ENGINEERING DATA-DRIVEN STRATEGIES FOR REDUCING THE COST OF CARE
Keywords:
Data Engineering, Healthcare Cost Reduction, Predictive Analytics, Real-Time Processing, Operational OptimizationAbstract
The escalating cost of healthcare is a global concern affecting patients, providers, and policymakers. This paper explores how data engineering can be leveraged to develop data-driven strategies aimed at reducing the cost of care without compromising quality. By harnessing advanced data integration techniques, real-time processing, predictive analytics, and automation, healthcare organizations can optimize operations, enhance patient outcomes, and achieve substantial cost savings. The paper delves into key data engineering methodologies, discusses implementation challenges, and presents case studies demonstrating successful applications. Recommendations for future directions are also provided.
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