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何蕾, 高博, 任晓晖, 等. 社会资本对居民就医机构选择的影响研究—基于分类树与logistic回归模型相结合的方法[J]. koko体育app 学报（医学版）, 2022, 53(2): 310-315. DOI:
引用本文: 何蕾, 高博, 任晓晖, 等. 社会资本对居民就医机构选择的影响研究—基于分类树与logistic回归模型相结合的方法[J]. koko体育app 学报（医学版）, 2022, 53(2): 310-315. DOI:
HE Lei, GAO Bo, REN Xiao-hui, et al. Impact of Social Capital on Residents' Choice of Medical Institutions: A Study Based on Classification Tree Model and Logistic Regression[J]. Journal of Sichuan University (Medical Sciences), 2022, 53(2): 310-315. DOI:
Citation: 🐻 HE Lei, GAO Bo, REN Xiao-hui, et al. Impact of Social Capital on Residents' Choice of Medical Institutions: A Study Based on Classification Tree Model and Logistic Regression[J]. Journal of Sichuan University (Medical Sciences), 2022, 53(2): 310-315. DOI:

社会资本对居民就医机构选择的影响研究—基于分类树与logistic回归模型相结合的方法

Impact of Social Capital on Residents' Choice of Medical Institutions: A Study Based on Classification Tree Model and Logistic Regression

  • 摘要:
      目的  探讨社会资本对居民就医机构选择的影响，为推动分级诊疗提供参考依据。
      方法  采用Exhaustive CHAID法建立分类树模型对居民就医机构选择的影响因素进行筛选，采用logistic回归模型定量分析影响因素的交互作用效应。
      结果  分类树模型包括4层，8个终末结点，共筛选出个体社会资本、自评生理健康、文化程度、社区社会资本、慢病患病和自评心理健康6个影响因素。logistic回归分析显示，文化程度〔比值比（odds ratio, OR）=0.660，95%置信区间（confidence interval, CI）：0.502～0.869〕，社区社会资本（OR=0.746，95% CI：0.589～0.943）和个体社会资本（OR=0.405，95% CI：0.287～0.572）对居民就医机构选择有影响（P<0.001）。个体社会资本与自评生理健康对居民就医机构选择存在交互作用（OR=1.872，95% CI：1.180～2.969，P<0.05）。
      结论  应考虑从社会资本因素进行干预，进而促进居民合理利用医疗资源。
     
    Abstract:
      Objective  To explore the influence of social capital on the local residents' choice of medical institutions and to provide a reference basis for promoting diagnosis and treatment services available at different tiers.
      Methods  A classification tree model was established using the exhaustive chi-square automatic interaction detection (Exhaustive CHAID) method to screen for factors influencing the residents' choice of medical institutions, and a logistic regression model was used to quantitatively analyze the interaction effect of the influencing factors.
      Results  The classification tree model showed that there were four layers and eight terminal nodes, identifying a total of six influencing factors, including individual social capital, self-reported physical health, education, community social capital, chronic disease prevalence, and self-reported mental health. Logistic regression analysis showed that education (odds ratio OR=0.660, 95% confidence interval CI: 0.502-0.869), community social capital (OR=0.746, 95% CI: 0.589-0.943), and individual social capital (OR=0.405, 95% CI: 0.287-0.572) (P<0.001) had an impact on residents' choice of medical institution. There was an interaction between individual social capital and self-reported physical health on residents' choice of medical institution (OR=1.872, 95% CI: 1.180-2.969, P<0.05).
      Conclusion  Interventions in terms of social capital factors should be considered in order to promote the rational use of medical resources.
     
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