EHR Nudges: Optimizing a Clinical Decision Support System for Evidence-Based Statin Medication Prescribing to Reduce the Risk of Cardiovascular Disease - PROJECT ABSTRACT Statins reduce the risk of major adverse cardiovascular events and mortality. However, providers fail to prescribe statin therapy for about half of patients meeting guideline criteria for initiation. The electronic health record (EHR) creates opportunities to develop clinical decision support systems (CDSSs) to support cardiovascular disease (CVD) risk recognition, assessment, and management. However, low provider adoption has limited the clinical impact of CDSSs designed to improve guideline-concordant statin prescribing. Integrating insights from behavioral economics into CDSS design represents a novel approach to improving adoption by minimizing key barriers - provider time and cognitive load burden. Behavioral economics studies the effects of psychological, social, cognitive, and emotional factors on the decisions of individuals and uses nudges to influence behavior at a largely unconscious level. Nudges are defined as positive reinforcement and indirect suggestions which have a non-forced effect on decision-making. For example, “opt-out” options for organ donation consent lead to striking differences in enrollment. Nudges represent an exciting and novel approach to developing CDSSs that minimize provider burden and are, therefore, more efficient, scalable, and impactful (i.e., optimized). The overall objective of this proposal is to develop and optimize a CDSS, including several nudges, to increase guideline-concordant statin prescribing for CVD risk (Nudge-CVD-CDSS). We use an innovative, engineering-inspired multiphase optimization strategy (MOST) framework to arrive at an intervention that is not just efficacious or effective but efficient and scalable. Several potential intervention components (EHR-nudges) will be developed, usability tested, revised, and evaluated. A randomized trial using a specialized design will evaluate the individual and combined effects of nudges. We will seek the combination of nudges that maximizes impact on guideline-concordant statin prescribing while minimizing provider time and cognitive load burden. Specific Aims: 1) To develop, based on a conceptual model of the prescribing process, a set of potential intervention components (EHR-nudges) to promote and support AHA/ACC guideline-concordant statin prescribing, 2) To revise potential intervention components through iterative usability testing, including real-time measures of provider time and cognitive load burden and 3) To use a randomized trial with a specialized design to identify which EHR-nudges, or combinations of nudges, contribute most efficiently to AHA/ACC guideline-concordant statin prescribing. The proposed work is significant in its efforts to develop an effective, efficient, and scalable intervention to improve guideline- concordant care for CVD risk management. It is innovative in its use of insights from behavioral economics and the MOST framework to optimize a CDSS by balancing clinical impact with provider time and cognitive load burden. Achieving the project’s objectives will advance the science of CDSS design and development.
