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The AHRQ has released a report (available here) on the implementation of clinical decision support (CDS) software within the context of an EMR. This report reviews the work to date of two AHRQ demonstration grant recipients, Brigham and Women’s Hospital and Yale University School of Medicine. In each of these projects the intent was, at least in part, to implement two or more existing practice guidelines as on line and integrated component of the EMR.

In the context of these projects CDS means the provision of clinical knowledge and patient-specific information to help make decisions that enhance patient care. While this type of general statement remains somewhat vague as to what constitutes such help, the report comments further that in a CDS “the patient’s information is matched to a clinical knowledge base, and patient-specific assessments or recommendations are then communicated effectively at appropriate times during patient care”.  Therefore, as used here, CDS is more than just the effective presentation of integrated patient information, as might be done by a Medical Device Data System (as discussed here) for example. Instead it is knowledge based and the relevant knowledge is used to compare a patient to a predefined pattern in order to “suggest” or “advise” (or “tell”) the clinician what course of treatment is to be followed.

In this regard a CDS is, in older and somewhat forgotten terminology, an expert system. Introduced in the late 1990’s,the idea of an expert system was that the knowledge and expertise of one or more human experts could be captured and implemented as a computer code. Once this code was written (and perhaps verified), it would be possible to enter a new situation within the domain of the expert system, and the expert system would then provide the same result as the original expert or experts. It was further believed that some expert systems could be written that could “learn” such that it actually became more expert than the original experts whose knowledge was tapped (by a knowledge engineer) in its original creation. Of course such learning could only occur if the expert system was given controlled feedback along with having a coding scheme that was self adjusting. Neural nets was one of the popular approaches to such learning. (more…)

Read More: http://feedproxy.google.com/~r/MedicalConnectivityConsulting/~3/t4ILgmIXhPk/