Evidence map›Paper›PMID 32257167›Full record

ArticleJournal of global health2020

An application of ARIMA model for predicting total health expenditure in China from 1978-2022.

Ang Zheng, Quan Fang, Yalan Zhu, Chunling Jiang, Feng Jin, Xin Wang

Abstract read
In one paragraph

Article in Journal of global health, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers.

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37citing papers in PubMed
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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

Who cites it

37 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Ang ZhengDepartment of Breast Surgery, the First Affiliated Hospital of China Medical University, Shenyang, Liaoning Province, China.
Quan FangCollege of the Humanities and Social Sciences, China Medical University, Shenyang, Liaoning Province, China.
Yalan ZhuCollege of the Humanities and Social Sciences, China Medical University, Shenyang, Liaoning Province, China.
Chunling JiangCollege of Basic Medical Science, China Medical University, Shenyang, Liaoning Province, China.
Feng JinDepartment of Breast Surgery, the First Affiliated Hospital of China Medical University, Shenyang, Liaoning Province, China.
Xin WangCollege of the Humanities and Social Sciences, China Medical University, Shenyang, Liaoning Province, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundChina's health financing system has changed from the government-led mode under the planned economy to the diversified mode under the market economy. Equity in health financing has been a national health priority. This study aimed to predict changes in total health expenditure (THE), government health expenditure (GHE), social health expenditure (SHE) and out-of-pocket health expenditure (OOP) in China from 2018 to 2022, and to provide a theoretical basis for health policy adjustment.

methodsBased on health expenditure date of time series from 1978-2017, R3.5.1 software was used to construct the Autoregressive Integrated Moving Average (ARIMA) model.

resultsThe model of THE, GHE, SHE and OOP are ARIMA (3.3.0), ARIMA (1.3.1), ARIMA (2.4.0), ARIMA (2.2.2). According to the simulation results, in 2022, China's THE is expected to reach 8473.00 billion Yuan, and the constituent ratios in GHE, SHE and OOP will be 25.49%, 51.25% and 23.26%, respectively. The proportion of THE to GDP will continuously increase from 2018-2022 at a reasonable pace, while THE itself will increase rapidly.

conclusionsChina should take effective measures to control the excessive growth of THE, keep decreasing the OOP percentage, and improve the efficiency and fairness of the use of health funds.

Indexed as

Healthcare FinancingHealth ExpendituresChinaHealth Care ReformHumansModels, StatisticalPredictive Value of Tests

Identifiers

PMID32257167
PMCPMC7101215

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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.