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Journal of Tuberculosis and Lung Disease ›› 2024, Vol. 5 ›› Issue (1): 58-63.doi: 10.19983/j.issn.2096-8493.2024010

• Original Articles • Previous Articles     Next Articles

Analysis of patient delay and its influencing factors among elderly pulmonary tuberculosis patients in Tongzhou District of Beijing, 2016—2022

Yang Chao, Wang Jing(), Tang Guilin, Gao Hanqing, Wang Bin   

  1. nstitute of Tuberculosis Prevention and Control, Tongzhou District Center for Disease Prevention and Control, Beijing 101100, China
  • Received:2023-12-09 Online:2024-02-20 Published:2024-02-02
  • Contact: Wang Jing,Email:tzjfs2008yangchao@126.com

Abstract:

Objective: To analyze the current situation and influencing factors of patient delay among elderly (≥60 years old) pulmonary tuberculosis (PTB) in Tongzhou District of Beijing from 2016 to 2022, and to provide scientific basis for reducing the patient delay in the future. Methods: Data of 963 cases of PTB patients in the elderly people in Tongzhou District of Beijing from 2016 to 2022 were extracted from the Tuberculosis Management Information System of China Information System for Disease Control and Prevention, including medical records, diagnosis and treatment information, and so on. Descriptive statistics was used to analyze the distribution and trend of patient delay. Influencing factors of patient delay was analyzed by multivariable logistic regression. Results: From 2016 to 2022, the median and quartile of patient delay days was 5 (0,32) days. The average patient delay rate was 40.08% (386/963). The median of patient delay days went down from 12 (0,37) days in 2016 to 0 (0,24) days in 2022. The patient delay rate changed from 34.39% (54/157) in 2016 to 50.42% (60/119) in 2019, showing a upward trend ( χ t r e n d 2=7.605,P=0.006), and then decreased to 30.99% (44/142) in 2022, showing a downward trend ( χ t r e n d 2=7.138,P=0.008). Multivariable logistic regression analysis showed that patient registered during 2020—2022 (OR=0.667,95%CI:0.508-0.876) was the protective factor for patient delay. Non-urban area (OR=1.368,95%CI:1.037-1.804) was the risk factor for patient delay. Conclusion: The patient delay showed an upward-then-downward trend from 2016 to 2022. The patient delay was related to year of registration and current address. It is necessary to perform targeted intervention measures.

Key words: Tuberculosis, pulmonary, Factor analysis, Beijing

CLC Number: