Designing a computerized decision support system for asthma chronic disease management in community pharmacies

Introduction: We previously built and validated the Electronic Asthma Management System (eAMS) - a clinic-based asthma computerized clinical decision support system (CDSS) which is in clinical use. Aim: Herein, we sought to adapt and optimize the eAMS for implementation in community pharmacy practice. Methods: We iteratively developed a system prototype (the eAMS- Pharm ) with input from clinical pharmacists, and asthma, knowledge translation, and eHealth experts. After face-validation by three external community pharmacists, we used a rapid-cycle development process for optimization of system functionality/design, content, and user workflows. This involved a sequential and repeated three-stage process: (1) system prototype demonstration and testing in 90 minute, semi-structured virtual focus groups with target end-users; (2) analysis of focus group findings; and (3) corresponding modifications to the prototype, then re-testing in another focus group. This process continued until we reached pre-defined stopping criteria. We used a questionnaire to gather demographic information and further usability data and feedback. Community pharmacy team members were recruited from an existing pharmacy database. Results: Stopping criteria were met after six focus group cycles with 28 participants [23 (83%) pharmacists, 4 (14%) registered pharmacy technicians/assistants, and 1 (3%) pharmacy student]. User feedback and corresponding system improvements spanned usability, workflow, and prescriber communication domains. The optimized system consisted of a pharmacy portal with a patient dashboard, patient and provider versions of a point-of-care questionnaire, an interactive CDSS producing guideline-based recommendations, automated documentation, and pre-formatted prescriber communications. The System Usability Scale score was 82.9 ± 16.8 (maximum 100), and user responses to Likert scale-based assessments of eAMS-Pharm format, content, workflow, impact, and overall impressions were highly favorable. Conclusion: We built and optimized a chronic disease CDSS for use in community pharmacies, identifying and addressing pharmacy-specific barriers to implementation. The system achieved a high system usability score and highly favorable ratings for perceived system benefits, likelihood of clinical use, and patient benefits. The eAMS-Pharm can now be evaluated for uptake, care impact, and outcome impact in real-world settings. Our findings surrounding users’ usability, workflow, and content preferences, and our unique development strategy, can also inform future pharmacy-based chronic disease CDSS design.