Enhancing patient care and treatment through explainable AI
Shyni Carmel Mary S, Dhyana Sharon Ross, Anbumani Bala, Joe Arun · Artificial Intelligence in Medicine · 2024
Artificial intelligence (AI) in healthcare is pivotal for advancing science and fostering a healthier society. Embracing mental, physical, preventive, and nutritional care, the key focus lies in enhancing patient care and treatment. AI excels in crucial healthcare tasks, including disease diagnosis and tumor identification, transforming treatment plan design based on patient data. Explainable Artificial Intelligence (XAI) is gaining prominence, acting as a conduit for effective AI integration into patient experience. This chapter explores XAI‘s impact on patient care quality, specifically Patient Expectation, Patient Perception, and Patient Experience, aiming to propose a Gap model assessing AI&s;s influence on healthcare service quality. Discussing the principles of AI in patient care, the chapter emphasizes the significance of understanding XAI, highlighting its tools and methods. Patient Experience (PE) is dissected into three aspects: Patient Expectation (PE), Patient Perception (PP), and Patient Experience (PEx) in pre–post-treatments. Variables impacting patient care expansion, including Access, Waiting, Information, Administration, Communication, Security, Satisfaction, and Ancillary Services, are identified according to XAI. The novel GAPs Model represents identified gaps in factors contributing to patient care, such as trained staff, service quality, equipment, medication, and technology. Through the application of XAI, these identified gaps can be narrowed, enhancing the influence of Explainable AI on Patient Expectation, Patient Perception, and Patient Experience in inpatient care and treatment. A survey of 150 medical professionals and 150 non-medical individuals around Chennai, India, using questionnaires, underscores the lack of awareness leading to hesitation and fear about AI-based treatment. This hampers feedback on service quality, reinforcing the critical role of Explainable AI in delivering optimal quality in tech-driven healthcare services.