Beta Testing a Novel Smartphone Application to Improve Medication Adherence

Abstract

We developed and beta-tested a patient-centered medication management application, PresRx optical character recognition (OCR), a mobile health (m-health) tool that auto-populates drug name and dosing instructions directly from patients' medication labels by OCR. We employed a single-subject design study to evaluate PresRx OCR for three outcomes: (1) accuracy of auto-populated medication dosing instructions, (2) acceptability of the user interface, and (3) patients' adherence to chronic medications. Eight patients beta-tested PresRx OCR. Five patients used the software for ≥6 months, and four completed exit interviews (n = 4 completers). At baseline, patients used 3.4 chronic prescription medications and exhibited moderate-to-high adherence rates. Accuracy of auto-populated information by OCR was 95% for drug name, 98% for dose, and 96% for frequency. Study completers rated PresRx OCR 74 on the System Usability Scale, where scores ≥70 indicate an acceptable user interface (scale 0-100). Adherence rates measured by PresRx OCR were high during the first month of app use (93%), but waned midway through the 6-month testing period (78%). Compared with pharmacy fill rates, PresRx OCR underestimated adherence among completers by 3%, while it overestimated adherence among noncompleters by 8%. Results suggest smartphone applications supporting medication management are feasible and accurately assess adherence compared with objective measures. Future efforts to improve medication-taking behavior using m-health tools should target specific patient populations and leverage common application programming interfaces to promote generalizability. Our medication management application PresRx OCR is innovative, acceptable for patient use, and accurately tracks medication adherence.