Multiple Correspondence Analysis of the Influence of Heterogeneity in Sample Composition on the Investigation Results of Primary Chronic Disease Management Quality

Autor: YU Guo, CHEN Jinhua, WU Yuelei, LIU Shuyi, DU Wen, XIAO Zhu, WANG Yijun
Jazyk: čínština
Rok vydání: 2024
Předmět:
Zdroj: Zhongguo quanke yixue, Vol 27, Iss 28, Pp 3515-3519 (2024)
Druh dokumentu: article
ISSN: 1007-9572
DOI: 10.12114/j.issn.1007-9572.2022.0682
Popis: Background The assessment of chronic disease management capabilities in healthcare institutions is an important element of chronic disease management, but the researchers did not pay attention to the impact of sample heterogeneity on the scientific validity of survey results when using relevant scales, which requires our attention. Objective To explore the impact of the heterogeneity of sample composition on the evaluation results of the scale and put forward countermeasures based on the investigation of chronic disease management quality in primary medical institutions in Chengdu. Methods In February 2022, a total of 889 medical workers was selected from 46 primary care institutions in 23 prefectures and districts (counties) of Chengdu City by using multi-stage stratified cluster sampling method. The Chinese version of Assessment of Chronic Illness Care (ACIC) was used to assess the quality scores of chronic disease management in the medical institutions. Multiple correspondence analysis was used to explore the impact of sample heterogeneity caused by different genders, years of experience, professional titles, educational levels and job composition on the scale scores. Results The total score of chronic disease management competence of medical workers was negatively correlated with their education level and positively correlated with their professional title (P
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