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<p>With increasing emphasis on public health programs, Indian health system continues to exhibit substantial inefficiencies in translating resources into improved health outcomes. Within this context, this study estimates the efficiency across 36 Indian States and Union Territories for the year 2022–23 and explores how efficiency relates to progress toward Sustainable Development Goal (SDG) 3. Using state-level data, we apply Data Envelopment Analysis (DEA) to estimate output- and input-oriented technical efficiency, as well as Pareto–Koopmans efficiency, under a variable returns-to-scale framework. The results reveal substantial heterogeneity in health system performance across states. While a large number of states appear efficient under radial measures, the non-radial Pareto–Koopmans measure uncovers significant input–output slacks, indicating imbalances across different dimensions. Moreover, efficiency and health outcomes do not always coincide. Several states exhibit high efficiency but only moderate SDG 3 scores, while others achieve relatively strong outcomes despite lower efficiency. The findings suggest that India’s health system not only suffers from resource scarcity but also from misallocation and uneven distribution. Policy interventions, therefore, need to move from incremental uniform spending towards state-specific strategies. Herein, we can address the underlying sources of inefficiency, improve health outcomes, and accelerate progress toward SDG 3.</p>

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Do efficient health systems achieve better SDG 3 outcomes? Evidence from Indian states

  • 期刊论文

  • 发表日期：

    2026年4月25日

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  • Aryama Sarkar,
  • Soumyaranjan Mukherjee

摘要

With increasing emphasis on public health programs, Indian health system continues to exhibit substantial inefficiencies in translating resources into improved health outcomes. Within this context, this study estimates the efficiency across 36 Indian States and Union Territories for the year 2022–23 and explores how efficiency relates to progress toward Sustainable Development Goal (SDG) 3. Using state-level data, we apply Data Envelopment Analysis (DEA) to estimate output- and input-oriented technical efficiency, as well as Pareto–Koopmans efficiency, under a variable returns-to-scale framework. The results reveal substantial heterogeneity in health system performance across states. While a large number of states appear efficient under radial measures, the non-radial Pareto–Koopmans measure uncovers significant input–output slacks, indicating imbalances across different dimensions. Moreover, efficiency and health outcomes do not always coincide. Several states exhibit high efficiency but only moderate SDG 3 scores, while others achieve relatively strong outcomes despite lower efficiency. The findings suggest that India’s health system not only suffers from resource scarcity but also from misallocation and uneven distribution. Policy interventions, therefore, need to move from incremental uniform spending towards state-specific strategies. Herein, we can address the underlying sources of inefficiency, improve health outcomes, and accelerate progress toward SDG 3.