Clinical Decision Support Systems: Impacting the Future of Clinical Decision Making

  • Eta S. Berner
  • Tonya La Lande
Part of the Health Informatics Series book series (HI)


With the increased focus on the prevention of medical errors that has occurred since the publication of the landmark Institute of Medicine report, To Err Is Human, computer-based physician order entry (CPOE) systems have been proposed as a key element of systems approaches to improving patient safety [1–4]. While CPOE systems alone can eliminate several types of errors, their major impact will be when they are linked to clinical decision support systems. Clinical decision support systems (CDSS) are computer systems designed to influence clinician decision making about individual patients when these decisions are made. If used properly, they have the potential to change the way medicine has been taught and practiced. This chapter will illustrate several types of CDSS, summarize current data on the use and effect of CDSS in practice, and will provide guidelines for users to consider as these systems begin to be incorporated in commercial systems and implemented outside the research and development settings.


Decision Support System Clinical Decision Support System Computerize Physician Order Entry Healthcare Inform Proc Amia 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Kohn LT, Corrigan JM, Donaldson MS, editors.To err is human: building a safer health system. Committee on Quality Health Care in America, Institute of Medicine. Washington, DC: National Academy Press; 2000.Google Scholar
  2. 2.
    Institute of Medicine. Crossing the quality chasm: a new health system for the 21st century. Washington, DC: National Academy Press; 2001.Google Scholar
  3. 3.
    The Leapfrog Group. Scholar
  4. 4.
    Bates DW, Leape LL, Cullen DJ, et al. Effect of computerized physician order entry and a team intervention of prevention of serious medical errors. JAMA 1998; 28: 1311–1316.CrossRefGoogle Scholar
  5. 5.
    Oliveira, JO. A shotgun wedding: business decision support meets clinical decision support. J Healthcare Inform Manag 2002; 16 (4): 28–33.Google Scholar
  6. 6.
    DeGruy KB. Healthcare applications of knowledge discovery in databases. J Healthcare Inform Manag 2000; 14 (2): 59–69.Google Scholar
  7. 7.
    Perreault LE, Metzger JB. A pragmatic framework for understanding clinical decision support. In: Middleton B, editor. Clinical decision support systems. J Healthcare Inform Manag 1999;13(2):5–21.Google Scholar
  8. 8.
    Metzger J, MacDonald, K. Clinical decision support for the independent physician practice. California Healthcare Foundation; 2002.Google Scholar
  9. 9.
    Shortliffe EH, Axline SG, Buchanan BG, Merigan TC, Cohen SN. An artificial intelligence program to advise physicians regarding antimicrobial therapy. Comput Biomed Res 1973; 6 (6): 544–560.PubMedCrossRefGoogle Scholar
  10. 10.
    Miller RA, Pople HE Jr, Myers JD. Internist-I, an experimental computer-based diagnostic consultant for general internal medicine. N Engl J Med 1982; 307: 468–476.PubMedCrossRefGoogle Scholar
  11. 11.
    Miller R, McNeil M, Challinor S, Masarie F, Myers J. The Internist-1/Quick Medical Reference project: status report. West J Med 1986; 145: 816–822.PubMedGoogle Scholar
  12. 12.
    Miller RA, Masarie FE Jr. The demise of the “Greek Oracle” model for medical diagnostic systems. Methods Inform Med 1990; 29: 1–2.Google Scholar
  13. 13.
    Tan JKH, Sheps S. Health decision support systems. Gaithersburg: Aspen; 1998.Google Scholar
  14. 14.
    Kuperman GJ, Teich JM, Bates DW, et al. Detecting alerts, notifying the physician, and offering action items: a comprehensive alerting system. Proc AMIA Symp 1996; 704–708.Google Scholar
  15. 15.
    Shabot MM, LoBue M, Chen J. Wireless clinical alerts for physiologic, laboratory and medication data. Proc AMIA Symp 2000; 789–793.Google Scholar
  16. 16.
    Geissbuhler A, Miller RA. Clinical application of the UMLS in a computerized order entry and decision-support system. Proc AMIA Symp 1998; 320–324.Google Scholar
  17. 17.
    Galanter WL, DiDomenico RJ, Polikaitis A. Preventing exacerbation of an ADE with automated decision support. J Healthcare Inform Manag 2002; 16 (4): 44–49.Google Scholar
  18. 18.
    Eccles M, McColl E, Steen N, et al. Effect of computerised evidence based guidelines on management of asthma and angina in adults in primary care: cluster randomised controlled trial. 2002.Google Scholar
  19. 19.
    Marakas GM. Decision support systems in the 21st century. Upper Saddle River, NJ: Prentice Hall; 1999.Google Scholar
  20. 20.
    Devillers J, editor. Neural networks in QSAR and drug design. London: Academic Press; 1996.Google Scholar
  21. 21.
    Hirshberg A, Adar R. Artificial neural networks in medicine. Isr J Med Sci 1997; 33 (10): 700–702.PubMedGoogle Scholar
  22. 22.
    Cross S, Harrison R, Kennedy RL. Introduction to neural networks. Lancet 1995; 346: 1075–1079.PubMedCrossRefGoogle Scholar
  23. 23.
    Baxt WG. Application of artificial neural networks to clinical medicine. Lancet 1995; 346: 1135–1138.PubMedCrossRefGoogle Scholar
  24. 24.
    Holst H, Astrom K, Jarund A, et al. Automated interpretation of ventilation-perfusion lung scintigrams for the diagnosis of pulmonary embolism using artificial neural networks. Eur J Nuclear Med 2000; 27 (4): 400–406.CrossRefGoogle Scholar
  25. 25.
    Olsson SE, Ohlsson M, Ohlin H, Edenbrandt L. Neural networks—a diagnostic tool in acute myocardial infarction with concomitant left bundle branch block. Clin Physiol Funct Imaging 2002; 22 (4); 295–299.PubMedCrossRefGoogle Scholar
  26. 26.
    Naguib RNG, Sherbet GV, editors. Artificial neural networks in cancer diagnosis, prognosis, and patient management. Boca Raton: CRC Press; 2001.Google Scholar
  27. 27.
    Levin M. Use of genetic algorithms to solve biomedical problems. MD Comput 1995; 12 (3): 193–199.PubMedGoogle Scholar
  28. 28.
    Laurikkala J, Juhola M, Lammi S, Viikki K. Comparison of genetic algorithms and other classifications methods in the diagnosis of female urinary incontinence. Methods Inform Med 1999; 38: 125–131.Google Scholar
  29. 29.
    Evans RS, Pestotnik SL, Classen DC, et al. A computer-assisted management program for antibiotics and other antiinfective agents. N Engl J Med 1998; 338: 232–238.PubMedCrossRefGoogle Scholar
  30. 30.
    Teich JM, Merchia PR, Schimz JL, et al. Effects of computerized physician order entry on prescribing practices. Arch Intern Med 2000; 160: 2741–2747.PubMedCrossRefGoogle Scholar
  31. 31.
    Tierney WM, Miller ME, McDonald CJ. The effect on test ordering of informing physicians on the charges for outpatient diagnostic tests. N Engl J Med 1990; 322: 1499–1504.PubMedCrossRefGoogle Scholar
  32. 32.
    Doolan DF, Bates DW, James BC. The use of computers for clinical care: a case series of advanced U.S. sites. J Am Med Inform Assoc 2003; 10: 94–107.PubMedCrossRefGoogle Scholar
  33. 33.
    Berner ES, Maisiak RS, Cobbs CG,Taunton OD. Effects of a decision support system on physician diagnostic performance. J Am Med Inform Assoc 1999; 6: 420–427.PubMedCrossRefGoogle Scholar
  34. 34.
    Berner ES, Maisiak RS. Influence of case and physician characteristics on perceptions of decision support systems. J Am Med Inform Assoc 1999; 6: 428–434.PubMedCrossRefGoogle Scholar
  35. 35.
    Friedman CP, Elstein AE, Wolf FM, et al. Enhancement of clinicians’ diagnostic reasoning by computer-based consultation. A multisite study of 2 systems. JAMA 1999; 282: 1851–1856.PubMedCrossRefGoogle Scholar
  36. 36.
    Doolan DF, Bates DW. Computerized physician order entry systems in hospitals: mandates and incentives. Health Affairs 2002; 21 (4): 180–188.PubMedCrossRefGoogle Scholar
  37. 37.
    Wong HJ, Legnini MW, Whitmore HH. The diffusion of decision support systems in healthcare: are we there yet? J Healthcare Manag 2000;45(4):240–249; discussion 249–253.Google Scholar
  38. 38.
    Hunt D, Haynes R, Hanna S, Smith K. Effects of computer-based clinical decision support systems on physician performance and patient outcomes: a systematic review. JAMA 1998; 280 (15): 1339–1346.PubMedCrossRefGoogle Scholar
  39. 39.
    Kaplan B. Evaluating informatics applications: clinical decision support systems literature review. Int J Med Inform 2001; 64: 15–37.PubMedCrossRefGoogle Scholar
  40. 40.
    de Dombal FT. The diagnosis of acute abdominal pain with computer assistance: worldwide perspective. Ann Chir 1991; 45: 273–277.PubMedGoogle Scholar
  41. 41.
    Adams ID, Chan M, Clifford PC, et al. Computer aided diagnosis of acute abdominal pain: a multicentre study. Br Med J 1986; 293: 800–804.CrossRefGoogle Scholar
  42. 42.
    KLAS Research and Consulting Firm. CPOE digest (computerized physician order entry). KLAS Enterprises, LLC; 2003.Google Scholar
  43. 43.
    Covell DG, Uman GC, Manning PR. Information needs in office practice: are they being met? Ann Intern Med 1985; 103: 596–599.PubMedGoogle Scholar
  44. 44.
    Gorman PN, Helfand M. Information seeking in primary care: how physicians choose which clinical questions to pursue and which to leave unanswered. Med Decision Making 1995; 15: 113–119.CrossRefGoogle Scholar
  45. 45.
    Berner ES, Maisiak RS, Phelan ST, et al. Use of a diagnostic decision support system by internal medicine residents. Unpublished study.Google Scholar
  46. 46.
    Teich JM, Merchia PR, Schmiz JL, Kuperman GJ, Spurr CD, Bates DW. Effects of computerized physician order entry on prescribing practices Arch Intern Med 2000; 160 (18): 2741–2747.Google Scholar
  47. 47.
    Turisco F, Case J. Wireless and mobile computing. California Healthcare Foundation; 2001.Google Scholar
  48. 48.
    Morris AH. Decision support and safety of clinical environments. Qual Saf Health Care 2002; 11 (1): 69–75.PubMedCrossRefGoogle Scholar
  49. 49.
    Weed LL, Weed L. Opening the black box of clinical judgment—an overview. BMJ 1999;319:1279. Data supplement—complete version. 319/7220/1279/DC1.Google Scholar
  50. 50.
    The T.J. Hooper. 60 F.2d 737 (2d Cir. 1932 ).Google Scholar
  51. 51.
    Osler, Harkins & Harcourt Law Firm. Ten commandments of computerization. Reprinted by permission by the Canadian Information Processing Society; 1992. resources/default.asp?load=practices.Google Scholar
  52. 52.
    Terry NP. When the machine that goes “ping” causes harm: default torts rules and technologically-mediated health care injuries. St. Louis U Law 2002; 46: 37.Google Scholar
  53. 53.
    Brannigan VM, Dayhoff RE. Medical informatics. The revolution in law, technology and medicine. J Legal Med 1986; 7 (1): 53.CrossRefGoogle Scholar
  54. 54.
    Sim I, Gorman P, Greenes RA, et al. Clinical decision support for the practice of evidence-based medicine. J Am Med Inform Assoc 2001; 8: 527–534.PubMedCrossRefGoogle Scholar
  55. 55.
    Kittelson B. Spotlight: CPR systems. Healthcare Inform 2002; 18 (5): 41–47.Google Scholar
  56. 56.
    The 2002 Healthcare Informatics 100. Healthcare Inform 2002; 18 (6): 33–64.Google Scholar
  57. 57.
    Poikonen J. Arden syntax: the emerging standard language for representing medical knowledge in computer systems. Am J Health Syst Pharm 1997; 54 (3): 281–284.PubMedGoogle Scholar
  58. 58.
    Berner ES, Maisiak RS, Heudebert GR, Young KR Jr. Clinician performance and prominence of diagnoses displayed by a clinical diagnostic decision support system. Proceedings, AMIA Symposium; 2003.Google Scholar
  59. 59.
    Miller RA, Schaffner KF, Meisel A. Ethical and legal issues related to the use of computer programs in clinical medicine. Ann Intern Med 1985; 102: 529–536.PubMedGoogle Scholar
  60. 60.
    Fried BM, Zuckerman JM. FDA regulation of medical software. J Health Law 2000; 33 (1): 129–140.PubMedGoogle Scholar
  61. 61.
    Miller RA, Gardner RM. Recommendations for responsible monitoring and regulation of clinical software systems. American Medical Informatics Association, Computer-based Patient Record Institute, Medical Library Association, Association of Academic Health Science Libraries, American Health Information Management Association, American Nurses Association. J Am Med Inform Assoc 1997; 4 (6): 442–457.PubMedCrossRefGoogle Scholar
  62. 62.
    Berner ES, Kennedy JI, Blackwell G, et al. Use of computer-generated ECG reports by residents and faculty. Proceedings of the Nineteenth Annual Symposium of Computer Applications in Medical Care. Philadelphia: Hanley & Belfus; 1995. p. 953.Google Scholar

Copyright information

© Springer Science+Business Media New York 2004

Authors and Affiliations

  • Eta S. Berner
    • 1
  • Tonya La Lande
    • 1
  1. 1.Health Informatics in the Department of Health Services Administration University of AlabamaBirminghamUK

Personalised recommendations