从测试前和测试后的概率到医疗决策
Michelle Pistner Nixon1, Farhani Momotaz1, Claire Smith2
1College of Information Science and Technology, Pennsylvania State University, University Park, PA.
临床医生现在可以通过将成本整合到贝叶斯的测试前/测试后概率 (BPP) 框架中来做出更好的医疗决策. 这个简单的工具可以量化不确定性,并根据患者特定的成本和收益指导最佳行动.
科学领域:
- 医疗决策 - - 医疗决策
- 基于证据的医学基于证据的医学.
- 生物统计学 生物统计学
背景情况:
- 现代基于证据的医学旨在提供简单的工具,将定量信息整合到临床决策中.
- 贝叶斯前测试/后测试概率 (BPP) 框架量化了诊断不确定性,但没有将其与决策成本和收益相平衡.
- 对于定量临床决策的简单,灵活的方法仍然难以捉摸.
结论:
- 拟议的方法是BPP框架的核心,以前被忽视的组成部分.
- 它简化了定量临床决策,特别是对于患者特定的,难以量化的成本和效益.
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