Designing a Decision Support System for Tailored eHealth Solutions in Patient Care

While clinicians rely on clear guidelines to determine the best conventional medical treatments for individual patients, the integration of digital healthcare presents unique challenges. There is currently no structured approach to help clinicians identify the most suitable digital health solutions for their patients. This gap complicates efforts to address individual patient needs and ensure the effective adoption of digital health technologies. To create a patient-centered approach, it is essential to understand the individual barriers patients face when using digital tools. These may include access to the internet, attitudes toward technology, fears related to privacy, impairing physical problems, and the availability of support in case of technical difficulties. By gathering data through qualitative interviews (n=10), focus groups (n=9), and questionnaires (n=500), this project aims to develop a decision tree that guides clinicians in identifying the most appropriate digital healthcare approach for individual patients. The decision tree will involve answering a limited set of questions about the patient’s demographics, attitudes, prior experience with technology, and potential barriers. Based on these responses, the system will provide tailored recommendations on feasible digital tools and necessary support options. The ultimate goal is to empower clinicians to incorporate digital health solutions into patient care effectively and equitably. This abstract seeks input from healthcare professionals on how such a decision tool might work in practice. Specifically, should it take the form of a paper-based tool or an online platform? What practical considerations should be taken into account? How many questions are feasible? How to evaluate the feasibility?