Generative AI for Clinical Communication, Healthcare Worker Wellbeing, and Patient Care

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Authors: Muaath I. Alsufi, Sana Alsayed, Muthafar Alsufi, Fares A. Qtaishat
Cited by: 0
References: 64

Abstract

Communication failures between physicians and nurses are considered as one of the main contributors to to preventable patient harm, often resulting in delayed interventions and compromised care. While Electronic Health Records (EHRs) aim to improve data accessibility, they currently demand excessive time and cognitive resources, leading to clinician fatigue and reduced patient interaction. This chapter explores the capabilities of Generative AI (GenAI) in natural language processing and speech recognition to enhance clinical collaboration. We examine GenAI applications in real-time note generation, standardized handovers, and care plans to prevent ambiguity. Furthermore, this chapter proposes a human-supervised clinical documentation model emphasizing safety, transparency, and ethical use. By reducing administrative burdens, GenAI functions as a collaborative partner that enables professionals to prioritize patient care, representing a vital evolution in team-based healthcare

Fields of Study & Subjects

Artificial Intelligence in Healthcare and Education Electronic Health Records Systems Nursing Diagnosis and Documentation

Publication details

Journal / source
Advances in computational intelligence and robotics book series
Pages
49–70
Publication date
4 March 2026
Language
EN
Document type
Book chapter