Mitigating Cardiovascular Risk Through User Informed Clinical Decision Support

Abstract

As the volume of data within the electronic health record (EHR) increases, there is an evident need for user-friendly and efficient clinical decision support tools developed to assist with patient assessment. Risk calculators, specifically for atherosclerotic cardiovascular disease (ASCVD), are examples of surveillance tools that intend to quantify and predict patient risk of suffering a cardiovascular event. However, despite reported frequent use by clinicians, risk calculators exist largely outside of the EHR, requiring external navigation and increasing the likelihood of user error. Using a mixed methods approach to development, the present research mitigates the challenges posed by external surveillance platforms and discusses the process of designing and optimizing a clinical tool intended to address ASCVD risk at the point of care. These methods ultimately resulted in a risk calculator with both provider- and patient-facing platforms, data autopopulating functionality, and customizable and flexible integration within the provider’s EHR workflow.