Design and statistical analysis reporting among interrupted time series studies in drug utilization research: a cross-sectional survey.

Authors:
Zhang Y; Ren Y; Huang Y; Yao M; Jia Y and 5 more

Journal:
BMC Med Res Methodol

Publication Year: 2024

DOI:
10.1186/s12874-024-02184-8

PMCID:
PMC10924989

PMID:
38461257

Journal Information

Journal Title: BMC Med Res Methodol

Detailed journal information not available.

Publication Details

Subject Category: Health Care Sciences & Services

Available in Europe PMC: Yes

Available in PMC: Yes

PDF Available: No

Transparency Score
4/6
66.7% Transparent
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Evidence found in paper:

"table 1 general characteristics of included its studies (n=153) characteristics n % study sites multi-sites108 70 6 single-site 45 29 4 data source a hospital data (from electronic medical record) 60 39 2 other administrative databases54 35 3 insurance (claims) database 27 17 6 others b 12 7 8 intervention stages single 126 82 4 multiple 27 17 6 type of intervention prescription restriction 45 29 4 drug price change (price purchase or reimbursement policy) 27 17 6 clinical guideline change (guidelines statements or publications) 23 15 0 education or training for physicians22 14 4 digital technology 13 8 5 drug safety advisory 13 8 5 drug approval or withdrawal 8 5 2 others c 2 1 3 level of intervention national 90 58 8 hospital 30 19 6 state or province 21 13 7 region 6 3 9 others d 6 3 9 measure type of outcome drug utilization 125 81 7 health outcomes17 11 1 expenditures10 6 5 others e 1 0 7 data type of outcome rate 98 64 1 continuous38 24 8 count 15 9 8 binary 2 1 3 a administrative medical databases are massive repositories of data collected in healthcare for various purposes."

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Evidence found in paper:

"Declarations Ethics approval and consent to participateNot applicable. Consent for publicationNot applicable. Competing interestsThe authors declare no competing interests. Competing interests The authors declare no competing interests."

Evidence found in paper:

"Funding This study was supported by National Natural Science Foundation of China (Grant No. 72004149), China Postdoctoral Science Foundation (Grant No. 2022M720101), National Science Fund for Distinguished Young Scholars (Grant No. 82225049), Sichuan Provincial Central Government Guides Local Science and Technology Development Special Project (Grant No. 2022ZYD0127) and Xiamen Science and Technology Plan Project (3502Z20224004)."

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Last Updated: Aug 05, 2025