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评估 COVID-19 大流行对中国卫生服务利用的影响:使用自回归积分移动平均模型的研究。

Evaluation of the impact of the COVID-19 pandemic on health service utilization in China: A study using auto-regressive integrated moving average model.

机构信息

School of Humanities and Management, Zhejiang Chinese Medical University, Hangzhou, China.

School of Nursing, Zhejiang Chinese Medical University, Hangzhou, China.

出版信息

Front Public Health. 2023 Apr 6;11:1114085. doi: 10.3389/fpubh.2023.1114085. eCollection 2023.

DOI:10.3389/fpubh.2023.1114085
PMID:37089481
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10115989/
Abstract

BACKGROUND

The outbreak of COVID-19 in early 2020 presented a major challenge to the healthcare system in China. This study aimed to quantitatively evaluate the impact of COVID-19 on health services utilization in China in 2020.

METHODS

Health service-related data for this study were extracted from the China Health Statistical Yearbook. The Auto-Regressive Integrated Moving Average model (ARIMA) was used to forecast the data for the year 2020 based on trends observed between 2010 and 2019. The differences between the actual 2020 values reported in the statistical yearbook and the forecast values from the ARIMA model were used to assess the impact of COVID-19 on health services utilization.

RESULTS

In 2020, the number of admissions and outpatient visits in China declined by 17.74 and 14.37%, respectively, compared to the ARIMA model's forecast values. Notably, public hospitals experienced the largest decrease in outpatient visits and admissions, of 18.55 and 19.64%, respectively. Among all departments, the pediatrics department had the greatest decrease in outpatient visits (35.15%). Regarding geographical distribution, Beijing and Heilongjiang were the regions most affected by the decline in outpatient visits (29.96%) and admissions (43.20%) respectively.

CONCLUSION

The study's findings suggest that during the first year of the COVID-19 pandemic, one in seven outpatient services and one in six admissions were affected in China. Therefore, there is an urgent need to establish a green channel for seeking medical treatment without spatial and institutional barriers during epidemic prevention and control periods.

摘要

背景

2020 年初 COVID-19 的爆发对中国的医疗体系提出了重大挑战。本研究旨在定量评估 COVID-19 对中国 2020 年卫生服务利用的影响。

方法

本研究从《中国卫生统计年鉴》中提取了卫生服务相关数据。使用自回归求和移动平均模型(ARIMA)根据 2010 年至 2019 年的趋势对 2020 年的数据进行预测。将统计年鉴中报告的 2020 年实际值与 ARIMA 模型的预测值之间的差异用于评估 COVID-19 对卫生服务利用的影响。

结果

与 ARIMA 模型的预测值相比,2020 年中国的住院人数和门诊就诊人数分别下降了 17.74%和 14.37%。值得注意的是,公立医院的门诊和住院量下降幅度最大,分别为 18.55%和 19.64%。在所有科室中,儿科的门诊就诊量降幅最大(35.15%)。就地域分布而言,北京和黑龙江是受门诊就诊量(29.96%)和住院量(43.20%)下降影响最大的地区。

结论

本研究结果表明,在 COVID-19 大流行的第一年,中国有七分之一的门诊服务和六分之一的住院服务受到影响。因此,在疫情防控期间,迫切需要建立一个没有空间和制度障碍的就医绿色通道。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/665e/10115989/3844f61df2d2/fpubh-11-1114085-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/665e/10115989/927208f25514/fpubh-11-1114085-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/665e/10115989/988c06e3628d/fpubh-11-1114085-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/665e/10115989/ad67af33cf81/fpubh-11-1114085-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/665e/10115989/4b6160834530/fpubh-11-1114085-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/665e/10115989/3844f61df2d2/fpubh-11-1114085-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/665e/10115989/927208f25514/fpubh-11-1114085-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/665e/10115989/988c06e3628d/fpubh-11-1114085-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/665e/10115989/ad67af33cf81/fpubh-11-1114085-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/665e/10115989/4b6160834530/fpubh-11-1114085-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/665e/10115989/3844f61df2d2/fpubh-11-1114085-g005.jpg

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