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.

2021 年，退伍军人接受了超过 300 万次急诊就诊，其中近三分之一 处于非 VA 设置。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。院间转运用于遣返退伍军人 急性发作的护理或提供专业护理（例如心脏病学），如果这种熟练的服务不 可在最初的医院获得。然而，这种转移对退伍军人及其家人来说是负担，并且 与临床结果恶化有关。人因工程领域运用系统科学 通过评估“非常规治疗”来检查可能导致次优临床结果的因素 活动”。这些是与护理标准的次优偏差或已识别的意外事件 通过对工作人员、临床医生和患者进行有效的调查。 在此试点应用中，我们寻求通过应用程序推进非常规事件 (NRE) 的研究 从 VA 和非 VA 急诊科进行院间转诊。我们将使用经过验证的 NRE 调查 连同转移文件一起研究转移以获取 NRE 的证据。最后，为了自动化NRE 数据收集，我们寻求训练光学字符识别和自然语言处理信息学 很酷的“MIRROR EHR”，从扫描的医疗记录中提取 NRE 组件的数据，供退伍军人使用 具有丰富的院际转运经验。 在高可靠性原则的指导下，我们的创新试点提案直接解决了 ORD 范围内的多个问题 HSR&D 优先领域包括获得护理、质量和安全以及医疗信息学 研究医院间转移和处理数据的卫生系统工程的跨领域方法 质量以及如何整合非 VA 数据。这项工作涉及《使命法》的主要立法优先事项 解决非 VA 紧急护理的质量和安全问题。具体目标是： 1) 检查非常规 退伍军人院际转移引起的事件； 2）识别转移医院临床中的NRE 经历院间转移的退伍军人之间的记录； 3) 证明该方案的可行性 MIRROR EHR 信息学工具，用于收集和分类作为 NRE 指标的数据。 该团队具有独特的资格来实现这些目标，拥有系统科学、人为因素方面的专业知识 工程学、生物医学信息学、实施科学、定性方法和急性医院基础 护理（急诊和医院医学）。 VA 田纳西河谷医疗保健机构的机构环境 系统和范德比尔特大学医学中心非常出色，包括老年研究、教育 临床中心 (GRECC)，VA 质量学者网站，一个创新的定性研究中心； 相关研究领域的全国排名研究生课程；以及国家 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 使用经过验证的 NRE 调查从 VA 和非 VA 环境中进行院间转诊。这是一个高度 推进安全科学和生物医学信息学方法的创新提案，旨在提高 以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 这项工作被证明是可行的，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 医院间转移中的 NRE 并制定干预措施以减轻其对退伍军人的潜在伤害。