Improving Medical Adherence Using Machine Learning Tools and Human Computer Interaction

Abstract: Medication adherence usually refers to whether patients take their medications as prescribed (eg, twice daily), as well as whether they continue to take a prescribed medication. Medication non adherence is a growing concern to clinicians, healthcare systems, and other stakeholders (e.g., payers) because of mounting evidence that it is prevalent and associated with adverse outcomes and higher costs of care. Engaging patients and the healthcare team is essential to success in achieving medical adherence and persistence. Notable interventions include face-to-face counseling, reminders, regimen simplification, providing cost incentives or savings, and maintaining ongoing communication. This paper provides a review on current challenges faced in medication adherence. The current work aims to design an application that improves medical adherence by reading medical prescriptions of patient from prescription image, searching and extracting the information of the medicine from World Wide Web and providing the information, reminders to patient at regular intervals. The application also uses rewarding techniques to encourage the patient to medical adherence.

Keywords: Primary Non Adherence, Secondary Non Adherence, Intentional Non Adherence, Unintentional non-adherence, Google ML Kit, HCI (Human Computer Interaction)