DATA ANALYTICS FOR RESOURCE ALLOCATION IN HEALTH CARE SYSTEMS

*Arshiya Siddiqua and Kalakada Bhavya Sree

ABSTRACT

Resource allocation is a pivotal aspect of healthcare management, impacting patient outcomes, cost-efficiency, and overall system performance. With the advent of data analytics, healthcare organizations are increasingly turning to data-driven approaches to optimize resource allocation. This review article explores the multifaceted role of data analytics in healthcare resource allocation. We delve into the significance of resource allocation in healthcare, the diverse data sources available for analysis, and the various data analytics techniques applied, including descriptive, predictive, prescriptive analytics, and the integration of machine learning and artificial intelligence. Moreover, we examine emerging technologies such as big data analytics, genomics, telemedicine, and remote monitoring, which promise to revolutionize resource allocation in healthcare. By shedding light on current practices and future trends, this review provides valuable insights for healthcare professionals, policymakers, and researchers seeking to harness the power of data analytics for improved resource allocation in healthcare systems.

Keywords: Data Analytics, Resource Allocation, Healthcare Management, Descriptive Analytics, Predictive Analytics, Prescriptive Analytics.