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

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Healthcare Information Management Systems

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

Abstract

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.

If used properly, Clinical Decision Support Systems have the potential to change the way medicine has been taught and practiced.

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References

  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. Institute of Medicine. Crossing the quality chasm: a new health system for the 21st century. Washington, DC: National Academy Press; 2001.

    Google Scholar 

  3. The Leapfrog Group. www.leapfroggroup.org.

    Google Scholar 

  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.

    Article  Google Scholar 

  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. DeGruy KB. Healthcare applications of knowledge discovery in databases. J Healthcare Inform Manag 2000; 14 (2): 59–69.

    CAS  Google Scholar 

  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. Metzger J, MacDonald, K. Clinical decision support for the independent physician practice. California Healthcare Foundation; 2002.

    Google Scholar 

  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.

    Article  PubMed  CAS  Google Scholar 

  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.

    Article  PubMed  CAS  Google Scholar 

  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.

    PubMed  CAS  Google Scholar 

  12. Miller RA, Masarie FE Jr. The demise of the “Greek Oracle” model for medical diagnostic systems. Methods Inform Med 1990; 29: 1–2.

    CAS  Google Scholar 

  13. Tan JKH, Sheps S. Health decision support systems. Gaithersburg: Aspen; 1998.

    Google Scholar 

  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. Shabot MM, LoBue M, Chen J. Wireless clinical alerts for physiologic, laboratory and medication data. Proc AMIA Symp 2000; 789–793.

    Google Scholar 

  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. 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. 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. BMJ.com 2002.

    Google Scholar 

  19. Marakas GM. Decision support systems in the 21st century. Upper Saddle River, NJ: Prentice Hall; 1999.

    Google Scholar 

  20. Devillers J, editor. Neural networks in QSAR and drug design. London: Academic Press; 1996.

    Google Scholar 

  21. Hirshberg A, Adar R. Artificial neural networks in medicine. Isr J Med Sci 1997; 33 (10): 700–702.

    PubMed  CAS  Google Scholar 

  22. Cross S, Harrison R, Kennedy RL. Introduction to neural networks. Lancet 1995; 346: 1075–1079.

    Article  PubMed  CAS  Google Scholar 

  23. Baxt WG. Application of artificial neural networks to clinical medicine. Lancet 1995; 346: 1135–1138.

    Article  PubMed  CAS  Google Scholar 

  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.

    Article  CAS  Google Scholar 

  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.

    Article  PubMed  Google Scholar 

  26. Naguib RNG, Sherbet GV, editors. Artificial neural networks in cancer diagnosis, prognosis, and patient management. Boca Raton: CRC Press; 2001.

    Google Scholar 

  27. Levin M. Use of genetic algorithms to solve biomedical problems. MD Comput 1995; 12 (3): 193–199.

    PubMed  CAS  Google Scholar 

  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.

    CAS  Google Scholar 

  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.

    Article  PubMed  CAS  Google Scholar 

  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.

    Article  PubMed  CAS  Google Scholar 

  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.

    Article  PubMed  CAS  Google Scholar 

  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.

    Article  PubMed  Google Scholar 

  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.

    Article  PubMed  CAS  Google Scholar 

  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.

    Article  PubMed  CAS  Google Scholar 

  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.

    Article  PubMed  CAS  Google Scholar 

  36. Doolan DF, Bates DW. Computerized physician order entry systems in hospitals: mandates and incentives. Health Affairs 2002; 21 (4): 180–188.

    Article  PubMed  Google Scholar 

  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. 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.

    Article  PubMed  CAS  Google Scholar 

  39. Kaplan B. Evaluating informatics applications: clinical decision support systems literature review. Int J Med Inform 2001; 64: 15–37.

    Article  PubMed  CAS  Google Scholar 

  40. de Dombal FT. The diagnosis of acute abdominal pain with computer assistance: worldwide perspective. Ann Chir 1991; 45: 273–277.

    PubMed  Google Scholar 

  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.

    Article  CAS  Google Scholar 

  42. KLAS Research and Consulting Firm. CPOE digest (computerized physician order entry). KLAS Enterprises, LLC; 2003.

    Google Scholar 

  43. Covell DG, Uman GC, Manning PR. Information needs in office practice: are they being met? Ann Intern Med 1985; 103: 596–599.

    PubMed  CAS  Google Scholar 

  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.

    Article  CAS  Google Scholar 

  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. 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.

    CAS  Google Scholar 

  47. Turisco F, Case J. Wireless and mobile computing. California Healthcare Foundation; 2001.

    Google Scholar 

  48. Morris AH. Decision support and safety of clinical environments. Qual Saf Health Care 2002; 11 (1): 69–75.

    Article  PubMed  CAS  Google Scholar 

  49. Weed LL, Weed L. Opening the black box of clinical judgment—an overview. BMJ 1999;319:1279. Data supplement—complete version. http://www.bmj.org/cgi/content/full/ 319/7220/1279/DC1.

    Google Scholar 

  50. The T.J. Hooper. 60 F.2d 737 (2d Cir. 1932 ).

    Google Scholar 

  51. Osler, Harkins & Harcourt Law Firm. Ten commandments of computerization. Reprinted by permission by the Canadian Information Processing Society; 1992. http://www.cips.ca/it/ resources/default.asp?load=practices.

    Google Scholar 

  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. Brannigan VM, Dayhoff RE. Medical informatics. The revolution in law, technology and medicine. J Legal Med 1986; 7 (1): 53.

    Article  Google Scholar 

  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.

    Article  PubMed  CAS  Google Scholar 

  55. Kittelson B. Spotlight: CPR systems. Healthcare Inform 2002; 18 (5): 41–47.

    Google Scholar 

  56. The 2002 Healthcare Informatics 100. Healthcare Inform 2002; 18 (6): 33–64.

    Google Scholar 

  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.

    PubMed  CAS  Google Scholar 

  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. 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.

    PubMed  CAS  Google Scholar 

  60. Fried BM, Zuckerman JM. FDA regulation of medical software. J Health Law 2000; 33 (1): 129–140.

    PubMed  CAS  Google Scholar 

  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.

    Article  PubMed  CAS  Google Scholar 

  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 

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Author information

Authors and Affiliations

  1. Health Informatics in the Department of Health Services Administration , University of Alabama, Birmingham, UK

    Eta S. Berner EdD (Professor) & Tonya La Lande (School of Health Related Professions at the University of Alabama at Birmingham)

Authors
  1. Eta S. Berner EdD
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  2. Tonya La Lande
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Editor information

Editors and Affiliations

  1. Clinical Informatics Strategies, Healthlink Incorporated, Baltimore, MD, USA

    Marion J. Ball EdD (Vice President, Adjunct Professor) (Vice President, Adjunct Professor)

  2. School of Nursing, Johns Hopkins University, Baltimore, MD, USA

    Marion J. Ball EdD (Vice President, Adjunct Professor) (Vice President, Adjunct Professor)

  3. Cerner Corporation, Kansas City, MO, USA

    Charlotte A. Weaver (CNO and Vice President of Patient Care Systems) (CNO and Vice President of Patient Care Systems)

  4. Department of Health Management Systems John G. Rangos, Sr., School of Health Sciences, Duquesne University, Pittsburgh, PA, USA

    Joan M. Kiel PhD, MPA, MPhil (Chairman) (Chairman)

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Berner, E.S., Lande, T.L. (2004). Clinical Decision Support Systems: Impacting the Future of Clinical Decision Making. In: Ball, M.J., Weaver, C.A., Kiel, J.M. (eds) Healthcare Information Management Systems. Health Informatics Series. Springer, New York, NY. https://doi.org/10.1007/978-1-4757-4041-7_36

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  • DOI: https://doi.org/10.1007/978-1-4757-4041-7_36

  • Publisher Name: Springer, New York, NY

  • Print ISBN: 978-1-4419-2350-9

  • Online ISBN: 978-1-4757-4041-7

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