Project HoPe: Achieving Home Discharge for institutionally-bound Patients with PROMs, AI, and the EHR

从医院到专业护理机构（SNF）的不必要出院费用高昂， 患者的功能丧失和长期住院的要求。阿尔茨海默病患者 和阿尔茨海默病相关痴呆（AD/ADRD）和其他类型的认知障碍是独特的， 这种现状使他们处于不利地位，因为他们住院的可能性是其他人的两倍， 被排放到SNF，只有不到50%的人返回家园。这种情况可以按照 这是一个典型的仓促的排放规划过程的产物，没有足够的时间来发现，更不用说解决， 病人出院的障碍最近的报告表明，多达三分之一的病人被解雇， SNF，包括AD/ADRD患者，如果他们需要急性后护理（PAC）， 预期并解决了障碍。几个关键缺陷阻碍了患者的潜力的广泛实现， 直接放电回家，或他们的家庭PAC潜力（HoPe）。这包括有限的能力：1）量化 决定PAC需求的因素，2）识别和解决家庭放电的可补救障碍，以及3） 动员利益相关者推进个性化出院计划。总的来说，这些赤字防止了 及时启动急症护理服务，实现患者出院回家的可能性，PAC作为 必要以康复为重点的医院-家庭医疗保健机构（HHA）合作伙伴关系已经建立， 在住院早期制定的跨学科护理计划，患者和护理人员的参与， 病人回家的可能性。我们的团队开发了基于Epic电子健康记录（EHR）的 出院计划系统，将EHR、患者报告结果（PRO）和社会决定因素进行三角化 健康数据，以确定HoPe障碍和直接需求匹配的康复服务提供。飞行员 358名患者的家庭出院率增加了25%以上， 可接受性然而，试点项目也确定了改善认知障碍解决方案的必要性， 针对高产HoPe屏障，以及非临床利益相关者的参与。我们建议解决 通过追求三个具体目标来克服这些局限性：1）开发低负担的计算机化自适应测试PRO， 评估与安全回家出院相关的功能认知领域; 2）开发机器学习 优先考虑可操作HoPe障碍并估计家庭放电所需的变化程度的算法; 以及3）应用以用户为中心的设计原则来改进EHR出院计划系统，以实现最佳可用性 以及增强的EHR门户患者、护理人员和HHA工作人员访问。我们的目标是既整合又试点 这些可交付成果在一个成熟的和最佳使用的电子病历出院规划系统，并评估 其实施的可行性和可接受性。我们预计该系统将是可扩展的， 到机构间转移，以在多地点进行实用性试验。

Unnecessary discharges from a hospital to a skilled nursing facility (SNF) are costly and may accelerate patients’ functional losses and requirement for long-term institutionalization. Patients with Alzheimer's Disease and Alzheimer's Disease Related Dementias (AD/ADRD) and other types of cognitive impairment are uniquely disadvantaged by this status quo in that they are twice as likely to be hospitalized, four times more likely to be discharged to SNFs with less than 50% returning to their homes. This situation can be addressed as it is the product of a typically rushed discharge planning process with inadequate time to discover, much less address, a patient’s barriers to home discharge. Recent reports suggest that as many as a third of patients dismissed to SNFs, including those with AD/ADRD, could return directly home if their post-acute care (PAC) needs and barriers were anticipated and addressed. Several key deficits prevent broad realization of a patients’ potential to discharge directly home, or their Home PAC Potential (HoPe). These include a limited ability to: 1) quantify factors that determine PAC needs, 2) identify and address remediable barriers to home discharge, and 3) mobilize stakeholders for advancement of individualized discharge plans. Collectively, these deficits prevent the timely initiation of acute care services that can realize a patient’s potential for home discharge, with PAC as necessary. Rehabilitation-focused, hospital-Home Healthcare Agency (HHA) partnerships have established that interdisciplinary care plans enacted early in a hospital stay with patient and caregiver involvement increase the likelihood of a patient’s return home. Our team developed an Epic electronic health record (EHR)-based discharge planning system that triangulates EHR, patient reported outcomes (PROs), and social determinants of health data to identify HoPe barriers and direct needs-matched rehabilitation service delivery. A pilot of the system among 358 patients increased the home discharge rate by over 25% and revealed high user acceptability. However, the pilot also identified the need to improve addressing of cognitive impairments, targeting of high-yield HoPe barriers, and engagement of non-clinical stakeholders. We propose to address these limitations by pursuing three Specific Aims: 1) Develop a low-burden computerized adaptive test PRO to assess the domains of functional cognition relevant to a safe home discharge; 2) Develop a machine learning algorithm to prioritize actionable HoPe barriers and estimate the degree of change needed for home discharge; and 3) Apply user-centered design principles to refine the EHR discharge planning system for optimal usability and enhanced EHR portal patient, caregiver, and HHA staff access. Our goal is to both integrate and pilot these deliverables in a mature and optimally usable EHR discharge planning system, and to evaluate the feasibility and acceptability of its implementation. We anticipate that the system will be scalable, and amenable to inter-institution transfer for testing in a multi-site pragmatic trial.