Evidence map›Paper›PMID 39986999›Full record

Observational studyBMJ open2025

Impact of insurance coverage for non-vitamin K antagonist oral anticoagulants on quality of care and care disparities in patients hospitalised with atrial fibrillation in tertiary hospitals in China: interrupted time series analysis.

Na Yang, Zhaoqing Sun, Jun Liu, Yongchen Hao, Deyong Long, Dong Zhao, Jing Liu, CCC-AF Investigators

Registry-linked trialAbstract readObservational Study
In one paragraph

Observational study in BMJ open, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT02309398 (Improving Care for Cardiovascular Disease in China), which is not on this 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

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

NCT02309398 completednot on this map

Improving Care for Cardiovascular Disease in China: A Collaborative Project of AHA and CSC (CCC Project) - Atrial Fibrillation

TypeobservationalSponsorBeijing Institute of Heart, Lung and Blood Vessel DiseasesRan2015 to 2020Enrolled67,028ConditionsAtrial Fibrillation
3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Na Yang *Center for Clinical and Epidemiologic Research, Beijing Anzhen Hospital, Capital Medical University, Beijing Institute of Heart, Lung and Blood Vessel Diseases, Beijing, People's Republic of China.
Zhaoqing Sun *Department of Cardiology, Beijing Anzhen Hospital, Capital Medical University; National Clinical Research Center for Cardiovascular Diseases, Beijing, People's Republic of China.
Jun LiuCenter for Clinical and Epidemiologic Research, Beijing Anzhen Hospital, Capital Medical University, Beijing Institute of Heart, Lung and Blood Vessel Diseases, Beijing, People's Republic of China.
Yongchen HaoCenter for Clinical and Epidemiologic Research, Beijing Anzhen Hospital, Capital Medical University, Beijing Institute of Heart, Lung and Blood Vessel Diseases, Beijing, People's Republic of China.
Deyong LongDepartment of Cardiology, Beijing Anzhen Hospital, Capital Medical University; National Clinical Research Center for Cardiovascular Diseases, Beijing, People's Republic of China.
Dong ZhaoCenter for Clinical and Epidemiologic Research, Beijing Anzhen Hospital, Capital Medical University, Beijing Institute of Heart, Lung and Blood Vessel Diseases, Beijing, People's Republic of China.ORCID http://orcid.org/0000-0002-3239-3449
Jing LiuCenter for Clinical and Epidemiologic Research, Beijing Anzhen Hospital, Capital Medical University, Beijing Institute of Heart, Lung and Blood Vessel Diseases, Beijing, People's Republic of China jingliu@ccmu.edu.cn.ORCID http://orcid.org/0000-0002-3311-0818
CCC-AF Investigators

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo examine recent patterns regarding oral anticoagulant (OAC) use among patients hospitalised with atrial fibrillation (AF) and quantify the impact of insurance coverage for non-vitamin K oral anticoagulants (NOACs) on quality of care and care inequality regarding OAC use among hospitalised patients with AF.

designInterrupted time series analysis.

settingHospitals in China.

participantsA total of 36 393 patients hospitalised with non-valvular AF were involved between 2015 and 2019 across China. PRIMARY AND SECONDARY OUTCOME MEASURES: Outcome was the impact of insurance coverage for NOACs on quality of care regarding OAC prescription using interrupted time series analysis with segmented regression models.

resultsOAC prescription rate during hospitalisation was 52.1% (31.3% for warfarin and 20.8% for NOACs) in patients with high-risk AF and 66.3% (29.8% for warfarin and 36.5% for NOACs) in low-risk patients. Insurance coverage for NOACs was associated with an immediate 10.9% (95% CI 7.6% to 14.3%) increase in NOAC prescription and a 0.33% (95% CI 0.08% to 0.58%) increase in the slope of the secular trend of NOAC prescription among all the patients. Disparities in NOAC prescription among hospitals decreased from 18.9 before the insurance coverage for NOACs to 3.4 after that. Similar results were found in patients with high risk of stroke.

conclusionA large gap exists between clinical practice and guideline recommendations regarding OAC prescription among patients hospitalised with AF in China. Insurance coverage may be an effective healthcare strategy to improve quality of care and reduce care disparities regarding OAC prescription among patients with AF. TRIAL REGISTRATION NUMBER: NCT02309398.

Indexed as

AnticoagulantsAtrial FibrillationHealthcare DisparitiesInsurance CoverageQuality of Health CareStrokeAdministration, OralAgedAged, 80 and overChinaFemaleHospitalizationHumansInterrupted Time Series AnalysisMaleMiddle AgedAnticoagulantsWarfarinCardiovascular DiseaseEPIDEMIOLOGIC STUDIESHealth policy

Identifiers

PMID39986999
PMCPMC11848658

What OpenQuestion holds

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Registered trials

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.