Data-Driven Decision-Making in Healthcare Systems Using Operations Research and Statistical Modeling: A Framework for Optimizing US Healthcare Delivery

The escalating complexity of healthcare delivery in the United States, coupled with increasing costs and demand for services, necessitates sophisticated analytical approaches to optimize system performance. This article presents a comprehensive framework for implementing data-driven decision-making in healthcare systems through the integration of operations research techniques and statistical modeling. By leveraging queuing theory, simulation modeling, and decision analysis, healthcare organizations can significantly improve resource allocation, patient flow management, and service delivery efficiency. The integration of advanced IT systems enables real-time data collection and analysis, supporting continuous optimization of healthcare operations. This research demonstrates how systematic application of these methodologies can address critical challenges in US healthcare delivery while maintaining quality standards and improving patient outcomes.