Measuring Cost–Revenue Technical Efficiency in Fragmented Outpatient Care: A Comparative DEA and SFA Analysis.
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| Title: | Measuring Cost–Revenue Technical Efficiency in Fragmented Outpatient Care: A Comparative DEA and SFA Analysis. |
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| Authors: | Vrabková, Iveta1 (AUTHOR) iveta.vrabkova@vsb.cz, Bauer, Dominik1 (AUTHOR) |
| Source: | Inquiry (00469580). 4/21/2026, Vol. 63, p1-11. 11p. |
| Subject Terms: | *Cost benefit analysis, *Financial management, *Comparative studies, Evaluation of organizational effectiveness, Dental clinics, Pearson correlation (Statistics), Labor productivity, Research funding, Medical quality control, Outpatient medical care, Value-based healthcare, Kruskal-Wallis Test, Scientific observation, Descriptive statistics, One-way analysis of variance, Data analysis software, Medical care costs |
| Geographic Terms: | Czech Republic |
| Abstract: | Fragmented outpatient care systems dominated by small providers require reliable efficiency measurement tools to inform benchmarking and reimbursement design. However, it remains unclear to what extent efficiency estimates depend on methodological choice, particularly when cost-based data are used. This study evaluates cost–revenue technical efficiency of 344 dental practices observed between 2017 and 2020 using input-oriented Data Envelopment Analysis (DEA) under constant and variable returns to scale and Stochastic Frontier Analysis (SFA). Inputs include labor and material costs; output is annual revenue, standardized per employee. Correlation, robustness testing, and temporal analysis were performed. Average technical efficiency ranged from 0.50 (SFA) to 0.61 (DEA_VRS), indicating substantial unused production potential. Strong correlation was observed between DEA variants (r =.763), while correlations between DEA and SFA were weak (r <.30), suggesting that the methods capture distinct dimensions of inefficiency. Efficiency increased modestly over time but dispersion across providers widened. The 2020 results may partially reflect pandemic-related service disruptions. Efficiency estimates in fragmented outpatient care are highly sensitive to methodological specification. The results reflect financial production efficiency rather than clinical or value-based performance. A combined DEA–SFA framework provides complementary insights for benchmarking and policy design, but operational implementation requires explicit decision rules and contextual adjustment. [ABSTRACT FROM AUTHOR] |
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| Database: | Education Research Complete |
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| Abstract: | Fragmented outpatient care systems dominated by small providers require reliable efficiency measurement tools to inform benchmarking and reimbursement design. However, it remains unclear to what extent efficiency estimates depend on methodological choice, particularly when cost-based data are used. This study evaluates cost–revenue technical efficiency of 344 dental practices observed between 2017 and 2020 using input-oriented Data Envelopment Analysis (DEA) under constant and variable returns to scale and Stochastic Frontier Analysis (SFA). Inputs include labor and material costs; output is annual revenue, standardized per employee. Correlation, robustness testing, and temporal analysis were performed. Average technical efficiency ranged from 0.50 (SFA) to 0.61 (DEA_VRS), indicating substantial unused production potential. Strong correlation was observed between DEA variants (r =.763), while correlations between DEA and SFA were weak (r <.30), suggesting that the methods capture distinct dimensions of inefficiency. Efficiency increased modestly over time but dispersion across providers widened. The 2020 results may partially reflect pandemic-related service disruptions. Efficiency estimates in fragmented outpatient care are highly sensitive to methodological specification. The results reflect financial production efficiency rather than clinical or value-based performance. A combined DEA–SFA framework provides complementary insights for benchmarking and policy design, but operational implementation requires explicit decision rules and contextual adjustment. [ABSTRACT FROM AUTHOR] |
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| ISSN: | 00469580 |
| DOI: | 10.1177/00469580261437001 |
