A Conceptual Framework Architecture for AI-Based Remote Patient Monitoring in Diabetes (RPM-D): Gap Analysis and Feasibility Assessment

Author(s):

Mrinmoy Roy*, Savdeep Vasudeva and Mohit Jamwal

Diabetes management is not only disease management but lifestyle modification with a strong vigil on diet, exercise, habits, regular consultation with doctors, pre-diagnosis, and monitoring of self-vital health parameters. Several AI-powered Diabetes diagnostic systems are out on the market. However, the efficiency of the entire AI-based Smart Healthcare Monitoring or Diagnostic Eco-System for Non-Communicable Diseases such as Diabetes depends on User Experience (UX), Quality by Design (QD) and Patient/Customer Centric Design thinking. This research paper studies the RPM architecture through intelligent wearables, the universal portability of the application, and various user-centric vital health parameters which are existing and new to be incorporated. The RPM Architecture for Diabetes (RPM-D) has been prepared to take the view on the gap analysis through initial qualitative interviews of physicians and their patients, then constructed questionnaires taking a combined literature review and the interview data and online/offline survey done for multiple stakeholders to find out a robust framework of model and its feasibility, validity and hypothesis tested through Structure Equation Modelling in Smart PLS 4. Finally, an architecture based on the basic requirements of RPM-D with more information on patients’ needs is discussed.