Preventing Future Falls among Older Adults Presenting to the Emergency Department

项目摘要/摘要 美国老年人依靠急诊科(ED)进行紧急、计划外的护理。不幸的是，许多年纪更大的 成年人在急诊室就诊后的结果很差，这表明这些相遇代表错过了 有机会识别高危患者并进行干预，以改善向门诊护理的过渡。特别是， 老年人的显著跌倒是一个严重的、可以预防的问题。教育署不定期探访可提供 在下列情况下识别跌倒风险比普通初级保健人口高的老年人的机会 跌倒风险因素可以修改，因此为初级保健以外的跌倒筛查提供了理想的额外设置。 这种筛查是在急诊科倡导的，但筛查干预往往因为提供者的时间限制而失败 在紧急情况下。随着电子健康记录(EHR)系统的发展，计算机化的决策支持 提供了支持秋季筛查的潜力，同时减少了提供商的负担。这项提案的目标是确定 未来跌倒的高危成年人，并在急诊期间和出院后改善他们的护理。 作为一名内科科学家，我的目标是领导一个独立的研究项目，以改善向门诊的过渡 对老年人进行急诊室探视后的护理。这项为期5年的提案将通过提供必要的 在执行科学以及基于信息学的干预措施方面的支助和培训。我有一个独一无二的 有工程学、急救医学和卫生服务研究的背景，并做好准备 成功完成建议书。我将得到一个机构的专家导师团队的帮助，该机构拥有大量 资源和优秀的环境为开展研究提出了建议，并向独立 具有R01支持的调查员。 建议的目标是：1)将基于电子病历的数据提取与未来门诊患者的亲自筛查进行比较 跌倒风险，2)使用演示时EHR中可用的数据，开发预测算法来风险- 对ED患者在接下来的6个月内显著跌倒的风险进行分层，以及3)设计并试行临床决策 支持干预措施，以识别跌倒高危老年人，并改善他们在急诊室和急诊室后的护理 出院。这些目标将通过创建和分析将电子健康记录和索赔联系起来的数据库来实现 数据，结合了自然语言处理得出的新元素，通过利用机器学习 除了传统的统计技术之外，还通过在一个卫生系统中开发和试点干预措施。

PROJECT SUMMARY/ABSTRACT Older Americans rely on the emergency department (ED) for acute, unscheduled care. Unfortunately, many older adults experience poor outcomes after ED visits, suggesting that these encounters represent missed opportunities to identify high risk patients and intervene to improve the transition to outpatient care. In particular, significant falls among older adults are a serious and preventable problem. Unscheduled ED visits offer an opportunity to identify older adults at higher risk of falls than the general primary care population at a time when fall risk factors can be modified, and thus offer an ideal additional setting for fall screening beyond primary care. Such screening is advocated in the ED, but screening interventions often fail due to time constraints of providers in the emergency setting. As electronic health record (EHR) systems evolve, computerized decision support offers the potential to support fall screening with less provider burden. The objective of this proposal is to identify adults at high risk for future falls and improve their care both during their ED visit and after discharge. As a physician scientist, my goal is to lead an independent research program to improve transitions to outpatient care following ED visits for older adults. This 5-year proposal will advance these goals by providing the necessary support and training in implementation science as well as informatics-based interventions. I have a unique background in engineering, emergency medicine, and health services research and am well prepared to successfully complete the proposal. I will be aided by a team of expert mentors at an institution with substantial resources and an outstanding environment to conduct the research proposed and transition to an independent investigator with R01 support. The proposed aims are to: 1) Compare EHR-based data extraction to in-person screening of future outpatient fall risk, 2) Using data available in the EHR at the time of presentation, develop a predictive algorithm to risk- stratify ED patients for risk of significant falls in the next 6 months, and 3) Design and pilot a clinical decision support intervention to identify older adults at high risk of falls and improve their care both in the ED and after discharge. These aims will be accomplished by creating and analyzing a database linking the EHR and claims data, incorporating novel elements derived by natural language processing, by utilizing machine learning in addition to traditional statistical techniques, and by developing and piloting an intervention in one health system.