在非保险患者的紧急医疗接触期间的阿片类药物和抗菌素处方模式
Michael A Grasso1, Anantaa Kotal2, Anupam Joshi2
1University of Maryland School of Medicine, Baltimore, Maryland.
没有保险的急诊患者接受的阿片类药物和抗菌素处方较少,往往得到非阿片类药物的替代品. 影响这一点的关键因素包括住房,健康状况和重复访问.
科学领域:
- 医疗保健服务研究 医疗服务研究
- 药理学 药理学是指药理学的学科.
- 医疗保健中的机器学习
背景情况:
- 没有保险的个人在获得医疗保健方面面临着独特的挑战.
- 处方模式的疼痛和感染管理在紧急情况下需要检查.
研究的目的:
- 分析非保险急诊室 (ED) 患者的阿片类药物和抗菌素处方.
- 开发能够预测这些处方模式的机器学习 (ML) 模型.
主要方法:
- 对ED患者数据的回顾性分析.
- 开发和验证预测性ML模型.
- 确定主要的人口和临床预测因素.
主要成果:
- 非保险患者的阿片类药物处方比保险患者少.
- 对于没有保险的人来说,非阿片类药物疼痛替代品更为常见.
- 在没有保险的患者中,抗菌素处方率较低.
- 住房状况,并发病症和患者复发症显著影响了处方决策.
结论:
- 在紧急护理的无保险患者中存在处方差异.
- 机器学习可以识别影响这些差异的因素.
- 需要进一步的研究,以解决弱势群体的公平疼痛和感染管理问题.
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