ADS Capstone Chronicles Revised

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high-density areas and inadequate services in low-density areas. This discrepancy affects various stakeholders: ● Policymakers : They require accurate and reliable data to formulate regulations and ensure proper resource distribution, preventing FWA. ● Beneficiaries : Those in underserved areas suffer from limited access to essential healthcare services. ● Providers : Understanding market Addressing these issues can prevent poor service quality, high program costs, and suboptimal health outcomes. By identifying regions susceptible to FWA and improving access in underserved areas, this project aims to contribute to a more equitable and efficient healthcare system. 2.2 Definition of Objectives The project’s main objective is to use advanced data analytics to identify and address inefficiencies in Medicare and Medicaid resource allocation, with a focus on market saturation and FWA. The specific objectives include: 1. Data Analysis and Market Saturation Evaluation: Analyze the Market Saturation and Utilization State-County dataset to assess saturation helps in the effective planning and expansion of the Medicare and Medicaid program.

to detect patterns of over-utilization and under-utilization, highlighting potential inefficiencies. 2. Fraud Detection through Machine Learning: Employ supervised machine learning techniques to identify abnormal patterns indicative of FWA within the dataset. 3. Performance Evaluation of Models: Evaluate the performance of the supervised machine learning models using metrics such as but not limited to accuracy, F1-score, and confusion matrix. 4. Policy Recommendations and Decision Support: Develop actionable recommendations based on data analysis and model insights to optimize resource allocation, improve healthcare services, and mitigate FWA. 5. Interactive Visualization Tool: Create an interactive dashboard using Tableau to visualize the analysis results, enabling dynamic

data exploration and aiding stakeholder decision-making.

The anticipated outcomes of this project will lead to targeted interventions that improve healthcare delivery. If the project findings are validated, it will confirm the critical need for optimized resource allocation in healthcare. However, if the findings are disproved, it will suggest that other factors may be contributing to inefficiencies in

healthcare provider density relative to the beneficiary population across various regions. This analysis aims

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