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.

该提案旨在利用人工智能（AI）和自然语言处理（NLP），并进行一项