在成和并发性疾病中的临床决策支持系统:系统性审查和元分析
Andy Man Yeung Tai1, Jane J Kim1, Jim Schmeckenbecher2
1Department of Psychiatry, Faculty of Medicine, University of British Columbia, Vancouver, British Columbia, Canada.
Journal of evaluation in clinical practice
|July 9, 2024
概括
临床决策支持系统 (CDSS) 正在向心理健康中的数据驱动模型发展. 虽然CDSS对成结果来说很适度,但它显著提高了患者的满意度,这表明尽管存在实施挑战,但CDSS有可能得到更广泛的采用.
科学领域:
- 数字健康数字健康
- 临床信息学 临床信息学
- 心理健康保健技术 技术
背景情况:
- 临床决策支持系统 (CDSS) 在心理健康,成和并发性疾病治疗中的整合是一个日益增长的研究领域.
- 了解CDSS的有效性,演变和实施挑战对于优化患者护理至关重要.
研究的目的:
- 综合现有的关于实施CDSS在心理健康和成服务中的有效性,发展轨迹和挑战的文献.
- 评估CDSS对患者结果的影响,包括治疗疗效,满意度和治疗接受度.
主要方法:
- 按照PRISMA指南进行了系统审查和元分析.
- 通过对主要数据库 (MEDLINE,Embase,CINAHL,PsycINFO,Web of Science) 到2023年5月的搜索,确定了27,344个记录,其中69项研究被纳入最终合成.
- 对随机对照试验数据应用了元分析技术,以评估患者的结果.
主要成果:
- 2017年后,从基于知识的CDSS模型到数据驱动的CDSS模型发生了显著的转变,与人工智能和大数据的进步相吻合.
- 分析表明,对于与成相关的结果,效果大小很小 (-0.11),但对于改善患者满意度和接受CDSS的效果大小更大 (-0.50).
- 大多数实施的CDSS模型都处于技术成熟度的第二或第四阶段.
结论:
- 数据驱动的CDSS方法正在出现,由技术进步驱动,显示出对心理健康和成治疗的希望.
- 虽然目前对成结果的直接影响有限,但患者满意度的提高表明了积极的接待和更广泛实施的潜力.
- 关键的挑战,如警报疲劳和人工智能模型的"黑子"性质,需要仔细考虑道德和有效的部署.
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