An empirical review of models used to empower health care data sharing for efficient query processing operation.

As the healthcare industry increasingly combines data-driven approaches to improve patient care. Data sharing across different systems becomes difficult for effective decision-making. This paper offers a comprehensive empirical review of existing models that facilitate healthcare data sharing for efficient query processing operations. The study aims to investigate the four-core metrics of precision, accuracy, complexity, and scalability systematically comparing these models to understand their capabilities and limitations. comparative analysis reveals salient features of each model and offers insights into their relative merits and drawbacks. This paper not only serves as a guide to navigate the landscape of existing solutions but also provides customized recommendations on selecting the most suitable model(s) based on individual and combined metrics. findings are expected to cover the way for future research in this field and contribute to creating more robust, efficient, and interoperable healthcare data sharing systems. [ABSTRACT FROM AUTHOR]