In the healthcare field there is a problem. Medical costs are going up. Budgets are limited. We need models to make the most of what we have without hurting patient care. Healthcare Economics and Outcomes Research is an area that helps us understand the value and effectiveness of medical treatments this study creates a framework. It looks at costs. How well services are delivered. We use a mix of methods, including Data Envelopment Analysis to see how efficient things are. We also use machine learning to predict what will happen with resources we looked at 15,000 cases from eight departments in a big hospital. We checked costs, patient outcomes and how well the hospital worked. Our model looks at how resources are used and how they are distributed. We found that using a model with DEA and XGBoost works well. It can predict costs and quality accurately. We got an R 2 of 0.87 a Mean Absolute Percentage Error of 8.2 and an Area Under the Receiver Operating Characteristic Curve of 0.91 this approach also found ways to save money. We can cut costs by 18.7 without hurting quality. This study helps healthcare leaders make decisions. They can use our method to make healthcare better and more efficient. Healthcare Economics, Outcomes Research, Cost Efficiency Analysis, Service Delivery Optimization, Data Envelopment Analysis, Machine Learning, in Healthcare, Resource Allocation, Healthcare Value, Predictive Analytics Quality Adjusted Life Years. 82-99 Smart Innovations in Computer Science and Applications Special Issue Sahib Qureshi