Objective: The study sought to evaluate a novel electronic health record (EHR) add-on application for chronic disease management that uses an integrated display to decrease user cognitive load, improve efficiency, and support clinical decision making.
Materials and methods: We designed a chronic disease management application using the technology framework known as SMART on FHIR (Substitutable Medical Applications and Reusable Technologies on Fast Healthcare Interoperability Resources). We used mixed methods to obtain user feedback on a prototype to support ambulatory providers managing chronic obstructive pulmonary disease. Each participant managed 2 patient scenarios using the regular EHR with and without access to our prototype in block-randomized order. The primary outcome was the percentage of expert-recommended ideal care tasks completed. Timing, keyboard and mouse use, and participant surveys were also collected. User experiences were captured using a retrospective think-aloud interview analyzed by concept coding.
Results: With our prototype, the 13 participants completed more recommended care (81% vs 48%; P < .001) and recommended tasks per minute (0.8 vs 0.6; P = .03) over longer sessions (7.0 minutes vs 5.4 minutes; P = .006). Keystrokes per task were lower with the prototype (6 vs 18; P < .001). Qualitative themes elicited included the desire for reliable presentation of information which matches participants' mental models of disease and for intuitive navigation in order to decrease cognitive load.
Discussion: Participants completed more recommended care by taking more time when using our prototype. Interviews identified a tension between using the inefficient but familiar EHR vs learning to use our novel prototype. Concept coding of user feedback generated actionable insights.
Conclusions: Mixed methods can support the design and evaluation of SMART on FHIR EHR add-on applications by enhancing understanding of the user experience.
Keywords: SMART on FHIR; clinical; cognitive load; decision support systems; electronic health records; human-computer interaction.
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