患者如何在医疗保健中区分临床和行政预测模型
Paige Nong1, Julia Adler-Milstein, Jodyn Platt
1Division of Health Policy and Management, University of Minnesota School of Public Health, 516 Delaware St SE, Minneapolis, MN 55455.
The American journal of managed care
|January 25, 2024
概括
患者更喜欢临床预测模型而不是行政模型. 健康数据隐私的透明度可以增加舒适性,但医疗保健不平等会对行政预测工具的看法产生负面影响.
科学领域:
- 医疗信息学 医疗信息学
- 患者体验研究 研究研究
- 卫生公平研究 卫生公平研究
背景情况:
- 预测模型在医疗保健中越来越多地用于临床和行政任务.
- 了解患者的感知对于这些技术的伦理和有效实施至关重要.
- 之前的研究还没有完全探索患者如何区分预测模型的各种应用.
研究的目的:
- 调查患者对预测模型在医疗保健中的特定应用的看法.
- 用临床与行政预测模型来确定影响患者舒适度的因素.
- 确定隐私问题和医疗保健经验对患者接受预测技术的影响.
主要方法:
- 一项针对美国成年人的全国在线调查于2021年11月至12月进行.
- 内部一致性测量评估了临床和行政预测模型之间的差异化.
- 多变量后勤回归分析了舒适度,人口统计,隐私感知和医疗保健系统经验之间的关系.
主要成果:
- 患者在临床和行政预测模型之间进行了区分.
- 对预测账单支付 (21.6%) 和错过预约 (36.6%) 的舒适度较低,但对于诸如中风风险 (55.8%) 等临床预测,舒适度较高.
- 经历歧视的经验对行政模式的舒适性有负面预测,而隐私政策的透明度对两种类型的舒适性有积极预测.
结论:
- 临床预测模型应用的患者舒适度高于行政应用.
- 加强隐私保护和透明的数据处理实践可以促进更多的患者接受.
- 解决医疗保健不平等问题和负面的患者体验对于改善对行政预测工具的看法至关重要.
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