A Human-Centered Systems Approach to AI-Enhanced VR Training for Home-Based Peritoneal Dialysis

Abstract

Peritoneal Dialysis (PD) is a home-based therapy for kidney failure that requires patients to independently perform detailed sterile procedures, often several times per day. Even minor deviations in technique can lead to serious complications, including peritonitis and catheter failure. Although structured education programs are typically available, variations in training quality, health literacy, home environments, and patient confidence continue to contribute to preventable harm. Immersive Virtual Reality (VR) and Artificial Intelligence (AI) present promising opportunities to enhance PD education. However, their implementation must be grounded in patient safety principles and Systems Engineering approaches rather than driven solely by technological advancement. This paper presents a patient-focused, systems-based framework for AI-enhanced VR training in home PD, informed by human-centereddesign. The framework integrates realistic procedural simulations with AI-driven feedback on sequencing and sterile technique, while modeling the complete PD workflow within the home as a safety-critical care environment. Core elements include co-design with patients and PD nurses, identification of high-risk procedural steps, adaptation to varying literacy levels, transparent AI feedback mechanisms, and structured processes for ongoing monitoring and evaluation. Interdisciplinary collaboration among clinicians, human factors experts, AI developers, and patient representatives is essential to ensure safe, effective, and scalable implementation aimed at reducing preventable complications and strengthening patient confidence.