The GUIDES checklist: development of a tool to improve the successful use of guideline-based computerised clinical decision support

Background: Computerised decision support (CDS) based on trustworthy clinical guidelines is a key component of a learning healthcare system. Research shows that the effectiveness of CDS is mixed. Multifaceted context, system, recommendation and implementation factors may potentially affect the success of CDS interventions. This paper describes the development of a checklist that is intended to support professionals to implement CDS successfully. Methods: We developed the checklist through an iterative process that involved a systematic review of evidence and frameworks, a synthesis of the success factors identified in the review, feedback from an international expert panel that evaluated the checklist in relation to a list of desirable framework attributes, consultations with patients and healthcare consumers and pilot testing of the checklist. Results: We screened 5347 papers and selected 71 papers with relevant information on success factors for guideline-based CDS. From the selected papers, we developed a 16-factor checklist that is divided in four domains, i.e. the CDS context, content, system and implementation domains. The panel of experts evaluated the checklist positively as an instrument that could support people implementing guideline-based CDS across a wide range of settings globally. Patients and healthcare consumers identified guideline-based CDS as an important quality improvement intervention and perceived the GUIDES checklist as a suitable and useful strategy. Conclusions: The GUIDES checklist can support professionals in considering the factors that affect the success of CDS interventions. It may facilitate a deeper and more accurate understanding of the factors shaping CDS effectiveness. Relying on a structured approach may prevent that important factors are missed

Human Factors Based Recommendations for the Design of Medication Related Clinical Decision Support Systems (CDSS)

International audienceThis study is part of a research project aiming at developing advanced functions of medication related CDSS to support the monitoring of patients' therapeutic treatments based mainly on corresponding lab values. We adopted a user-centred approach to the design of these advanced CDSS functions. We collected existing recommendations in the literature and completed previous Human Factors (HF) field studies and analyses by focused observations and modeling. We present resulting HF based recommendations for the design of such advanced medication CDSS and focus more specifically on two innovative high level recommendations completing those already existing in the literature. For illustration purposes, an example of the operationalization of one of the recommendation is presented