This study examines the performance of Medicare providers, with a focus on patient backgrounds, number of chronic illnesses, and efficacy of drug treatments as compared to traditional medical services. Over 1.2 million records from the Centers for Medicare & Medicaid Services and different methods, such as random forest regression and K-means clustering, were utilized to identify top-performing providers, categorize patients, and evaluate the results of treatments. The results reveal that while spending more on Medicare and offering more services can sometimes improve patient outcomes, these improvements are not always steady. This inconsistency points out some ongoing problems in the system, primarily affecting older adults and those in underserved communities, who often struggle with worse health and limited access to care. In addition, the study found that the effectiveness and cost of different treatment methods can vary widely. Drug treatments and direct medical services had varying impacts on resource use and health benefits. Combining large-scale public data with advanced analytic techniques, this research provides a reference for policymakers and healthcare organizations and offers insights into designing targeted interventions, with the ultimate aim to preserve fairness and sustainability in the U.S. healthcare system.