In 2009 we conceived the idea of using structured electronic recommendations directly as decision support, bypassing the tedious work of converting unstructured guideline texts into actionable decision support elements. We wanted to combine the methodological rigor and quality of GRADE guidelines, with the personalization possibilities of decision support systems.
A recurrent theme in existing decision support systems is the difficulty in using general advice from guidelines to make specific and targeted advice for single patients and the time consuming and resource demanding processes to do so. We looked through research done and systems developed, and that made us concerned about the rate at which the advice in decision support systems were updated. Most of the CDSS we looked at were based on existing content, tailored to its need, and this most often meant taking the advice from a published text guideline, into an electronic format, away from it’s original place of publishing. There seemed to be a lack of links between the update frequency of the textual guidelines the CDSS was based on, and the advice presented to clinicians in the CDSS.
We wanted to develop an approach that would alleviate these barriers, while keeping up the methodological rigor from GRADE (and later the IOM criteria for trustworthy guidelines) in addition to allow personalization and linkage to patient specific information the EHR. The solution we developed was reliant on moving guidelines from a text-based format to an electronic structure.
We have implemented this new approach into our MAGIC authoring and publication platform for guidelines: MAGICapp.
Read more about the technical aspects of the PLUGGED IN approach.
(blue in the screenshots below signify information from the recommendation, used by the EMR to contextualize content presentation)