Driving Patient Data With AI for Patient Care Path Optimization: A Theoretical Framework

Abstract

Background: Patient data and artificial intelligence are widely explored concepts for improving healthcare services. However, little is known about the application of lean thinking to quantify these two elements. Objective: The aim of this study is to develop a theoretical framework combining patient data and artificial intelligence, aimed at optimizing the care pathway by identifying the theories to be mobilized to address this issue. Methods: A systematic review of the literature was carried out. Inclusion criteria were that the article should focus on optimizing the patient's care pathway. Twenty articles were included. Results: The proposed framework can be used to create an overview of the potential of driving patient-related data with AI for optimizing the patient care pathway. Further research is needed to investigate the use of patient-related quantifications of this data. Conclusions: This research paper analyzes the application of artificial intelligence in data science to optimize patient care pathways.