鉴定精神分裂症高成本患者的独特子组:使用隐性类分析的基于人口的研究
Andrew J Stewart1, Scott B Patten1,2, Kirsten M Fiest1
1Department of Community Health Sciences, Cumming School of Medicine, University of Calgary, AB, Calgary, Canada.
Health services insights
|June 28, 2023
概括
这项研究使用行政健康数据确定了五个不同的高成本精神分裂症患者子组. 了解这些患者的个人资料可以改善医疗保健系统的护理和资源配置.
科学领域:
- 医疗保健服务研究 医疗服务研究
- 精神病学是一个精神病学.
- 数据科学数据科学数据科学
背景情况:
- 精神分裂症患者的护理高度变化,需要量身定制的医疗保健支持.
- 关于精神分裂症患者需求异质性的研究有限.
- 与精神分裂症相关的高医疗费用需要有效的资源配置.
研究的目的:
- 在高成本的精神分裂症患者中确定患者子组.
- 为改善患者的治疗结果提供有针对性的干预措施.
- 引导医疗保健系统内的高效资源分配.
主要方法:
- 来自加拿大阿尔伯塔省 (2017年) 的行政卫生数据的回顾性分析.
- 包括住院,门诊,急诊室和药物开支的成本.
- 隐性类分析应用于1659名高成本成年精神分裂症患者.
主要成果:
- 根据临床资料确定了五个不同的患者子组.
- 小组包括:年轻的高需要的男性,积极管理的中年患者,伴随疾病和多药的老年患者,以及不稳定的男性和女性,治疗率和急性护理利用率各不相同.
- 这些分类突出了与年龄,住房稳定性,治疗参与和医疗保健利用有关的各种需求.
结论:
- 高成本精神分裂症患者的数据驱动分类学可以为政策提供信息.
- 特定小组的干预措施可以提高护理质量并减少医疗保健支出.
- 这种方法支持对精神分裂症护理的更有效和更有效的资源管理.
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