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Journal of the American Medical Informatics Association 5:237-244 (1998)
© 1998 American Medical Informatics Association


Application of Information Technology

A Template-based Approach to Support Utilization of Clinical Practice Guidelines Within an Electronic Health Record

Suzanne Bakken Henry, RN, DNSc, Kathy Douglas, RN, MHA, Grace Galzagorry, RN, MS, ANP, Anne Lahey, LVN and William L. Holzemer, RN, PhD

Affiliations of the authors: University of California, San Francisco (SBH, GG, WLH); Oceania Inc., Palo Alto, California (KD, AL).

Correspondence and reprints: Suzanne Bakken Henry, RN, DNSc, Department of Community Health Systems, School of Nursing, University of California, San Francisco, CA 94143-0608. e-mail: <sbhenry{at}itsa.ucsf.edu>.

Abstract Practice guidelines are an integral part of evidence-based health care delivery. When the authors decided to install the clinical documentation component of an electronic health record in a nurse practitioner faculty practice, however, they found that they lacked the resources to integrate it immediately with other systems and components that would support the processing of clinical rules. They were thus challenged to devise an initial approach for decision support related to clinical practice guidelines that did not include interfacing with an inference engine and set of decision rules. The authors developed a prototypic application within the WAVE electronic health record that demonstrates the feasibility of representing a guideline as structured encoded text organized into an online patient-encounter template. Although this approach may be more broadly applicable, it is described within the context of the management of diabetes mellitus by nurse practitioners. The advantages of the approach relate primarily to the integration of the guideline recommendations with the encounter form, the online interaction of the clinician with the system, and the ease of creation and modification of the guideline-based encounter form. However, there are several limitations of the current approach as a result of the inability to do inference and the lack of integration with patient-specific data to trigger specific rules.




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