来自英国南威尔士的警察家庭虐待数据和健康数据的链接的见解:使用决策树分类的链接例行数据分析
Natasha Kennedy1, Tint Lwin Win2, Amrita Bandyopadhyay1
1National Centre for Population Health and Wellbeing Research, Swansea, UK.
The Lancet. Public health
|July 29, 2023
概括
通过将警察和卫生数据联系起来,确定了家庭虐待受害者的风险因素. 易受伤害的个体可以在事件发生前和之后被识别,以改善结果并减少医疗保健利用率.
科学领域:
- 公共卫生 公共卫生
- 数据科学数据科学数据科学
- 犯罪学 犯罪学
背景情况:
- 家庭虐待有严重的,持久的身体和心理影响.
- 根据"犯罪和混乱法" (Crime and Disorder Act) 的规定,各机构在减少犯罪方面进行合作,包括共享数据.
- 连接整个机构的数据仍然是一个挑战,限制了对家庭虐待影响的全面理解.
研究的目的:
- 整合警方和医疗保健数据,用于家庭虐待受害者.
- 识别与不利结果相关的风险因素集群.
- 分析从链接数据集中获得的知识,以改善受害者护理.
主要方法:
- 在南威尔士 (2015-2020年) 的家庭虐待受害者的回顾性队列研究.
- 通过安全匿名信息链接数据库,将公众保护通知 (PPN) 和健康记录之间的数据链接.
- 分析使用卡普兰-梅尔生存分析和多变量考克斯回归来确定风险因素和风险分层的决策树.
主要成果:
- 包括8709名家庭虐待受害者; 71.8%是女性.
- 41.9%的人在PPN的12个月内经历了结果 (急诊室出院,住院或死亡).
- 关键的风险因素包括年龄较小,进一步的PPN,受伤,高评估风险,转介给其他机构,暴力史,杀企图和怀孕. 事件前的健康因素,如先前的入院,吸烟和抗抑郁药物处方,也与结果有关.
结论:
- 在警察参与之前和之后,可以使用综合的警察和健康数据来识别脆弱的个人.
- 运用这些发现可以减少警察的呼叫和紧急医疗保健的使用.
- 审查过去的住院病例和对孕妇受害者的风险评估等策略可以改善弱势群体的结果.
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