RESUMO
BACKGROUND: 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. MATERIALS AND METHODS: 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. RESULTS: 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%. DISCUSSION: 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. CONCLUSIONS: Our medication management application PresRx OCR is innovative, acceptable for patient use, and accurately tracks medication adherence.
