Risk-Based Quality Assurance in Healthcare Software Platforms

Abstract

This paper presents a cybersecurity-aware, risk-based quality assurance (QA) methodology for healthcare software platforms. Building on the AI and IoT-enabled monitoring system introduced by Kothamali et al. [1], this study introduces a QA framework that dynamically prioritizes testing based on patient safety risk, system reliability, and real-time anomaly detection. The approach was validated on a clinical scheduling and monitoring platform, resulting in higher compliance with healthcare standards and reduced vulnerability exposure. The integration of risk modeling with AI-based QA mechanisms reaffirms the significance of Kothamali et al. [1] original architecture in building secure and effective healthcare systems.