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Application of DEA-Based Malmquist Productivity Index on Health Care System Efficiency of ASEAN Countries.

Shailender SinghMuhammad M BalaNishant KumarHawati Janor
Published in: The International journal of health planning and management (2021)
This study assesses and compares the productive efficiency of the national healthcare system of the ASEAN region which includes Brunei, Cambodia, Indonesia, Laos, Malaysia, Myanmar, Philippines, Singapore, Thailand and Vietnam amidst rising mortality rate from noncommunicable diseases (NCDs) in the Sustainable Development Goals (SDGs) era. Nonparametric data envelopment analysis technique based on the Malmquist Productivity Index is performed and its components, total factor productivity change, technical change and technological change are compared across the region. Two different models are considered in assessing and comparing the technical efficiency of the national healthcare system across the region with life expectancy at birth and mortality rate from NCDs as parallel health care output for both the models. The mean value of total factor productivity is 0.983 and 0.974 which suggests that national healthcare system productivity efficiency decays by 1.7% for Model I and 2.6% for Model II, respectively. This suggests that the health care system inefficiencies across the ASEAN region have not made life expectancy to improve as much as it should be and curtailed the mortality rate from growing chronic NCDs within a decade. The region is likely to lag behind in achieving SDGs 3 target 4 on reducing by one-third premature mortality from chronic NCDs unless the health care system's technical efficiency is improved across the region. The finding suggests a microlevel study on each country to identify major sources of healthcare system inefficiency in a bid to ameliorate it.
Keyphrases
  • climate change
  • cardiovascular events
  • healthcare
  • quality improvement
  • risk factors
  • cardiovascular disease
  • coronary artery disease
  • pregnant women
  • artificial intelligence
  • health insurance
  • preterm birth
  • big data