Background: Traditional clinical decision support systems in Electronic Medical Records (EMR) use algorithms with inclusion/exclusion criteria to provide direction to clinicians. Improved systems for developing trustworthy guidelines (e.g. GRADE) typically include many weak recommendations unsuited for clear inclusion/exclusion criteria, and in which the right decision varies from patient to patient. Through PLUGGED-IN phase 1 we developed a conceptual framework and a guideline authoring/ publication platform to allow use of trustworthy guidelines directly as decision support in EMRs, not dependent on traditional algorisms. Our framework is based on a multilayered guideline presentation format developed together with the DECIDE project. At the center of this framework you find the structured clinicial questions (PICO).

Objectives: To implement and test our novel approach to decision support where relevant patient specific information is shown alongside evidence based recommendations in EMRs.

Methods: We used a web guideline published through the MAGIC (Making Grade the Irresistible Choice) application, which allowed our EMR partner to make use of it’s structured content, ontology-coded clinical questions (PICO questions) and recommendation-specific EMR elements.

Results: The EMR system was able to interact with the guideline and the PICO questions, suggest relevant recommendations displayed along with relevant patient specific information (lab tests, measurements, medications), and offer these to facilitate direct ordering. We will show real examples and live products.

Discussion: Results suggest we can offer a complementary approach to traditional algoritm-based systems that is compatible with a large number of EMRs. Implications for guideline developers/users PLUGGED-IN provides a model for direct use of guidelines and it’s underlying content as decision support in EMRs.