Evidence map›Paper›PMID 40753201›Full record

Observational studyBMC public health2025

Quality of care for acute ischemic stroke in China during the COVID-19 pandemic: a retrospective study using a National database.

Ruize Guo, Jingkun Li, Mengyang Liu, Meina Liu

Abstract readObservational Study
In one paragraph

Observational study in BMC public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Ruize GuoDepartment of Biostatistics, School of Public Health, Harbin Medical University, No.157 Baojian Road, Harbin, 150081, China.
Jingkun LiDepartment of Biostatistics, School of Public Health, Harbin Medical University, No.157 Baojian Road, Harbin, 150081, China.
Mengyang LiuDepartment of Biostatistics, School of Public Health, Harbin Medical University, No.157 Baojian Road, Harbin, 150081, China.
Meina LiuDepartment of Biostatistics, School of Public Health, Harbin Medical University, No.157 Baojian Road, Harbin, 150081, China. liumeina369@163.com.

Funding

National Natural Science Foundation of China 82173614
6 · The paper itself

Abstract

backgroundAcute ischemic stroke (AIS) is one of the most time-sensitive diseases, which requires prompt medical services. Delayed treatment and resource scarcity during the coronavirus disease 2019 (COVID-19) pandemic may affect the quality of AIS care and increase the risk of adverse outcomes for patients.

methodsThe study used data from China's National Medical Quality Database spanning from January 1, 2019, to May 31, 2022. Quality of care was gauged utilizing 15 indicators, featuring 12 quality indicators (QIs) and 3 composite indicators. We used mixed-effects and interrupted time series models to compare care quality pre- and post-pandemic. Utilization rates of 15 indicators were compared across different age and gender groups to evaluate healthcare disparities. Multilevel Logistic regression and structural equation modeling assessed the impact of the 3 composite indicators on outcome (in-hospital mortality or 30-day readmission) during the pandemic.

resultsUtilization rates for 10 of 12 QIs and three composite indicators declined rapidly after the COVID-19 outbreak, but later improved. The most significant drop was observed for rehabilitation (QI12), with a decrease of 50.06% (P < 0.0001). The overall treatment quality (Score) showed a decrease of -14.44% (95% CI -15.62% to -13.26%; P < 0.0001), and experienced a long-term trend change of 0.58 (95% CI 0.40 to 0.75; P < 0.0001). Female patients had lower rates for 11 QIs and all composite indicators compared with male patients, with the greatest difference noted in dysphagia screening (66.45% vs. 69.87%, P = 0.0472). Patients aged 75 years or older had lower rates for 9 QIs and all composite indicators compared with other age groups, with the greatest difference in anticoagulation therapy (difference = 10.01%, P < 0.0001). High-quality care was significantly associated with lower rates of adverse outcomes (OR = 0.965; 95% CI 0.962 to 0.968; P < 0.0001).

conclusionsThe COVID-19 outbreak has deepened the gap between optimal care and clinical practice, which then gradually improved. During the pandemic, high-quality care was important to reduce the risk of adverse outcomes, but there were gender and age differences in the provision of health-care quality.

Indexed as

Ischemic StrokePandemicsQuality Indicators, Health CareQuality of Health CareStroke RehabilitationAdultAgedChinaCOVID-19Databases, FactualFacilities and Services UtilizationFemaleHealthcare DisparitiesHospital MortalityHumansInterrupted Time Series AnalysisAcute ischemic strokeCOVID-19Quality of care

Identifiers

PMID40753201
PMCPMC12317608

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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.