The European journal of health economics : HEPAC : health economics in prevention and care · 2026
Digital transformation, governance multipliers, and healthcare efficiency: evidence from emerging and high-income health systems.
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Kumar M V Manoj, S Prashanth B, Hoque Ariful, Al Muraqab Nasser, Moonesar Immanuel Azaad, Braendle Udo Christian, Rao Ananth
Аннотация
OBJECTIVES: This study examines how digital finance, digital transformation, and governance quality jointly influence healthcare efficiency across emerging and high-income health systems. We assess whether digital innovations contribute to productivity improvements and whether institutional capacity conditions these effects.
STUDY DESIGN: We analyse a balanced panel of 13 countries over 2000-2023 using a multi-method empirical strategy. Baseline OLS and fixed- and random-effects models establish structural patterns, while the two-step system GMM corrects for endogeneity, persistence, and unobserved heterogeneity. Random Forest Trees (RFT) provide complementary predictive validation.
DATA SOURCES: Healthcare efficiency, digital readiness, governance indices, and macroeconomic indicators were sourced from the World Bank, WHO, Global Findex, and national statistics, yielding 325 country-year observations.
PRINCIPAL FINDINGS: Healthcare efficiency exhibits strong persistence over time. Digital finance and digital transformation significantly improve efficiency across all model specifications. Critically, governance quality amplifies these digital effects: interaction terms (GOV × DF, GOV × DT) remain robust in GMM and rank among the most influential predictors in the RFT model. Cross-country disparities in efficiency largely reflect differences in digital and institutional maturity rather than economic or demographic scale.
CONCLUSION: Digital tools can enhance healthcare efficiency, but their effectiveness depends on the institutional environment in which they are deployed. Strengthening governance capacity alongside digital investment is therefore essential for improving system-wide performance and advancing SDG 3. The combined econometric-machine-learning approach provides robust causal and predictive evidence for policy design.
STUDY DESIGN: We analyse a balanced panel of 13 countries over 2000-2023 using a multi-method empirical strategy. Baseline OLS and fixed- and random-effects models establish structural patterns, while the two-step system GMM corrects for endogeneity, persistence, and unobserved heterogeneity. Random Forest Trees (RFT) provide complementary predictive validation.
DATA SOURCES: Healthcare efficiency, digital readiness, governance indices, and macroeconomic indicators were sourced from the World Bank, WHO, Global Findex, and national statistics, yielding 325 country-year observations.
PRINCIPAL FINDINGS: Healthcare efficiency exhibits strong persistence over time. Digital finance and digital transformation significantly improve efficiency across all model specifications. Critically, governance quality amplifies these digital effects: interaction terms (GOV × DF, GOV × DT) remain robust in GMM and rank among the most influential predictors in the RFT model. Cross-country disparities in efficiency largely reflect differences in digital and institutional maturity rather than economic or demographic scale.
CONCLUSION: Digital tools can enhance healthcare efficiency, but their effectiveness depends on the institutional environment in which they are deployed. Strengthening governance capacity alongside digital investment is therefore essential for improving system-wide performance and advancing SDG 3. The combined econometric-machine-learning approach provides robust causal and predictive evidence for policy design.