Mobile Medication Selector App for Symptom-Based Drug Selection

Details

This case study details a mobile medication selector app designed for use during a 'real symptomatic moment.' Existing tools were criticized for clumsy indication searching, missing contraindication checks, and unclear routing between OTC and Rx options. The developed solution, built with React Native for iOS and Android, addresses these gaps by providing several key features. These include symptom/condition-based drug search, contraindication and interaction checks against the patient profile, and appropriate OTC vs Rx routing tied to FHIR-backed metadata. Additional functionalities include a Mapbox pharmacy locator and secure favorites protected by biometrics. The core technical strength lies in using the FHIR backend. By linking the displayed contraindication signal directly back to the patient's electronic health record (FHIR record), the system establishes clinical trust, moving beyond simple catalog searching. This ensures that medication selection is based on the patient's unique context. The user experience (UX) is highly tuned for low-friction use—featuring large tap targets and plain language descriptions. This model demonstrates how mobile technology can provide evidence-based guidance in self-care scenarios, offering a robust framework for improving patient confidence and reducing ambiguous handoffs at the pharmacy level. Such an approach has significant relevance to Japanese healthcare IT, where supporting patients with reliable, context-aware medication information is crucial for safety and adherence.