Elucidating Non-Routine Events Arising from Interhospital Transfers

阐明院间转移引起的非常规事件

• 批准号: 10749448
• 负责人: Michael J. Ward
• 金额: --
• 依托单位: VETERANS HEALTH ADMINISTRATION
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-10-01 至 2025-03-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10749448
• 关键词: Academic Medical Centers; Accident and Emergency department; Accounting; Acute; Acute myocardial infarction; Address; Admission activity; Adverse event; Area; Award; Cardiology; Caring; Categories; Clinical; Collection; Communication; Community Healthcare; Computational algorithm; Data; Data Collection; Detection; Deterioration; Development; Documentation; Education; Elderly; Emergency Care; Emergency Medicine; Emergency Situation; Emergency department visit; Engineering; Environment; Evaluation; Event; Failure; Family; Family member; Feasibility Studies; Floor; Foundations; Future; Health Information System; Health Services Accessibility; Health system; Healthcare; Healthcare Systems; Hospitalization; Hospitals; Hour; Human; Incidence; Informatics; Information Systems; Injury; Institution; Intervention; Interview; Length of Stay; Literature; Manuals; Medical Records; Medical center; Medicine; Methods; Modeling; Natural Language Processing; Outcome; Patients; Perioperative; Population; Process; Provider; Psyche structure; Qualifying; Qualitative Methods; Qualitative Research; Records; Reporting; Research; Resources; Safety; Sampling; Scanning; Science; Services; Severities; Site; Surveys; System; Tennessee; Text; Time; Training; Veterans; Work; acute care; biomedical informatics; care costs; care episode; clinical care; clinical center; clinical predictors; cost; data exchange; data quality; design; digital imaging; experience; field study; high risk; hospital readmission; implementation intervention; implementation science; improved; informatics tool; innovation; medical specialties; novel; open source; optical character recognition; patient safety; prevent; programs; rapid detection; skills; stroke patient; structured data; tool

Veterans experienced more than 3 million emergency department visits in 2021 and nearly one-third of these are in non-VA settings. Non-VA emergency care is the single largest contributor to community care with an estimated $500 million in monthly costs. Interhospital transfers are used either to repatriate Veterans during acute episodes of care or to provide access specialty care (e.g., cardiology) should such skilled services not be available at the initial hospital. However, such transfers are burdensome for Veterans and their families, and are associated with worsened clinical outcomes. The field of Human Factors Engineering uses system science to examine what may contribute to suboptimal clinical outcomes through the evaluation of “Non-Routine Events.” These are sub-optimal deviations from the standards of care or unexpected events that are identified through validated surveys of staff, clinicians, and patients. In this pilot application, we seek to advance the study of Non-Routine Events (NREs) through their application to interhospital transfers from VA and non-VA emergency departments. We will use validated surveys of NREs along with transfer documentation to study transfers for evidence of NREs. Finally, in order to automate NRE data collection, we seek to train an optical character recognition and natural language processing informatics cool, “MIRROR EHR,” to extract data of NRE components from scanned medical records for Veterans who experienced interhospital transfers. Guided by the principles of high reliability, our innovative pilot proposal directly addresses multiple ORD-wide and HSR&D priority areas including Access to Care, Quality & Safety, and Healthcare Informatics by using cross-cutting methods of Health Systems Engineering to study interhospital transfers and addressing data quality and how to integrate non-VA data. This work addresses a major legislative priority of the MISSION Act to address the quality and safety of non-VA emergency care. The Specific Aims are: 1) Examine Non-Routine Events arising from interhospital transfers of Veterans; 2) Identify NREs in transferring hospital clinical documentation amongst Veterans experiencing interhospital transfer; and 3) Demonstrate the feasibility of the MIRROR EHR informatics tool to collect and categorize data that are indicators of NREs. The team is uniquely qualified to accomplish these Aims, with expertise in systems science, human factors engineering, biomedical informatics, implementation science, qualitative methods, and acute hospital-based care (emergency and hospital medicine). The institutional environment at the VA Tennessee Valley Healthcare System and Vanderbilt University Medical Center is outstanding, including the Geriatric Research, Education and Clinical Center (GRECC), a site for VA Quality Scholars, an innovative qualitative research center; nationally ranked graduate programs in the relevant fields of study; and the national CTSA coordinating center. This application will conduct necessary pilot work to evaluate the feasibility of NRE data collection arising from interhospital transfers from both VA and non-VA settings using validated NRE surveys. This is a highly innovative proposal to advance the methods of safety science and biomedical informatics designed to improve the quality and safety for Veterans experiencing care transitions in the form of interhospital transfers. Should this work prove feasible, we plan to use these pilot data to prepare a larger Merit award application to evaluate NREs in interhospital transfers and to develop interventions to mitigate their potential harm of Veterans.

退伍军人在2021年经历了300多万次急诊，其中近三分之一 在非VA设置中。非VA紧急护理是社区护理的最大贡献者， 估计每月费用为5亿美元。医院间转移用于遣返退伍军人， 护理的急性发作或提供访问专业护理（例如，心脏病学）是否应 在最初的医院。然而，这种转移对退伍军人及其家属来说是沉重的负担， 与临床结果恶化有关。人因工程学领域使用系统科学 通过评价“非常规”，检查可能导致次优临床结局的因素 事件”这些是与护理标准的次优偏差或识别出的意外事件 通过对工作人员、临床医生和患者的有效调查。 在这个试点应用中，我们试图通过应用非常规事件（NRE）来推进其研究 从退伍军人管理局和非退伍军人管理局的急诊室到医院间的转移。我们将使用经过验证的NRE调查 沿着转移文件，以研究转移以获得NRE的证据。最后，为了使NRE自动化 数据采集，我们力求培养一个光学字符识别和自然语言处理的信息学 很酷，“镜像EHR”，从扫描的医疗记录中提取NRE组件的数据， 经历了医院间的转移。 在高可靠性原则的指导下，我们的创新试点方案直接解决了多个订单范围内的 和HSR&D优先领域，包括获得护理、质量与安全以及医疗保健信息学， 卫生系统工程的交叉方法来研究医院间的转移和寻址数据 质量以及如何整合非VA数据。这项工作涉及《使命法》的一个主要立法优先事项 解决非退伍军人事务部紧急护理的质量和安全问题。具体目的是：1）检查非常规 退伍军人医院间转移引起的事件; 2）确定医院临床转移中的NRE 在经历医院间转移的退伍军人中记录;以及3）证明 MIRROR EHR信息学工具，用于收集和分类NRE指标数据。 该团队是唯一有资格实现这些目标，在系统科学，人为因素， 工程，生物医学信息学，实施科学，定性方法，和急性医院为基础的 护理（急诊和医院医学）。弗吉尼亚州田纳西河谷医疗保健中心的机构环境 系统和范德比尔特大学医学中心是杰出的，包括老年医学研究，教育 和临床中心（GRECC），VA质量学者的网站，一个创新的定性研究中心; 在相关研究领域的国家排名研究生课程;和国家CTSA协调中心。 该应用程序将进行必要的试点工作，以评估NRE数据收集的可行性， 使用经验证的NRE调查从VA和非VA设置的医院间转移。这是一个高度 创新的建议，以推进安全科学和生物医学信息学的方法，旨在提高 以医院间转移的形式经历护理过渡的退伍军人的质量和安全。应该 这项工作证明是可行的，我们计划使用这些试点数据来准备一个更大的优异奖申请来评估 NRE在医院间转移，并制定干预措施，以减轻其潜在的伤害退伍军人。