Beta Testing a Novel Smartphone Application to Improve Medication Adherence

التفاصيل البيبلوغرافية
العنوان: Beta Testing a Novel Smartphone Application to Improve Medication Adherence
المؤلفون: Megha Tewari, Erin Sarzynski, Angie C. Kennedy, Aaron Thul, Charles W. Given, Brian Decker, Michael H. Zaroukian, David Weismantel, Kristy Beckholt, Ronald Melaragni, Elizabeth Cholakis
المصدر: Telemedicine journal and e-health : the official journal of the American Telemedicine Association. 23(4)
سنة النشر: 2016
مصطلحات موضوعية: Adult, Male, medicine.medical_specialty, 020205 medical informatics, Health information technology, Medication adherence, Health Informatics, 02 engineering and technology, Smartphone application, Beta testing, computer.software_genre, Medication Adherence, 03 medical and health sciences, User-Computer Interface, 0302 clinical medicine, Physical medicine and rehabilitation, Health Information Management, Software Design, 0202 electrical engineering, electronic engineering, information engineering, Medicine, Humans, 030212 general & internal medicine, Dosing, Medical prescription, business.industry, System usability scale, General Medicine, Optical character recognition, Middle Aged, Mobile Applications, Physical therapy, Feasibility Studies, Female, Smartphone, business, computer
الوصف: 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.
تدمد: 1556-3669
URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::191d78afa5e5a2ac2cc7dc381c868442
https://pubmed.ncbi.nlm.nih.gov/27564971
Rights: CLOSED
رقم الانضمام: edsair.doi.dedup.....191d78afa5e5a2ac2cc7dc381c868442
قاعدة البيانات: OpenAIRE