OPTIMIZATION MODELING OF DEA FOR MEASURING HOSPITAL PERFORMANCE EFFICIENCY WITH PYTHON CODING
Saloni, Mohammad Rizwanullah
Department of Mathematics and Statistics
Manipal University Jaipur, Jaipur, Rajasthan, India
ABSTRACT: Decision-making units (DMUs) are regarded in the standard DEA technique as entities that transform numerous inputs into multiple outputs so that their relative efficiency may be evaluated. The performance of hospital branches is assessed in this study using the CCR and BCC models, respectively, under constant and variable returns to scale. The paper’s goal is twofold: Its objective is to evaluate the performance of seven branches of a hospital in a state Rajasthan. Evaluating the operational performance of hospitals has always been crucial because of their importance to the health and well-being of society. The primary goal is to assess the effectiveness of seven branches of Hospital locations in Rajasthan. The secondary goal is to demonstrate the applicability and effectiveness of Python-based Data Envelopment Analysis (DEA) using the CCR model for operational efficiency assessment. Hospital management will be able to examine and contrast operational efficacy across branches. The CCR and BCC models of Data Envelopment Analysis (DEA), which are implemented in Python, are used in the study to describe the effectiveness of these branches. Python offers strong modules and an adaptable syntax for Data Envelopment Analysis (DEA) that make data processing, visualization, and model implementation easier. It is ideal for both small- and large-scale efficiency assessments due to its adaptability and integration capabilities. To analysis the proposed method with computational calculation, a numerical example solves to validate the model. Finally, conclusion and future research directions are also presented.
KEYWORDS: Hospital efficiency; Data Envelopment Analysis (DEA); CCR model; Python