:396–418.

    Article  PubMed  CAS  Google Scholar 

  19. Yu H, Haug PJ, Lincoln MJ, Turner C, Warner HR. Clustered knowledge representation: Increasing the reliability of computerized expert systems. Proc Annu Symp Comput Appl Med Care 1988:126–130.

    Google Scholar 

  20. Giuse DA, Giuse NB, Miller RA. A tool for the computer-assisted creation of QMR medical knowledge base disease profiles. Proc Annu Symp Comput Appl Med Care 1991:978–979.

    Google Scholar 

  21. Giuse DA, Giuse NB, Miller RA. Consistency enforcement in medical knowledge base construction. Artif Intell Med 1993; 5:245–252.

    Article  PubMed  CAS  Google Scholar 

  22. Giuse DA, Giuse NB, Bankowitz RA et al. Heuristic determination of quantitative data for knowledge acquisition in medicine. Comput Biomed Res 1991; 24:261–272.

    Article  PubMed  CAS  Google Scholar 

  23. Warner HR. Computer-Assisted Medical Decision Making. New York: Academic Press, 1979.

    Google Scholar 

  24. Lincoln MJ, Turner CW, Haug PJ et al. Iliad training enhances medical students’ diagnostic skills. J Med Syst 1991; 15:93–109.

    Article  PubMed  CAS  Google Scholar 

  25. Shortliffe EH, Perreault LE, eds. Medical Informatics. Reading, MA: Addison Wesley Publishing, 1990.

    Google Scholar 

  26. Li YC, Haug PJ, Warner HR. Automated transformation of probabilistic knowledge for a medical diagnostic system. Proc Annu Symp Comput Appl Med Care 1994:765–769.

    Google Scholar 

  27. Newell A, Shaw JC, Simon HA. Elements of a theory of human problem solving. Psychol Rev 1958; 65:151–166.

    Article  Google Scholar 

  28. Kassirer JP. Diagnostic reasoning. Ann Intern Med 1989; 110:893–900.

    Article  PubMed  CAS  Google Scholar 

  29. Barrows HS, Norman GR, Neufeld VR et al. The clinical reasoning of randomly selected physicians in general medical practice. Clin Invest Med 1982; 5:49–55.

    PubMed  CAS  Google Scholar 

  30. Kassirer JP, Gorry GA. Clinical problem-solving—a behavioral analysis. Ann Intern Med 1978; 89:245–255.

    Article  PubMed  CAS  Google Scholar 

  31. Pople HE Jr. Heuristic methods for imposing structure on ill-structured problems: the structuring of medical diagnostics. In: Szolovits P, ed. Artificial Intelligence in Medicine. AAAS Symposium Series. Boulder, CO: Westview Press, 1982, 119–190.

    Google Scholar 

  32. Kassirer JP, Kopelman RI. Cognitive errors in diagnosis: instantiation, classification, and consequences. Am J Med 1989; 86:433–440.

    Article  PubMed  CAS  Google Scholar 

  33. Voytovich AE, Rippey RM, Suffredini A. Premature conclusions in diagnostic reasoning. J Med Educ 1985; 60:302–307.

    PubMed  CAS  Google Scholar 

  34. Lee AS, Cutts JH, Sharp GC et al. AI/LEARN network. The use of computer-generated graphics to augment the educational utility of a knowledge-based diagnostic system (AI/RHEUM). J Med Syst 1987; 11:349–358.

    Article  PubMed  CAS  Google Scholar 

  35. Miller R, Masarie FE, Myers J. Quick Medical Reference (QMR) for diagnostic assistance. MD Comput 1986; 3:34–48.

    PubMed  CAS  Google Scholar 

  36. First MB, Soffer LJ, Miller RA. QUICK (Quick Index to Caduceus Knowledge): Using the Internist-I/Caduceus knowledge base as an electronic textbook of medicine. Comput Biomed Res 1985; 18: 137–165.

    Article  PubMed  CAS  Google Scholar 

  37. 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.

    PubMed  CAS  Google Scholar 

  38. 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.

    PubMed  CAS  Google Scholar 

  39. Miller RA, Masarie FE. Use of the Quick Medical Reference (QMR) program as a tool for medical education. Methods Inf Med 1989; 28:340–345.

    PubMed  CAS  Google Scholar 

  40. Guo D, Lincoln MJ, Haug PJ et al. Exploring a new best information algorithm for Iliad. Proc Annu Symp Comput Appl Med Care 1991:624–628.

    Google Scholar 

  41. Turner CW, Williamson JW, Lincoln MJ et al. The effects of Iliad on medical student problem solving. Proc Annu Symp Comput Appl Med Care 1990:478–482

    Google Scholar 

  42. Cundick RM, Turner CW, Lincoln MJ et al. Iliad as a patient case simulator to teach medical problem solving. Proc Annu Symp Comput Appl Med Care 1989:13:902–906.

    Google Scholar 

  43. Lincoln MJ, Turner CW, Haug PJ et al. Iliad’s role in the generalization of learning across a medical domain. Proc Annu Symp Comput Appl Med Care 1992:174–178.

    Google Scholar 

  44. Elstein AS, Friedman CP, Wolf FM et al. Effects of a decision support system on the diagnostic accuracy of users: a preliminary report. JAMIA 1996; 3:422–428.

    Article  PubMed  CAS  Google Scholar 

  45. Murphy GC, Friedman CP, Elstein AS. The influence of a decision support system on the differential diagnosis of medical practitioners at three levels of training. Proc AMIA Fall Symp Comput 1996: 219–223.

    Google Scholar 

  46. Lange LL, Haak SW, Lincoln MJ et al. Use of Iliad to improve diagnostic performance of nurse practitioner students. J Nurs Educ 1997; 36:36–45.

    PubMed  CAS  Google Scholar 

  47. Barnett GO, Cimino JJ, Hupp JA et al. DXplain—an evolving diagnostic decision-support system. JAMA 1987; 258:67–74.

    Article  PubMed  CAS  Google Scholar 

  48. Barnett GO, Hoffer EP, Packer MS et al. DXplain—demonstration and discussion of a diagnostic decision support system. Proc Annu Symp Comput Appl Med Care 1992:822.

    Google Scholar 

  49. Barnett GO. Information technology and medical education at Harvard Medical School. In: Salamon R, Protti D, Moehr J, eds. Proceedings Medical Informatics & Education International Symposium. Victoria B.C.: International Medical Informatics Association, 1989:3–5.

    Google Scholar 

  50. Barnett GO. Information technology and medical education. JAMIA 1995;2:285–291.

    Article  PubMed  CAS  Google Scholar 

  51. Frolich MW, Miller PL, Morrow JS. PATHMASTER: modelling differential diagnosis as “dynamic competition” between systematic analysis and disease-directed deduction. Comput Biomed Res 1990; 23:499–513.

    Article  Google Scholar 

  52. Fontaine D, Le Beux P, Riou C et al. An intelligent Computer-Assisted Instruction system for clinical case teaching. Methods Inf Med 1994; 33:433–445.

    PubMed  CAS  Google Scholar 

  53. Beck JR, O’Donnell JF, Hirai F et al. Computer-based exercises in anemia diagnosis (PlanAlyzer). Methods Inf Med 1989; 28:364–369.

    PubMed  CAS  Google Scholar 

  54. Lyon HC, Healy JC, Bell JR et al. PlanAlyzer, an interactive computer-assisted program to teach clinical problem solving in diagnosing anemia and coronary heart disease. Acad Med 1992; 67:821–828.

    Article  PubMed  Google Scholar 

  55. Franco A, King JD, Farr FL et al. An assessment of the radiological module of NEONATE as an aid in interpreting chest X-ray findings by nonradiologists. J Med Syst 1991; 15:277–286.

    Article  PubMed  CAS  Google Scholar 

  56. Mitchell JA, Lee AS, TenBrink T et al. AI/Learn: an interactive video-disk system for teaching medical concepts and reasoning. J Med Syst 1987; 11:421–429.

    Article  PubMed  CAS  Google Scholar 

  57. Console L, Molino G, Ripa di Meana V et al. LIED-Liver: information, education and diagnosis. Methods Inf Med 1989; 31:284–297.

    Google Scholar 

  58. Shortliffe EH. Computer-Based Medical Consultations: MYCIN. New York, NY: Elsevier Computer Science Library, Artificial Intelligence Series, 1976.

    Google Scholar 

  59. Hickam DH, Shortliffe EH, Bischoff MB et al. The treatment advice of a computer-based cancer chemotherapy protocol advisor. Ann Intern Med 1985; 103:928–936.

    Article  PubMed  CAS  Google Scholar 

  60. Siegal JA, Parrino TA. Computerized diagnosis: implications for clinical education. Med Educ 1988; 22:47–54.

    Article  Google Scholar 

  61. Lundsgaarde HP. Evaluating medical expert systems. Soc Sci Med 1987; 241:805–819.

    Article  Google Scholar 

  62. Berner ES, Webster GD, Shugerman AA et al. Performance of four computer-based diagnostic systems. N Engl J Med 1994; 330: 1792–1796.

    Article  PubMed  CAS  Google Scholar 

  63. Weed LL. Physicians of the future. N Engl J Med 1981; 304:903–907.

    Article  PubMed  CAS  Google Scholar 

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© 1999 Springer Science+Business Media New York

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Lincoln, M.J. (1999). Medical Education Applications. In: Berner, E.S. (eds) Clinical Decision Support Systems. Health Informatics. Springer, New York, NY. https://doi.org/10.1007/978-1-4757-3903-9_5

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  • DOI: https://doi.org/10.1007/978-1-4757-3903-9_5

  • Publisher Name: Springer, New York, NY

  • Print ISBN: 978-1-4757-3905-3

  • Online ISBN: 978-1-4757-3903-9

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