A DIGITAL HEALTH BASED PERSONALIZED PREOPERATIVE PATIENT EDUCATION SYSTEM FOR PATIENTS UNDERGOING TAVI SURGERY

Abstract

Personalized Patient education is a critical factor in the healthcare service delivery as it contributes to better management of diseases and ultimately enhanced clinical outcomes. TAVI is a standard cardiac procedure for patients with severe aortic stenosis. TAVI is a minimally invasive procedure, however; this procedure is still associated with a number of considerable risks based on the condition of the patient before performing this procedure. To obtain an informed consent, it is important to appropriately inform patients and their families about the risks and benefits of TAVI. In this thesis, our research objective is to leverage digital health technologies to develop a “proof-of-concept” personalized preoperative patient education system for TAVI patients “TAVI System”. An iterative user-centered approach is used to develop the web-based TAVI system, and its knowledge content is based on digitized evidence and clinical expertise. We use a knowledge management approach to model, computerize, and integrate TAVI patient assessment to generate personalized educational messages for TAVI patients. For evaluating TAVI system, we used scenario-based evaluation to ensure the correctness of the outputs of the system based on the knowledge obtained from experts.