Published on in Vol 7, No 11 (2019): November

Impact of Social Determinants of Health and Demographics on Refill Requests by Medicare Patients Using a Conversational Artificial Intelligence Text Messaging Solution: Cross-Sectional Study

Impact of Social Determinants of Health and Demographics on Refill Requests by Medicare Patients Using a Conversational Artificial Intelligence Text Messaging Solution: Cross-Sectional Study

Impact of Social Determinants of Health and Demographics on Refill Requests by Medicare Patients Using a Conversational Artificial Intelligence Text Messaging Solution: Cross-Sectional Study

Journals

  1. Brar Prayaga R, Prayaga R. Mobile Fotonovelas Within a Text Message Outreach: An Innovative Tool to Build Health Literacy and Influence Behaviors in Response to the COVID-19 Pandemic. JMIR mHealth and uHealth 2020;8(8):e19529 View
  2. Tan M, Hatef E, Taghipour D, Vyas K, Kharrazi H, Gottlieb L, Weiner J. Including Social and Behavioral Determinants in Predictive Models: Trends, Challenges, and Opportunities. JMIR Medical Informatics 2020;8(9):e18084 View
  3. Krousel-Wood M, Craig L, Peacock E, Zlotnick E, O’Connell S, Bradford D, Shi L, Petty R. Medication Adherence: Expanding the Conceptual Framework. American Journal of Hypertension 2021;34(9):895 View
  4. Babel A, Taneja R, Mondello Malvestiti F, Monaco A, Donde S. Artificial Intelligence Solutions to Increase Medication Adherence in Patients With Non-communicable Diseases. Frontiers in Digital Health 2021;3 View
  5. Fu R, Xu H, Lai Y, Sun X, Zhu Z, Zang H, Wu Y. A VOSviewer-Based Bibliometric Analysis of Prescription Refills. Frontiers in Medicine 2022;9 View
  6. Levitz C, Kuo E, Guo M, Ruiz E, Torres-Ozadali E, Brar Prayaga R, Escaron A. Using Text Messages and Fotonovelas to Increase Return of Home-Mailed Colorectal Cancer Screening Tests: Mixed Methods Evaluation. JMIR Cancer 2023;9:e39645 View
  7. Lim Jit Fan C, Boon Kwang G, Chee Wing Ling V, Woh Peng T, Goh Qiuling B. Remodeling the Medication Collection Process With Prescription in Locker Box (PILBOX): Prospective Cross-sectional Study. Journal of Medical Internet Research 2022;24(6):e23266 View
  8. Ranchon F, Chanoine S, Lambert-Lacroix S, Bosson J, Moreau-Gaudry A, Bedouch P. Development of artificial intelligence powered apps and tools for clinical pharmacy services: A systematic review. International Journal of Medical Informatics 2023;172:104983 View
  9. Bohlmann A, Mostafa J, Kumar M. Machine Learning and Medication Adherence: Scoping Review. JMIRx Med 2021;2(4):e26993 View
  10. Aggarwal A, Tam C, Wu D, Li X, Qiao S. Artificial Intelligence–Based Chatbots for Promoting Health Behavioral Changes: Systematic Review. Journal of Medical Internet Research 2023;25:e40789 View
  11. Guo M, Brar Prayaga R, Levitz C, Kuo E, Ruiz E, Torres-Ozadali E, Escaron A. Tailoring a Text Messaging and Fotonovela Program to Increase Patient Engagement in Colorectal Cancer Screening in a Large Urban Community Clinic Population: Quality Improvement Project. JMIR Cancer 2023;9:e43024 View
  12. Bagheri A, Rouzi M, Koohbanani N, Mahoor M, Finco M, Lee M, Najafi B, Chung J. Potential applications of artificial intelligence and machine learning on diagnosis, treatment, and outcome prediction to address health care disparities of chronic limb-threatening ischemia. Seminars in Vascular Surgery 2023;36(3):454 View
  13. Larrain C, Torres-Hernandez A, Hewitt D. Artificial Intelligence, Machine Learning, and Deep Learning in the Diagnosis and Management of Hepatocellular Carcinoma. Livers 2024;4(1):36 View