A network Data Envelopment Analysis to estimate nations’ efficiency in the fight against SARS-CoV-2

Pereira, Miguel Alves; Dinis, Duarte; Marques, Rui Cunha; Figueira, José Rui; Marques, Rui Cunha

doi:10.1016/j.eswa.2022.118362

Cited by 23 publications

(6 citation statements)

References 83 publications

(99 reference statements)

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“…The national COVID-19 strategies of these countries should be examined, adjusted, and adopted by nations displaying poorer performances. Furthermore, the noteworthy observation that countries with larger populations tend to exhibit lower mean efficiency scores holds statistical significance [14].…”

Section: Introductionmentioning

confidence: 97%

“…By comparing the findings obtained from the analysis with the Covid-19 performances; it has been observed that there is no relationship between the efficiency level of the health systems of the countries and the Covid-19 performances [13]. Pereira et al (2022) introduced network DEA to assess the efficiencies of 55 countries that consisted of 37 OECD member countries, 6 OECD prospective members, 4 OECD key partners, and 8 additional countries. The network DEA model is structured in a general series with 5 distinct stages: population, contagion, triage, hospitalization, and intensive care unit admission.…”

Section: Introductionmentioning

confidence: 99%

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Determining Efficiency of 15 OECD Countries Coping with Covid-19 using Data Envelopment Analysis after 2 Years of Pandemic

POLAT

2023

Cumhuriyet Science Journal

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Covid-19, emerged in Wuhan, a city of China, at the date of December 2019, it spread to the entire world soon and then by the World Health Organization (WHO) accepted as a pandemic. Today, still the coping with Covid-19 is the one of the significant topics of countries. In this study, the relative efficiencies of 15 OECD countries for coping with the pandemic is analyzed with Data Envelopment Analysis (DEA). Current health expenditure (% of GDP), Nurses and midwives (per 1 thousand people), Hospital beds (per 1 thousand people), Physicians (per 1 thousand people) variables used as inputs; Number of Total Cases (per 1 million people), Number of Deaths (per 1 million people) and Number of Tests (per 1 million people) variables used as outputs. Output oriented Charnes, Cooper and Rhodes (CCR) and Banker, Charnes and Cooper (BCC) DEA models are used, scale efficiency values are determined and potential improvement suggestions are given for inefficient countries. Austria, Mexico, South Korea, Spain and Türkiye are found to be both relative technical, total and scale efficient. It is also concluded that inefficient countries must use their input variables efficiently and number of Covid-19 tests is important for a country’s efficiency against Covid-19.

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Section: Introductionmentioning

confidence: 97%

Section: Introductionmentioning

confidence: 99%

Determining Efficiency of 15 OECD Countries Coping with Covid-19 using Data Envelopment Analysis after 2 Years of Pandemic

POLAT

2023

Cumhuriyet Science Journal

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“…For example, a study evaluated the performance of Portuguese public hospitals using a network data envelopment analysis model and found a consistent decrease in efficiency during the pandemic, followed by a recovery to levels exceeding those prior to the pandemic ( 15 ). Another study estimated 55 nations’ efficiency in the fight against the pandemic ( 16 ). Zhou et al calculated the health service efficiency of primary healthcare institutions among 28 provinces in China before COVID-19 and compared compare the urban–rural differences ( 17 ).…”

Section: Introductionmentioning

confidence: 99%

Coping with COVID: Performance of China’s hierarchical medical system during the COVID-19 pandemic

Yang

Huang

Yan

et al. 2023

Front. Public Health

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ObjectiveThe COVID-19 pandemic has challenged the health system worldwide. This study aimed to assess how China’s hierarchical medical system (HMS) coped with COVID-19 in the short-and medium-term. We mainly measured the number and distribution of hospital visits and healthcare expenditure between primary and high-level hospitals during Beijing’s 2020–2021 pandemic relative to the 2017–2019 pre-COVID-19 benchmark period.MethodsHospital operational data were extracted from Municipal Health Statistics Information Platform. The COVID-19 period in Beijing was divided into five phases, corresponding to different characteristics, from January 2020 to October 2021. The main outcome measures in this study include the percentage change in inpatient and outpatient emergency visits, and surgeries, and changing distribution of patients between different hospital levels across Beijing’s HMS. In addition, the corresponding health expenditure in each of the 5 phases of COVID-19 was also included.ResultsIn the outbreak phase of the pandemic, the total visits of Beijing hospitals declined dramatically, where outpatient visits fell 44.6%, inpatients visits fell 47.9%; emergency visits fell 35.6%, and surgery inpatients fell 44.5%. Correspondingly, health expenditures declined 30.5% for outpatients and 43.0% for inpatients. The primary hospitals absorbed a 9.51% higher proportion of outpatients than the pre-COVID-19 level in phase 1. In phase 4, the number of patients, including non-local outpatients reached pre-pandemic 2017–2019 benchmark levels. The proportion of outpatients in primary hospitals was only 1.74% above pre-COVID-19 levels in phases 4 and 5. Health expenditure for both outpatients and inpatients reached the baseline level in phase 3 and increased nearly 10% above pre-COVID-19 levels in phases 4 and 5.ConclusionThe HMS in Beijing coped with the COVID-19 pandemic in a relatively short time, the early stage of the pandemic reflected an enhanced role for primary hospitals in the HMS, but did not permanently change patient preferences for high-level hospitals. Relative to the pre-COVID-19 benchmark, the elevated hospital expenditure in phase 4 and phase 5 pointed to hospital over-treatment or patient excess treatment demand. We suggest improving the service capacity of primary hospitals and changing the preferences of patients through health education in the post-COVID-19 world.

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“…A wide variety of analytic methods has been utilized by researchers to measure hospital efficiency in terms of costs and production frontiers and the associated inefficiency of individual organizations (6)(7)(8). These techniques can be divided into two main categories: parametric and non-parametric methods.…”

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confidence: 99%

“…In recent years, a vast amount of studies has been conducted in high-income countries benefiting from cutting-edge methodologies (8,11), so some of them incorporated preferences into the analysis (7,12,13), as well as in the EMR, aiming at measuring hospital efficiency through both parametric and non-parametric approaches (14-16). A context-specific overview and analysis of existing articles are helpful for everyone interested in the field of efficiency measurement in healthcare with a focus on hospitals.…”

mentioning

confidence: 99%

Hospital efficiency in the eastern mediterranean region: A systematic review and meta-analysis

Ravaghi

Afshari

Isfahani

et al. 2023

Front. Public Health

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BackgroundRecent rising costs and shortages of healthcare resources make it necessary to address the issue of hospital efficiency. Increasing the efficiency of hospitals can result in the better and more sustainable achievement of their organizational goals.ObjectiveThe purpose of this research is to examine hospital efficiency in the Eastern Mediterranean Region (EMR) using data envelopment analysis (DEA).MethodsThis study is a systematic review and meta-analysis of all articles published on hospital efficiency in Eastern Mediterranean countries between January 1999 and September 2020, identified by searching PubMed through MEDLINE, Web of Science, Scopus, Science Direct, and Google Scholar. The reference lists of these articles were checked for additional relevant studies. Finally, 37 articles were selected, and data were analyzed through Comprehensive Meta-Analysis Software (v.2.2.064).ResultsUsing the random-effects model, the mean hospital efficiency in Eastern Mediterranean hospitals was 0.882 ± 0.01 at 95% CI. Technical efficiency (TE) was higher in some countries such as Iraq (0.976 ± 0.035), Oman (0.926 ± 0.032), and Iran (0.921 ±0.012). A significant statistical correlation was observed between the hospital efficiency and the year of publication and sample size (p < 0.05).ConclusionEfficiency plays a significant role in hospital growth and development. Therefore, it is important for healthcare managers and policymakers in the EMR to identify the causes of inefficiency, improve TE, and develop cost-effective strategies.

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A network Data Envelopment Analysis to estimate nations’ efficiency in the fight against SARS-CoV-2

Cited by 23 publications

References 83 publications

Determining Efficiency of 15 OECD Countries Coping with Covid-19 using Data Envelopment Analysis after 2 Years of Pandemic

Determining Efficiency of 15 OECD Countries Coping with Covid-19 using Data Envelopment Analysis after 2 Years of Pandemic

Coping with COVID: Performance of China’s hierarchical medical system during the COVID-19 pandemic

Hospital efficiency in the eastern mediterranean region: A systematic review and meta-analysis

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