Evidence map›Paper›PMID 38702650›Full record

ArticleBMC health services research2024

Impact of an innovative bundled payment to TB health care providers in China: an economic simulation analysis.

Pengyu Xu, Yazhen Ying, Debin Xu, Shitong Huan, Lindu Zhao, Hong Wang

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Article in BMC health services research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Pengyu XuSchool of Economics & Management, Southeast University, No. 2, Sipailou, Xuanwu District, Nanjing, Jiangsu Province, 210096, China.
Yazhen YingNational Institute of Healthcare Security Capital Medical University, Beijing, China.
Debin XuNational Institute of Healthcare Security Capital Medical University, Beijing, China.
Shitong HuanBill & Melinda Gates Foundation, Seattle, WA, USA.
Lindu ZhaoSchool of Economics & Management, Southeast University, No. 2, Sipailou, Xuanwu District, Nanjing, Jiangsu Province, 210096, China. ldzhao@seu.edu.cn.
Hong WangBill & Melinda Gates Foundation, Seattle, WA, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTuberculosis is the second most deadly infectious disease after COVID-19 and the 13th leading cause of death worldwide. Among the 30 countries with a high burden of TB, China ranks third in the estimated number of TB cases. China is in the top four of 75 countries with a deficit in funding for TB strategic plans. To reduce costs and improve the effectiveness of TB treatment in China, the NHSA developed an innovative BP method. This study aimed to simulate the effects of this payment approach on different stakeholders, reduce the economic burden on TB patients, improve the quality of medical services, facilitate policy optimization, and offer a model for health care payment reforms that can be referenced by other regions throughout the world.

methodsWe developed a simulation model based on a decision tree analysis to project the expected effects of the payment method on the potential financial impacts on different stakeholders. Our analysis mainly focused on comparing changes in health care costs before and after receiving BPs for TB patients with Medicare in the pilot areas. The data that were used for the analysis included the TB service claim records for 2019-2021 from the health insurance agency, TB prevalence data from the local Centre for Disease Control, and health care facilities' revenue and expenditure data from the Statistic Yearbook. A Monte Carlo randomized simulation model was used to estimate the results.

resultsAfter adopting the innovative BP method, for each TB patient per year, the total annual expenditure was estimated to decrease from $2,523.28 to $2,088.89, which is a reduction of $434.39 (17.22%). The TB patient out-of-pocket expenditure was expected to decrease from $1,249.02 to $1,034.00, which is a reduction of $215.02 (17.22%). The health care provider's revenue decreased from $2,523.28 to $2,308.26, but the health care provider/institution's revenue-expenditure ratio increased from -6.09% to 9.50%.

conclusionsThis study highlights the potential of BPs to improve medical outcomes and control the costs associated with TB treatment. It demonstrates its feasibility and advantages in enhancing the coordination and sustainability of medical services, thus offering valuable insights for global health care payment reform.

Indexed as

TuberculosisChinaComputer SimulationCOVID-19Health Care CostsHealth ExpendituresHealth PersonnelHumansModels, EconomicControl strategiesDescriptive studyHealth economicsHealth policyTuberculosis

Identifiers

PMID38702650
PMCPMC11069261

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.