意大利与 COVID-19 相关的住院情况:应用合成控制法调查 2010-2021 年期间与诊断相关的 79 组及其反事实的轨迹。

IF 1.8 4区 医学 Q3 HEALTH CARE SCIENCES & SERVICES
Carlo Lazzaro, Giovanni Fattore, Angelo Guido Corsico
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引用次数: 0

摘要

背景:2019 年冠状病毒病(COVID-19)大流行给意大利带来了 1,095 万病例(2020 年 3 月 11 日至 2022 年 2 月 9 日)。大多数与 COVID-19 相关的住院病人出院都被归入诊断相关组别(DRG)79。2019-2021年期间,DRG79住院病人出院人数从20,377人增加到130,580人(+540.82%)。研究设计与方法:为研究DRG79住院病人出院人数与COVID-19之间的因果关系,合成对照法(SCM)比较了真实与反事实DRG79。后者是控制单元(与 COVID-19 无关的 22 个 DRGs)的加权组合。SCM 模拟了 DRG 79 在没有 COVID-19 的情况下的轨迹。安慰剂研究和稳健性测试调查了基线研究结果的可靠性。自 2019 年起,实际 DRG 79 与反事实 DRG 79 不再重叠。安慰剂研究和稳健性测试证实了 COVID-19 与 2019-2021 年期间 DRG 79 下编码的住院病人出院数量增加之间的因果关系。希望未来能在意大利国家卫生服务机构的医疗决策中利用单因子模式(以及一般因果推断)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
COVID-19-related hospitalizations in Italy: an application of the synthetic control method to investigate the trajectory of diagnosis-related group 79 and its counterfactual during 2010-2021.

Background: With 10.95 million cases (11 March 2020-9 February 2022), Italy was massively hit by the coronavirus disease 2019 (COVID-19) pandemic. Most of the COVID-19-related inpatient discharges were codified under the Diagnosis-Related Group (DRG) 79. During 2019-2021, DRG 79 inpatient discharges increased from 20,377 to 130,580 (+540.82%).

Research design and methods: To investigate the causal relationship between DRG 79 inpatient discharges and COVID-19, the synthetic control method (SCM) compared the real with the counterfactual DRG 79. The latter was a weighted combination of control units (22 DRGs unrelated to COVID-19). The SCM mimicked the trajectory of DRG 79 in the absence of COVID-19.Placebo studies and robustness test investigated the reliability of the baseline findings.

Results: Six out of the 22 control units contribute to the counterfactual DRG 79. The real and the counterfactual DRG 79 cease to overlap from 2019 onward. Placebo studies and robustness test confirm the causal relationship of COVID-19 with the increased number of inpatient discharges coded under DRG 79 during 2019-2021.

Conclusion: The SCM identifies a causal link between COVID-19 and DRG 79 in Italy. Hopefully, future contributions will utilize SCM (and causal inference in general) in health care decision-making within the Italian National Health Service.

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来源期刊
Expert Review of Pharmacoeconomics & Outcomes Research
Expert Review of Pharmacoeconomics & Outcomes Research HEALTH CARE SCIENCES & SERVICES-PHARMACOLOGY & PHARMACY
CiteScore
4.00
自引率
4.30%
发文量
68
审稿时长
6-12 weeks
期刊介绍: Expert Review of Pharmacoeconomics & Outcomes Research (ISSN 1473-7167) provides expert reviews on cost-benefit and pharmacoeconomic issues relating to the clinical use of drugs and therapeutic approaches. Coverage includes pharmacoeconomics and quality-of-life research, therapeutic outcomes, evidence-based medicine and cost-benefit research. All articles are subject to rigorous peer-review. The journal adopts the unique Expert Review article format, offering a complete overview of current thinking in a key technology area, research or clinical practice, augmented by the following sections: Expert Opinion – a personal view of the data presented in the article, a discussion on the developments that are likely to be important in the future, and the avenues of research likely to become exciting as further studies yield more detailed results Article Highlights – an executive summary of the author’s most critical points.
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