Revolutionizing Healthcare Data Management: The Role of Artificial Intelligence in Transforming Health Information Systems and Optimizing Patient Care"

Abstract

Objective: Organizations operating 
within a core healthcare structure 
depend on practices in health 
information management to gather patient data and safeguard that 
information, along with overseeing data storage and retrieval 
processes. Healthcare facilities have begun to integrate AI and ML 
technologies into their data workflows to establish secure data 
systems that improve transparency while utilizing the benefits of 
these systems. This article demonstrates how artificial intelligence 
technologies enhance the precision of clinical diagnostics and 
treatment advancements by impacting the functions of data network 
systems.
Methods: A systematic review was performed using the 
databases PubMed, IEEE Xplore, and Scopus to collect articles 
published from January 2018 to August 2024. The study 
concentrated on the use of AI in health information 
management, emphasizing areas such as data analysis, 
predictive analytics, and privacy issues.
Results: Healthcare providers gain improved support in 
making decisions through artificial intelligence, as the system 
autonomously analyzes data to produce in-depth predictive 
insights. The adoption of AI technologies has significantly 
improved the accuracy of medical coding and the standard of 
clinical documentation, leading to better management of 
healthcare information.
Conclusion: Health information management improves its 
outcomes through artificial intelligence by increasing data 
accuracy as well as making better decisions and medical 
coding.