Data envelopment analysis: a pioneering approach to benchmarking healthcare resource utilization and clinical outcomes
In India, the nursing profession faces significant challenges due to manpower shortages, making the optimal use of nursing staff crucial for patient safety and care quality. This study aims to identify high-performing nursing units that demonstrate optimal staffing and better clinical outcomes using benchmarking. By adopting data envelopment analysis (DEA), a proven tool in management and technical sectors but relatively new to healthcare, the study introduces a novel method for evaluating nursing efficiency. DEA was used to assess the relative efficiency of nine nursing units across medical and surgical specialties. The analysis considered one input (number of bedside nurses) and two outputs (number of patients served and clinical performance). The DEA software calculated efficiency scores, identifying benchmark units and highlighting areas for improvement. The Obstetrics and Gynecology Ward, Ortho 1 Ward, and Surgery Male General Unit were found to be 100% efficient, serving as benchmarks for optimal clinical performance and manpower utilization. Conversely, units such as plastic surgery, extended ortho, ortho female, urology, surgery female, and medical general demonstrated the need for improvements. The findings encourage healthcare administrators to adopt best practices from efficient units, improve workflows, revise staffing models, and reallocate resources based on patient volume and acuity. This study showcases DEA as a powerful multi-criteria decision-making tool, offering a comprehensive alternative to traditional single-criterion benchmarking methods. DEA not only identifies performance gaps but also fosters a culture of continuous quality improvement in nursing and healthcare systems.
Authors
- K. M. Sharath Kumar
- G. Balamurugan
- Lima Mathews
Institutions
- M S Ramaiah University of Applied Sciences (IN)
- National Institute of Mental Health and Neurosciences (IN)
Publication Details
- Journal
- International Journal of Community Medicine and Public Health
- Published
- 2025-06-30
- DOI
- https://doi.org/10.18203/2394-6040.ijcmph20252137
- Primary Topic
- Healthcare Policy and Management
- Type
- article
- Field-Weighted Citation Impact
- 0.00