Suppr超能文献

分析促进慢性病患者参与药物治疗共享决策的因素:中国湖北省的横断面调查。

Analysis of factors that promote the participation of patients with chronic diseases in shared decision making on medication: a cross-sectional survey in Hubei Province, China.

机构信息

School of Medicine and Health Management, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China.

Science and Education Department, Traditional Chinese and Western Medicine Hospital of Wuhan, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430014, Hubei, China.

出版信息

BMC Public Health. 2023 Dec 6;23(1):2440. doi: 10.1186/s12889-023-17099-0.

Abstract

BACKGROUND

Shared decision making (SDM) improves the health status of patients with chronic diseases, especially in the condition of poly-medicated patients. This study aims to find the factors associated with participation of patients with chronic diseases in SDM on medication.

METHODS

A total of 1,196 patients with chronic diseases were selected in Hubei Province of China using cluster sampling methods. The random forest method was applied to rank the importance of independent variables by Mean Decrease Gini and out-of- bag (OOB) curve. Multivariate logistic regression was used to explore the independent variables' effect direction and relative hazard.

RESULTS

In this study, 5.18% of patients used patient-directed decision making (PDM, a decision-making model led by patients), 37.79% of patients used SDM (a collaborative decision-making model by patients and doctors), and 57.02% of patients used doctor-directed decision making (DDM, or paternalistic decision making, a decision-making model led by doctors). The random forest analysis demonstrated that the top 5 important factors were age, education, exercise, disease course, and medication knowledge. The OOB curve showed that the error rate reached minimum when top 5 variables in importance ranking composed an optimal variable combination. In multivariate logistic regression, we chose SDM as a reference group, and identified medication knowledge (OR = 2.737, 95%CI = 1.524 ~ 4.916) as the influencing factor between PDM and SDM. Meanwhile, the influencing factors between DDM and SDM were age (OR = 0.636, 95%CI = 0.439 ~ 0.921), education (OR = 1.536, 95%CI = 1.122 ~ 2.103), exercise (OR = 1.443, 95%CI = 1.109 ~ 1.877), disease course (OR = 0.750, 95%CI = 0.584 ~ 0.964), and medication knowledge (OR = 1.446, 95%CI = 1.120 ~ 1.867).

CONCLUSION

Most Chinese patients with chronic diseases used DDM during their medication decision-making, and some patients used PDM and SDM. The participation in SDM should be taken seriously among elderly patients with lower education levels. The SDM promotion should focus on transformation of patients' traditional perception and enhance their medication knowledge.

摘要

背景

共同决策(SDM)可改善慢性病患者的健康状况,尤其是在多用药患者的情况下。本研究旨在找出与慢性病患者参与药物治疗的 SDM 相关的因素。

方法

采用整群抽样方法,从中国湖北省选取 1196 例慢性病患者。应用随机森林法通过平均减少基尼系数(Mean Decrease Gini)和袋外(Out-of- bag,OOB)曲线对自变量的重要性进行排序。采用多因素 logistic 回归分析探讨自变量的作用方向和相对危险度。

结果

本研究中,5.18%的患者采用患者导向决策(PDM,以患者为导向的决策模式),37.79%的患者采用 SDM(患者和医生共同决策的协作决策模式),57.02%的患者采用医生导向决策(DDM,或家长式决策,以医生为导向的决策模式)。随机森林分析表明,前 5 个重要因素是年龄、教育程度、运动、病程和用药知识。OOB 曲线显示,当按重要性排序的前 5 个变量组成最佳变量组合时,错误率达到最低。多因素 logistic 回归分析中,我们选择 SDM 作为参考组,发现用药知识(OR=2.737,95%CI=1.5244.916)是 PDM 和 SDM 之间的影响因素。同时,DDM 和 SDM 之间的影响因素是年龄(OR=0.636,95%CI=0.4390.921)、教育程度(OR=1.536,95%CI=1.1222.103)、运动(OR=1.443,95%CI=1.1091.877)、病程(OR=0.750,95%CI=0.5840.964)和用药知识(OR=1.446,95%CI=1.1201.867)。

结论

大多数中国慢性病患者在药物治疗决策中使用 DDM,部分患者使用 PDM 和 SDM。应重视老年、低教育程度患者参与 SDM。SDM 的推广应注重转变患者的传统观念,增强其用药知识。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/aad2/10701977/4bdbfa019f0a/12889_2023_17099_Fig1_HTML.jpg

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验