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Balancing efficiency and clinical quality in dialysis centers: Insights from a nationwide DEA study in Taiwan
Shu-Chuan Jennifer Yeh1, Wen Chun Wang2, Andrew Pruett3
1Institute of Health Care Management & Department of Business Management, National Sun Yat-sen University, Kaohsiung, Taiwan.
Objectives:
The increasing prevalence of end-stage renal disease (ESRD), especially in aging populations, presents significant challenges for healthcare systems. Dialysis centers must navigate growing demands for cost efficiency while maintaining high-quality care. This study aimed to evaluate the relationship between operational efficiency and clinical quality in dialysis centers, using a systems-based performance assessment framework.
Methods:
We analyzed 578 dialysis centers in Taiwan using Data Envelopment Analysis (DEA) to estimate operational efficiency. Clinical quality was assessed using outcome indicators including mortality rate, dialysis adequacy (urea reduction ratio [URR], Kt/V), serum albumin and hemoglobin levels, calcium-phosphate (Ca × P) product, and cardiothoracic ratio. Multiple regression analyses were conducted to examine associations between efficiency scores, clinical outcomes, and organizational characteristics, including chain affiliation and ownership type.
Results:
Higher efficiency scores were significantly associated with lower URR, Kt/V, and Ca × P values, suggesting potential trade-offs between operational efficiency and clinical quality. Centers affiliated with chains generally reported better clinical outcomes. For-profit centers exhibited higher URR, Kt/V, and albumin levels, as well as lower Ca × P values, compared to their non-profit counterparts.
Conclusions:
Operational efficiency in dialysis centers may come at the cost of certain clinical outcomes. However, organizational characteristics such as chain affiliation and for-profit ownership are linked to better quality indicators. These findings highlight the value of DEA as a tool for system-level performance evaluation and inform strategies to optimize dialysis care delivery.
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