通过状态序列分析,捕捉精神分裂症患者的各种临床途径
Laura Savaré1,2,3, Francesca Ieva4,5,6, Giovanni Corrao6,7
1MOX - Department of Mathematics, Politecnico di Milano, Milan, Italy. laura.savare@polimi.it.
BMC medical research methodology
|July 29, 2023
概括
状态序列分析在患有严重精神障碍的患者中发现了三种不同的治疗模式. 这种数据驱动的方法可以帮助优化护理途径和个性化患者治疗计划,以获得更好的心理健康结果.
科学领域:
- 医疗信息学 医疗信息学
- 数据挖掘 数据挖掘
- 心理健康研究 心理健康研究
背景情况:
- 护理途径对于优质的医疗保健至关重要,但往往缺乏基于证据的治疗序列.
- 经典的统计方法在与现实世界医疗保健数据的变化作斗争.
- 数据挖掘技术,如状态序列分析,可以从例行数据中识别有效的护理模式.
研究的目的:
- 应用状态序列分析 (SSA) 来识别严重精神障碍的不同治疗模式.
- 评估SSA对基于患者的护理途径进行分析的实用性.
主要方法:
- 该研究分析了伦巴第地区2015-2018年精神分裂症患者的行政数据.
- 患者的护理路径被视为每周治疗状态的序列 (精神病学访问,心理干预,抗精神病药物).
- 最长的常见子序列 (不相似性) 测量用于序列比较和聚类.
主要成果:
- 确定了三种不同的患者治疗模式集群.
- 这些集群显示了患者接受护理序列的显著差异.
结论:
- SSA 是一种有价值的工具,用于理解和分析患者的纵向治疗模式.
- 识别共同的护理模式可以为卫生政策制定者提供资源分配和个性化患者护理的信息.
- 这种方法有助于分析人口健康趋势,并确定心理健康下降的风险因素.
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