课题基金 / 基金详情

Patient-Driven Medication Safety Learning Laboratory in Care Transitions

Patient-Driven Medication Safety Learning Laboratory in Care Transitions
护理转变中患者驱动的药物安全学习实验室
批准号:
10769211
负责人:
Heui-Yen Chen
金额:
$50.0万
依托单位国家:
美国
项目类别:
财政年份:
2023
资助国家:
美国
项目状态:
未结题
起止时间:
2023-09-01 至 2027-06-30

项目摘要

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中文摘要
翻译
项目总结/摘要 药物伤害是世界各地医疗保健系统中造成伤害和可避免伤害的主要原因。这 对于老年人来说尤其如此,他们有更高的药物伤害风险,特别是在过渡期, 治疗(TOC),因为他们经常服用多种药物,并在治疗过程中对药物进行了多次改变。 住院老年患者和护理人员在实现安全方面存在重大差距和障碍 在护理过渡期间和之后使用药物。这个拟议的学习实验室将使患者和 护理人员与医疗保健系统团队合作,从分析现有药物开始 安全工作体系,跨越整个护理过渡期。这将导致设计,开发, 在模拟环境中测试可扩展的以人为本的干预措施,并从实践中获得输入 临床医生和患者作为最终用户,然后在临床环境中进行试点测试。完成 为此,研究小组将遵循五个阶段的系统工程方法,以实现以下目标 目标:目标1:问题分析-这一目标使用多方面的方法来识别和理解 医疗过渡期间用药问题的原因和后果,包括 病人和护理人员,以及塑造和限制护理过渡工作的操作复杂性。的 研究小组将:目标1(a)研究患者和护理人员最近住院的经历,重点是 药物变化、相关症状和健康相关挑战的社会决定因素;目标1(B) 进行认知工程分析,以确定认知工作挑战及其相关信息 医院和初级保健场所的护理过渡工作所涉及的需求;以及目标1(c)利用保健 信息交换(HIE)数据,以识别患者和系统级风险因素并开发风险算法 意外住院和药物伤害目标2:(a)设计、开发,(B)实施, 和评价。目标2(a)反复设计和开发患者驱动的干预措施, 关键利益相关者(例如,项目社区咨询委员会成员);目标2(B)实施 并评估有希望的解决方案-首先在模拟环境中(具有现实任务),然后在 临床设置。本提案的总体目标是开发一个跨系统的学习实验室, 以创新的方式将老年人、护理人员、研究人员和医疗团队聚集在一起, 药害。我们的方法将重点放在患者和护理人员身上,同时关注社会 健康的决定因素,并让他们广泛参与系统工程过程的每一步。的 从该提案中学习实验室基础设施和试点数据将为持续的 利益相关者伙伴关系,将产生未来资助的研究,以提高老年人的用药安全。
英文摘要
Project Summary/Abstract Medication harm is a leading cause of injury and avoidable harm in health care systems across the world. This is especially true for older adults, who are at higher risk for medication harm, especially around transitions of care (TOC), as they often take multiple medicines and have several changes made to their medicines during inpatient admission. There are major gaps and barriers for older adult patients and caregivers to achieve safe medication use during and after care transitions. This proposed Learning Lab will empower patients and caregivers in partnership with the healthcare system team, starting with analyzing the existing medication safety work system, spanning the entire transition of care. This will lead to the design, development, and testing of scalable human-centered interventions in a simulated environment with input from practicing clinicians and patients as the end-users, followed by pilot testing in the clinical environment. To accomplish this, the research team will follow the five-phase, systems-engineering methodology to achieve the following aims: Aim 1: Problem Analysis – This aim uses a multifaceted approach to identify and understand the causes and consequences of medication problems in transitions of care, including the needs and priorities of patients and caregivers, and the operational complexities that shape and constrain care transition work. The team will: Aim 1(a) study patients’ and caregivers’ experiences with recent hospitalizations, focusing on medication changes, associated symptoms, and Social Determinants of Health-related challenges; Aim 1(b) perform cognitive engineering analysis to identify cognitive work challenges and their associated information needs involved in the care transition work at hospital and primary care sites; and Aim 1(c) use health information exchange (HIE) data to identify patient- and system-level risk factors and develop risk algorithms for unplanned hospitalizations and medication harm. Aim 2: (a) Design, Development, (b) Implementation, and Evaluation. The team will: Aim 2(a) iteratively design and develop patient-driven interventions with inputs from key stakeholders (e.g., members of the project’s Community Advisory Board); and Aim 2(b) implement and evaluate promising solutions—first in a simulated environment (with realistic tasks) and subsequently in a clinical setting. The overall goal of this proposal is to develop a cross-system learning laboratory that brings together older adults, caregivers, researchers, and healthcare teams in innovative ways to protect them from medication harm. Our approach puts the focus on patients and caregivers, with attention to the Social Determinants of Health, and engages them extensively in every step of the systems engineering process. The learning laboratory infrastructure and pilot data from this proposal will create a strong foundation for sustained stakeholder partnership that will spawn future funded studies to improve medication safety for older adults.
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Data-driven Recommendation System Construction of an Online Medical Platform Based on the Fusion of Information