在多种长期条件下风险预测工具管理:定性研究
Stella Arakelyan1, Atul Anand2, Stewart W Mercer3
1University of Edinburgh, Edinburgh, United Kingdom stella.arakelyan@ed.ac.uk.
概括
针对多种长期疾病 (MLTC) 的风险预测工具有希望,但需要仔细实施. 医疗保健专业人员和患者强调需要整合临床判断,考虑心理社会因素,并与患者优先事项保持一致的工具.
科学领域:
- 医疗保健服务研究 医疗服务研究
- 临床信息学 临床信息学
- 以患者为中心的护理
背景情况:
- 风险分层对于有效的医疗保健服务至关重要.
- 它在治疗多种长期疾病 (MLTC) 患者中的应用需要进一步研究.
研究的目的:
- 探索医疗保健专业人员,患者和护理人员对在MLTC管理中使用风险预测工具的好处和挑战的看法.
主要方法:
- 该研究涉及对30名医疗保健专业人员的专题分析,以及对28名MLTC患者及其护理人员的6个重点小组的采访.
- 数据收集发生在2023年5月至2024年5月期间,涉及四个苏格兰综合健康和社会护理伙伴关系.
主要成果:
- 医疗保健专业人员对当前风险预测工具的临床实用性和算法偏差表示担忧,强调需要与临床判断和心理社会因素进行整合.
- 患者和护理人员对潜在的焦虑和失去与风险沟通有关的自主性表示担忧,强调了上下文相关性和患者优先事项的重要性.
- 人工智能 (AI) 和常规数据具有提高预测准确性的潜力,但需要强大的IT基础设施,培训和人类监督.
结论:
- 如果不增加工作量,支持临床决策,并纳入患者的复杂性和偏好,那么AI知情的风险分层工具可能对MLTC管理有益.
- 有效实施需要解决有关临床效用,工作量和以患者为中心的沟通方面的担忧.
相关概念视频
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