A TEMPLATE-BASED APPROACH TO SUPPORT UTILIZATION OF CLINICAL-PRACTICEGUIDELINES WITHIN AN ELECTRONIC HEALTH RECORD

Citation
Sb. Henry et al., A TEMPLATE-BASED APPROACH TO SUPPORT UTILIZATION OF CLINICAL-PRACTICEGUIDELINES WITHIN AN ELECTRONIC HEALTH RECORD, Journal of the American Medical Informatics Association, 5(3), 1998, pp. 237-244
Citations number
49
Categorie Soggetti
Information Science & Library Science","Computer Science Interdisciplinary Applications","Medical Informatics","Computer Science Information Systems
ISSN journal
10675027
Volume
5
Issue
3
Year of publication
1998
Pages
237 - 244
Database
ISI
SICI code
1067-5027(1998)5:3<237:ATATSU>2.0.ZU;2-X
Abstract
Practice guidelines are an integral part of evidence-based health care delivery. When the authors decided to install the clinical documentat ion component of an electronic health record in a nurse practitioner f aculty 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 t o 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 tex t organized into an online patient-encounter template. Although this a pproach may be more broadly applicable, it is described within the con text of the management of diabetes mellitus by nurse practitioners. Th e advantages of the approach relate primarily to the integration of th e guideline recommendations with the encounter form, the online intera ction of the clinician with the system, and the ease of creation and m odification of the guideline-based encounter form. However, there are several limitations of the current approach as a result of the inabili ty to do inference and the lack of integration with patient-specific d ata to trigger specific rules.