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Design and Implementation Issues

  • Jerome H. Carter
Part of the Health Informatics book series (HI)

Abstract

The early 1970s were a time of great optimism for researchers in the field of medical artificial intelligence. The initial successes of systems such as MYCIN,1 CASNET,2 and the Leeds abdominal pain system3 made it reasonable to assume that it was only a matter of time until computers became a standard part of physicians’ diagnostic armamentarium. Over the past few years, the emphasis in clinical decision support has shifted from its initial narrow focus on diagnostic expert systems to a much broader range of applications. Increasingly, clinicians have access to alerts, reminders, and patient-specific advice for such common tasks as prescription writing and test ordering.4,5,6,7 Despite these gains, CDSS are not yet common in patient care settings.8 This chapter will examine the key design and implementation concerns that must be addressed if these systems are to realize their full potential.

Keywords

Clinical Decision Support Mean Corpuscular Volume Pernicious Anemia Clinical Decision Support System Computerize Physician Order Entry 
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.

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Copyright information

© Springer Science+Business Media, LLC 2007

Authors and Affiliations

  • Jerome H. Carter
    • 1
  1. 1.Department of Medical EducationMorehouse School of MedicineAtlantaUSA

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