Comparison of technical efficiency of South Korean and Vietnamese public hospitals in 2006-2009

Nguyen, Thi Tuyet Hanh; Lee, Jun Young; Lee, Hae Jong

doi:10.1504/ijpp.2012.045879

Cited by 2 publications

(1 citation statement)

References 12 publications

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“…DEA analysis can also be carried out at a hospital level to measure and compare technical efficiency across hospitals in view to improve efficiency with input parameters as number of doctors, nurses, technicians, number of beds, fixed assets, operating expenses and output parameters such as in-patient days and patient mortality. Such tools can be used to provide input to policy formulation and implementation (Debata et al, 2014;Dharmapala, 2009;Harrison and Coppola, 2007;Hu et al, 2012;Nguyen et al, 2012;Pavitra, 2013). From the analysis above, DEA is a robust multi-input, multi-output tool that helps to identify the efficiency frontier.…”

Section: Introductionmentioning

confidence: 99%

Evaluating Health System Efficiency using Data Envelopment Analysis: A case of Indian Healthcare System

Coutinho¹,

Prasad²,

Prabhudesai³

2021

Gurukul Business Review

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Purpose-With increased demand and restricted healthcare resources, it becomes important to take a step back and evaluate the efficiency of healthcare delivery. The present study aims to evaluate the health system efficiency of India by benchmarking it against its peers in BRICS countries and against OECD countries. Design/Methodology/Approach: The input and output variables required for measuring the efficiency of healthcare system were identified. A Data Envelopment Analysis (DEA) approach was used and efficiency frontier identified with the rankings of the BRICS and OECD countries. India is thus benchmarked against its peers (BRICS) and against OECD countries. Finding: India was found to operate at the efficiency frontier along with China, Russia, Brazil, and South Africa, however it ranked fourth. When benchmarked against OECD countries, India operates on the efficiency frontier along with Canada, Greece, Japan, Korea, Mexico, Spain, Sweden, Switzerland, Turkey, Great Britain, Chile and Israel. Countries like Germany, United States of America, Czech Republic, Slovakia and Lithuania operate at a lower healthcare efficiency and need to use their resources wisely. Practical/Research Implications: Developing countries like India can look to improve its healthcare system delivery by replicating best practices of healthcare systems from its peers and the top 10 OECD countries. Majority of the OECD countries in the top 10 have implemented universal health coverage, have higher physician and nurse density and higher hospital bed ratios. They are inclined towards branded drugs vis-à-vis generics and have follow evidence based medicine. From a theoretical perspective, it adds to the body of literature of DEA and health system efficiency. Originality/Value: This is a pioneer study that benchmarks India against its peers and against OECD countries drawing unique insights about healthcare efficiency

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Section: Introductionmentioning

confidence: 99%

Evaluating Health System Efficiency using Data Envelopment Analysis: A case of Indian Healthcare System

Coutinho¹,

Prasad²,

Prabhudesai³

2021

Gurukul Business Review

View full text Add to dashboard Cite

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Analysis on RTS and the Change of Productivity Efficiency of Public General Hospitals in Vietnam using Parametric and Non-Parametric Approach

Yang¹

2014

Journal of the Korea Academia-Industrial cooperation Society

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This study estimated productivity change and RTS using Parametric and Non-Parametric approach with 5 year annual data from 2006 to 2010 of 20 public general hospitals in Vietnam collected from Ho Chi Min City Health Department of Health Database. The results could be summarized as follows; First, by the Non-Parametric approach. cumulated productivity growth of 5 years was increased by 2.8% due to regress 5.2% of technical efficiency, 0.3% of pure technical efficiency, but scale efficiency was decreased 5.1% Second, by the Non-Parametric approach, cumulated productivity growth was decreased by 12.8% to due to drop of 17.1% of technical change, 9.1% of scale efficiency. In conclusion, the common result of both approaches was that scale inefficiencies occurs in public hospitals in Vietnam, and they affected productivity change of public hospitals in Vietnam. Namely, 70% to 80% of the analyzed Vietnam public hospitals were at the status of DRS(decreased returns to scale), which suggested that they had oversupply beds relative to the number of occupied patients, it was meaningful that this study was the first study in Korea to measure efficiency and productivity change of Vietnamese public general hospitals and so it could be utilized as the basic information needed to enter hospital industry of Vietnam in the future.

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Comparison of technical efficiency of South Korean and Vietnamese public hospitals in 2006-2009

Cited by 2 publications

References 12 publications

Evaluating Health System Efficiency using Data Envelopment Analysis: A case of Indian Healthcare System

Evaluating Health System Efficiency using Data Envelopment Analysis: A case of Indian Healthcare System

Analysis on RTS and the Change of Productivity Efficiency of Public General Hospitals in Vietnam using Parametric and Non-Parametric Approach

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