估计医生风险处方对医生与患者共同关系的基础网络结构的影响
Xin Ran1,2, Ellen Meara3,4, Nancy E Morden2,5
1Department of Biomedical Data Science, Geisel School of Medicine at Dartmouth, Lebanon, NH 03756 USA.
概括
医生倾向于与类似的处方者联系,在处方和抑郁行为中表现出同类性. 这一发现支持针对连接医生之间的风险处方的小组干预.
科学领域:
- 社交网络分析分析
- 公共卫生 公共卫生
- 医疗服务研究 医疗服务研究
背景情况:
- 医生协作网络对于了解医疗保健提供至关重要.
- 风险的处方,特别是对老年患者来说,是一个重大的公共卫生问题.
- 同性恋,或"相似吸引相似",可以影响专业网络和行为.
研究的目的:
- 在俄俄州的共享患者网络中调查医生处方和减压行为中的同类性.
- 确定处方行为是否塑造医生网络,并确定潜在的干预策略.
- 在像集团和三合一这样的网络结构中探索同类关系.
主要方法:
- 利用医疗保险D部分数据来衡量医生风险处方强度.
- 采用指数随机图模型来分析网络同类性.
- 开发了三元结构的新型网络措施和随机化测试.
主要成果:
- 在处方和失处处方方面发现了医生同志关系的重要证据.
- 在有风险的处方中观察到三位一体内同型性,超过机会水平.
- 结果表明,处方行为影响医生网络形成.
结论:
- 医生网络表现出同类性,类似的处方者形成连接.
- 研究结果支持针对有风险处方行为的医生进行群体级干预的理由.
- 该方法可以适应在其他网络环境中研究同类关系.
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