REmote symptom COllection to improVE postopeRative care (RECOVER)

远程症状收集以改善术后护理（恢复）

• 批准号: 10637739
• 负责人: Waddah B. AL-RAFAIE
• 金额: $ 65.78万
• 依托单位: MEDSTAR HEALTH RESEARCH INSTITUTE
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-07-15 至 2027-12-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10637739
• 关键词: Address; Adverse event; Artificial Intelligence; Attention; Black race; Cancer Patient; Caring; Cessation of life; Cholangiocarcinoma; Clinical; Clinical Trials; Collection; Colorectal Cancer; Communication; Devices; Disparity; Disparity population; Effectiveness; Emergency department visit; Event; Friends; Gastrointestinal Surgical Procedures; Goals; Health; Health Services Research; Health system; Healthcare Systems; Hispanic; Home; Hospitals; Informatics; Inpatients; Intervention; Intuition; Malignant neoplasm of gastrointestinal tract; Malignant neoplasm of liver; Malignant neoplasm of pancreas; Marketing; Medical; Mid-Atlantic Region; Minority; Modeling; Monitor; Natural Language Processing; Operative Surgical Procedures; Outcome; Patients; Phase; Postoperative Care; Postoperative Period; Predictive Factor; Provider; Reporting; Research; Sampling; Social Problems; Strategic Planning; Structural Racism; Symptoms; System; Technology; United States National Institutes of Health; Voice; cancer care; cancer surgery; coronavirus disease; cost; disparity reduction; effectiveness evaluation; efficacy evaluation; ethnic health disparity; ethnoracial; ethnoracial disparity; ethnoracial minority; experience; flexibility; follow-up; gastroesophageal cancer; gastrointestinal symptom; health care disparity; health information technology; hospital readmission; improved; innovation; innovative technologies; low health literacy; minority patient; mobile application; multidisciplinary; patient oriented; patient-clinician communication; pilot test; provider adherence; racial disparity; randomized, clinical trials; response; safety net; smart speaker; social; success; surgery outcome; telephone based; tool

This proposal aims to leverage artificial intelligence (AI) and natural language processing (NLP) and conduct a randomized clinical trial to examine how a voice-assisted remote patient symptom monitoring system (VARSMS) can be useful in reducing ethnoracial disparities after gastrointestinal (GI) cancer surgery. There are significant disparities among ethnoracial minorities along the continuum of GI surgical cancer care. Even after controlling for key factors, Black and Hispanic patients are twice as likely as White patients to experience operative deaths and complications after GI cancer surgery in part due to poor communication, low health literacy, understanding or follow-up across a range of factors. Research indicates that disparities in outcomes for minority surgical patients may be driven by events during the vulnerable phase of surgical transitions when patients are recovering at home under difficult social and medical conditions. Lack of early recognition or management of postoperative symptoms can lead to complications and readmissions. Remote patient symptom monitoring may be a powerful tool to reduce disparities in post-discharge complications by facilitating patient-friendly connections to the care team. Our pilot test, built on Amazon Alexa and Echo devices, has shown successful usage of this innovative technology among a sample of mostly ethnoracial minority patients (70%) to which it was targeted. But large-scale evidence is lacking. To address this timely gap, we propose to conduct a randomized clinical trial to examine how a voice-assisted remote patient symptom monitoring system can reduce disparities in GI cancer surgery outcomes within one of the largest and ethnoracially rich (50% Black) healthcare systems in the Mid-Atlantic region. Our overarching goal is to increase patient-clinician communication in reporting post-discharge symptoms using an innovative voice-assisted system to better inform early clinical intervention decisions and thereby reduce readmissions, complications, and emergency room (ER) visits. Building on the success of a pilot clinical trial that leveraged voice-assisted remote patient symptom monitoring and the care transition conceptual framework, our collaborative multidisciplinary team to: Aim 1: To conduct a randomized clinical trial to evaluate the effectiveness of a VARSMS at reducing the number of adverse events assessed by a composite outcome including in-patient readmissions and ER visits among GI cancer surgery patients for 40 days post-discharge. Aim 2: To evaluate the efficacy of VARSMS in improving patient-clinician communication and adherence during post-discharge care transition after GI cancer surgery for minority patients compared to White patients. Aim 3: To evaluate provider’s experience with the VARSMS system during post-discharge care transition after GI cancer surgery, with special attention to non-White patients.

该建议旨在利用人工智能（AI）和自然语言处理（NLP）并进行 随机临床试验检查语音辅助远程患者症状监测系统如何 （VARSMS）可用于减少胃肠道（GI）癌症手术后的民族差异。那里 沿GI手术癌症护理的连续体中的民族少数群体之间存在显着差异。甚至 在控制关键因素之后，黑人和西班牙裔患者的经历的可能性是白人患者的两倍 胃肠道癌症手术后手术死亡和并发症部分是由于沟通不良，健康状况不佳 识字，理解或随访跨多种因素。研究表明结果差异 对于少数族裔手术患者，可能是在手术转变脆弱阶段驱动的 患者在困难的社会和医疗状况下在家中康复。缺乏早期认可或 术后症状的治疗可能导致并发症和再入院。 远程患者症状监测可能是减少分发后分布的强大工具 通过支持患者友好的联系与护理团队的并发症。我们的试点测试，建立在Amazon Alexa上 ECHO设备，已成功地在大多数样本中使用了这种创新技术 将其作为目标的民族少数民族患者（70％）。但是缺乏大规模证据。 为了解决这个及时的差距，我们建议进行一项随机临床试验，以检查语音辅助 远程患者症状监测系统可以减少胃肠道癌手术结果中的分布 大西洋中部地区最大，最大的富裕（50％黑色）医疗系统。我们的总体 目的是通过创新在报告后出院症状进行报告时增加患者 - 阵容的沟通 语音辅助系统，以更好地告知早期临床干预决策，从而减少再入院， 并发症和急诊室（ER）就诊。建立在利用试验临床试验的成功的基础上 语音辅助远程患者症状监测和护理过渡概念框架，我们 协作多学科团队： 目标1：进行随机临床试验以评估VARSM在降低的有效性 通过复合结果评估的不良事件的数量，包括住院再入院 胃肠道癌手术患者的急诊室检查后40天。 目的2：评估VARSM在改善患者 - 雨林沟通和的效率 GI癌症手术后，少数族裔患者的遵守后出院后护理过渡期间的依从性 与白人患者相比。 AIM 3：评估提供商在放电后护理期间提供的VARSMS系统的经验 胃肠道癌手术后的过渡，并特别注意非白人患者。