Department of Emergency Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA.
BerbeeWalsh Department of Emergency Medicine, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA.
J Am Geriatr Soc. 2024 Jan;72(1):258-267. doi: 10.1111/jgs.18594. Epub 2023 Oct 9.
Geriatric emergency department (GED) guidelines endorse screening older patients for geriatric syndromes in the ED, but there have been significant barriers to widespread implementation. The majority of screening programs require engagement of a clinician, nurse, or social worker, adding to already significant workloads at a time of record-breaking ED patient volumes, staff shortages, and hospital boarding crises. Automated, electronic health record (EHR)-embedded risk stratification approaches may be an alternate solution for extending the reach of the GED mission by directing human actions to a smaller subset of higher risk patients.
We define the concept of automated risk stratification and screening using existing EHR data. We discuss progress made in three potential use cases in the ED: falls, cognitive impairment, and end-of-life and palliative care, emphasizing the importance of linking automated screening with systems of healthcare delivery.
Research progress and operational deployment vary by use case, ranging from deployed solutions in falls screening to algorithmic validation in cognitive impairment and end-of-life care.
Automated risk stratification offers a potential solution to one of the most pressing problems in geriatric emergency care: identifying high-risk populations of older adults most appropriate for specific GED care. Future work is needed to realize the promise of improved care with less provider burden by creating tools suitable for widespread deployment as well as best practices for their implementation and governance.
老年急诊科(GED)指南支持在急诊科对老年患者进行老年综合征筛查,但在广泛实施方面存在重大障碍。大多数筛查计划需要临床医生、护士或社会工作者的参与,这在急诊科患者数量创历史新高、人员短缺和医院病床危机的情况下,进一步增加了已经繁重的工作量。自动化、电子健康记录(EHR)嵌入式风险分层方法可能是通过将人为干预指向风险较高的较小患者子集来扩大 GED 任务范围的替代解决方案。
我们使用现有的 EHR 数据定义自动化风险分层和筛查的概念。我们讨论了在急诊科的三个潜在用例中取得的进展:跌倒、认知障碍以及临终关怀和姑息治疗,强调了将自动化筛查与医疗保健提供系统联系起来的重要性。
研究进展和运营部署因用例而异,从跌倒筛查的已部署解决方案到认知障碍和临终关怀的算法验证。
自动化风险分层为老年急诊护理中最紧迫的问题之一提供了潜在的解决方案:确定最适合特定 GED 护理的高风险老年人群。需要进一步的工作来通过创建适合广泛部署的工具以及为其实施和治理制定最佳实践来实现改善护理和减轻提供者负担的承诺。