Abstract
We commend Shiffman and colleagues (“Bridging the Guideline Implementation Gap: A Systematic, Document-Centered Approach to Guideline Implementation”1) for highlighting the challenges of integrating guidelines into clinical practice and proposing pragmatic mechanisms for addressing them. We note, however, that the approach advocated by Shiffman et al., as well as by numerous other groups recently,2–8 is fundamentally a document-centric model. This approach may lead others to assume that representing a guideline correctly as a “computer-readable” document is the majority of the work required for implementation success. Although the “understanding” and representation of the clinical content of a guideline are a sine qua non for its local implementation, the document-centric approach leaves a substantial gap between the idealized document model and any specific guideline implementation in a local clinical system. This considerable gap is not unlike the “curly braces” problem documented for the Arden Syntax a decade ago.3–5 We estimate that 90% of the effort required for successful guideline implementation is (and must be) local, and the remaining 10% of the effort involves “getting the document right.” We believe that an alternative approach to local guideline implementation is to focus on the guideline's recommended actions; on the capabilities of the local care provider order entry (CPOE) or electronic health record (EHR) system that will serve as the “effector mechanism” for the guideline; on locally available computational and clinical resources; and on the guideline's required “clinical infrastructure.” We believe that guidelines should be implemented locally and directly (with a systematic approach, as described below) via local clinical systems (as opposed to a quasi-automatic implementation using a computer-readable, nationally disseminated document). The goal of both the “document-centric” and the “locally customized and guided” approaches is the same: implementation of locally effective guidelines that appropriately influence clinical decision making, …
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More From: Journal of the American Medical Informatics Association
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