约旦成年慢性病患者的药物坚持:使用回归和机器学习的综合分析
Walid Al-Qerem1, Anan Jarab2, Judith Eberhardt3
1Department of Pharmacy, Faculty of Pharmacy, Al-Zaytoonah University of Jordan, Amman, Jordan.
Annals of medicine
|August 20, 2025
概括
患者的健康素养和保险类型在慢性疾病管理中对药物坚持有重大影响. 干预措施应解决个人理解和系统性障碍,以改善遵守.
科学领域:
- 医疗服务研究
- 数字健康
- 慢性疾病管理
背景情况:
- 慢性疾病的有效治疗主要取决于患者的药物服药.
- 了解影响患者坚持治疗的因素对于改善患者的治疗结果至关重要.
研究的目的:
- 研究影响约旦成年慢性疾病患者服药的因素.
- 将传统的回归与机器学习进行比较,以预测附着性.
主要方法:
- 在981名患有慢性疾病的患者中进行了横截面在线调查.
- 评估人口,临床和行为变量,包括健康素养问卷 (HLQ-12) 和药物坚持评分表 (MARS-5).
- 应用量子回归和机器学习 (随机森林,SHAP分析).
主要成果:
- 较高的健康素养,糖尿病/心血管疾病诊断和较少的药物与坚持相关.
- 婚姻和公共/军事/没有保险与较低的保证率有关.
- 随机森林模型的准确性最高 (R2 = 0.38);SHAP确定了健康素养,疾病持续时间和年龄作为关键预测因素.
结论:
- 干预措施应针对健康素养和保险和治疗复杂性等结构因素.
- 提高健康素养和简化治疗方案可以提高患者的坚持.
- 在资源有限的环境中,可解释的人工智能提供了新的洞察力.
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