The Value of Assertiveness in Patient Care in Health Institutions Under the Expert Systems Approach

Abstract

Abstract Assertive communication between health professionals and patients plays a crucial role in the disease–health relationship, creating trust and loyalty while promoting health. A medical expert computer system that emulates human reasoning by acting as a human expert would do so to provide clinical decision support to physicians, patients, and others involved in health care. This research aims to analyse and develop a model of assertiveness in patient care in health institutions through Bayesian networks with machine learning techniques. For this, a model is created in which the critical factors that impact optimally managing assertive communication are identified and quantified, which allows health institutions to generate value for the patient through a service experience with humane treatment. The results show that the most relevant factors in managing assertive communication in health institutions are disease information, communication, human capital, medical team, health institution, continuity of care, patient safety, and patient rights. Furthermore, the evidence shows that the optimal or non-optimal management of assertive communication and its various processes, through the causality of the variables, allow the interrelation to be more adequately captured to manage it.

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