Improving Post-Acute Care Value for Veterans

提高退伍军人的急性后护理价值

• 批准号: 10187950
• 负责人: Robert Edward Burke
• 金额: --
• 依托单位: PHILADELPHIA VA MEDICAL CENTER
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-10-01 至 2025-09-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10187950
• 关键词: Acute; Affect; Age; Algorithms; Area; Big Data; Caring; Characteristics; Communities; Contracts; Data; Data Set; Data Sources; Development; Emergency department visit; Engineering; Enrollment; Fee-for-Service Plans; Fees; Geriatrics; Health care facility; Healthcare; Home; Hospitalization; Hospitals; Individual; Information Systems; Leadership; Life; Long-Term Care; Machine Learning; Medicaid; Medical; Medicare; Medicare/Medicaid; Methodology; Methods; Modeling; Nursing Homes; Nursing Staff; Outcome; Patients; Policies; Population; Positioning Attribute; Process; Provider; Proxy; Publishing; Quality of Care; Queuing Theory; Recording of previous events; Rehabilitation therapy; Risk; Risk Adjustment; Role; Shapes; Site; Skilled Nursing Facilities; System; Techniques; Time; Variant; Veterans; Work; acute care; adverse event risk; adverse outcome; authority; care costs; care episode; care providers; community living; cost; health economics; hospital readmission; human old age (65+); improved; improved outcome; innovation; insight; machine learning method; military veteran; mortality; novel; operation; point of care; success; tool

Background: The transition to a skilled nursing facility (SNF) after an acute hospitalization is one of the most perilous times in the life of an older Veteran. Veterans undergo more than 250,000 transitions between hospitals and SNFs annually, but more than 1 in 4 is readmitted to the hospital from SNF and less than half have returned to the community by 100 days following hospital discharge. Although the intent of SNF care is to allow recuperation and rehabilitation, Veterans who do not successfully recover are commonly placed in institutional long-term care at significant cost to themselves and to the VA, which spends more than $7 billion annually on this care. However, SNFs vary widely in their rates of community discharge and costs of care delivered. It is unclear how to identify “high-value” SNFs (those that deliver the best community discharge rates at lowest cost) for Veterans since existing public quality metrics do not include VA SNFs, do not list Veteran- specific outcomes, and do not include costs. Similarly, it is unclear how much matching individual Veteran needs with particular SNF characteristics might improve value. The VA as both payer and provider of SNF care has the unique opportunity to develop an optimal SNF network to drive high-value care. Significance/Impact: This work aligns with VA priorities to develop an integrated, high-performing network for Veterans as part of the MISSION Act and positions the VA as a leader in delivery of post-acute care. There are more than 4 million Veterans currently over age 65, making it imperative to improve outcomes and lower costs in SNFs as more Veterans transition out of the hospital to this care setting. Innovation: The approach uses novel data sets and methods drawn from health economics, big data, and systems engineering to provide new insights. To our knowledge, there are no published studies describing the outcomes of Veterans in post-acute care, identifying characteristics of high-performing facilities, nor establishing how matching patient to post-acute care provider characteristics affects outcomes. Specific Aims: Our Specific Aims are to: 1) Compare outcomes (successful discharge to the community) and costs (Federal dollars) across the population of Veterans discharged from a VA hospital to the three most common post-acute care settings where Veterans receive SNF care: CLCs, CNHs, and non-VA SNFs. 2) Evaluate the effect of matching individual subpopulations of Veterans (e.g., by risk for adverse outcome) to SNF type (CLCs, CNHs, or non-VA SNFs) and SNF star rating on outcomes and costs. 3) Compare the effects of consolidating SNF referrals to the SNF type with best outcomes and lowest costs (Aim 1) or matching individual Veteran characteristics to different SNFs (Aim 2) on Veteran outcomes, overall costs of care, and SNF capacity. Methodology: This proposal uses advanced statistical techniques (such as instrumental variable and machine learning methods) and a unique dataset (the 2014-18 Residential History File, which concatenates VA, fee- basis, Medicare, and Medicaid data into longitudinal episodes of care for individual Veterans) to accomplish our Aims. Implementation/Next Steps: The results of this work will be disseminated to VA Geriatrics and Extended Care and Office of Community Care leadership, who have been involved in the development of the proposal, as well as VISN and VA facility leadership through two tools that can be used 1) at the bedside to optimize SNF choice and 2) at a leadership level to help shape the SNF network to maximize value.

背景：急性住院后向熟练护士设施（SNF）的过渡是最多的 老年退伍军人生活中的危险时代。退伍军人之间经历了超过25万 每年医院和SNF，但四分之一以上的人从SNF恢复到医院，不到一半 出院后100天，已经返回社区。虽然SNF护理的意图是 为了允许恢复和康复，通常没有成功康复的退伍军人 机构的长期护理对自己和弗吉尼亚州的支出超过70亿美元 每天在这个护理上。但是，SNF的社区出院率和护理成本差异很大 发表。目前尚不清楚如何识别“高价值” SNF（那些提供最佳社区出院率的SNF 以最低的价格）对于退伍军人而言，由于现有的公共质量指标不包括VA SNF，因此不列出资深人士 - 具体的结果，不包括费用。同样，还不清楚多少匹配个人资深人士 具有特定SNF特征的需求可能会提高价值。 VA作为SNF的付款人和提供商 CARE有独特的机会开发最佳的SNF网络来推动高价值护理。 意义/影响：这项工作与VA优先级相吻合，以开发一个集成，表现高的网络 退伍军人作为《任务法》的一部分，并将VA定位为急性后护理的领导者。那里 目前超过65岁以上的退伍军人超过400万，因此必须改善结果并降低 SNF的费用是从医院过渡到此护理环境的越来越多的退伍军人。 创新：该方法使用健康经济学，大数据和 系统工程以提供新的见解。据我们所知，没有任何已发表的研究描述 退伍军人在急性后护理中的成果，确定高性能设施的特征，也不 确定匹配患者与急性护理后提供者的特征如何影响结果。 具体目的：我们的具体目的是： 1）比较结果（成功解除社区）和成本（联邦美元） 从VA医院出院到三个最常见的急性后护理的退伍军人人口 退伍军人获得SNF护理的设置：CLC，CNHS和非VA SNF。 2）评估匹配退伍军人的单个亚群的效果（例如，通过广告风险 结果）to SNF类型（CLC，CNHS或非VA SNF）和SNF星级评级。 3）将合并SNF转介到SNF类型的效果与最佳结果和最低的效果 成本（AIM 1）或将个人的退伍军人特征与退伍军人的不同SNF相匹配（AIM 2） 结果，总体护理成本和SNF容量。 方法论：该建议使用高级统计技术（例如仪器变量和机器 学习方法）和一个独特的数据集（2014-18的住宅历史文件，它会加入VA，费用 - 基础，Medicare和Medicaid数据中的个人退伍军人的纵向纵向发作） 我们的目标。 实施/下一步：这项工作的结果将被传播到VA老年医学家并扩展 参与该提案的发展的社区护理领导层的护理和办公室， 以及VISN和VA设施通过两种可以使用的工具1）在床边进行优化 SNF选择和2）在领导层面上有助于塑造SNF网络以最大程度地提高价值。