Background: Integration of evidence into practice is suboptimal. Clinical pathways, defined as multidisciplinary care plans, are a method for translating evidence into local settings and have been shown to improve the value of patient care.
Objective: To describe the development of a clinical pathways programme across a large academic healthcare system.
Methods: We use a 10-step framework (grounded in the Knowledge-to-Action framework and ADAPTE Collaboration methodology for guideline adaptation) to support pathway development and dissemination, including facilitating clinical owner and stakeholder engagement, developing pathway prototypes based on rapid reviews of the existing literature, developing tools for dissemination and impact assessment. We use a cloud-based technology platform (Dorsata, Washington, DC) to assist with development and dissemination across our geographically distributed care settings and providers. Content is viewable through desktop and mobile applications. We measured programme adoption and penetration by examining number of pathways developed as well as mobile application use and pathway views.
Results: From 1 February 2016 to 30 April 2018, a total of 202 pathways were disseminated. The three most common clinical domains represented were oncology (46.5%, n=94), pulmonary/critical care (8.9%, n=18) and cardiovascular medicine (7.4%, n=15). Users opting to register for a personal account totalled 1279; the three largest groups were physicians (45.1%, n=504), advanced practice providers (19.5%, n=245) and nurses (19.1%, n=240). Pathway views reached an average of 2150 monthly views during the last 3 months of the period. The majority of pathways reference at least one evidence-based source (93.6%, n=180).
Conclusions: A healthcare system can successfully use a framework and technology platform to support the development and dissemination of pathways across a multisite institution.
Keywords: clinical decision support; clinical pathway; dissemination and implementation; evidence based medicine; evidence-based framework; quality improvement.
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