Characterizing the Complexity of Advanced Cancer Pain in the Home Context by Leveraging Smart Health Technology

利用智能健康技术表征家庭中晚期癌症疼痛的复杂性

• 批准号: 10518410
• 负责人: Virginia Townsend LeBaron
• 金额: $ 68.56万
• 依托单位: UNIVERSITY OF VIRGINIA
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-02-01 至 2025-11-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10518410
• 关键词: Accident and Emergency department; Acute Pain; Address; Adherence; Advanced Malignant Neoplasm; Affect; Behavioral; Breakthrough Pain; Cancer Intervention; Cancer Pain Management; Cancer Patient; Caregivers; Caring; Clinic; Communication; Complex; Custom; Data; Disease; Disease Progression; Distress; Effectiveness; Emotional; Environmental Risk Factor; Event; Family Caregiver; Fingerprint; Frequencies; Health; Health Personnel; Health Technology; Health system; Healthcare Systems; Home; Hospice Programs; Individual; Interdisciplinary Study; Intervention; Life; Malignant Neoplasms; Managed Care; Monitor; Moods; Observational Study; Oncology; Opioid; Outpatients; Pain; Palliative Care; Patient Care; Patient Self-Report; Patients; Persons; Pharmaceutical Preparations; Phenotype; Physiological; Play; Psychological Impact; Quality of life; Reporting; Research; Role; SMART health; Signs and Symptoms; Sleep; Source; Symptoms; System; Technology; Time; Wireless Technology; Work; advanced disease; cancer complication; cancer pain; contextual factors; coping; data integration; data sharing; data visualization; design; digital; empowerment; end of life; evidence base; experience; improved; innovation; minimally invasive; mobile computing; negative affect; novel; opioid epidemic; personalized management; personalized strategies; pharmacologic; prediction algorithm; preference; recruit; sensor; smart watch; social; symptom management; symptomatic improvement; treatment effect; wearable sensor technology

Project Summary Cancer pain is complex, prevalent and has serious consequences for patients, family caregivers and healthcare systems. Inadequately managed cancer pain can be particularly problematic for patients coping with advanced, metastatic disease. Most symptom management occurs in the home setting, and family caregivers often play a key role in helping to manage cancer pain, but often find this task daunting and stressful. Complicating cancer pain management is the reality that opioids, a main-stay class of medications used to control serious cancer pain, are subject to increased scrutiny given well-publicized concerns about the national `opioid epidemic.' Now more than ever, it is imperative we understand how patients and family caregivers attempt to manage cancer pain at home so we can offer them personalized support to effectively and safely alleviate pain. Mobile and wireless technology (`smart health') can help support symptom management in the home setting, but must be carefully designed to account for the realities of patients and family caregivers coping with advanced disease. We hypothesize that individuals, and patient-family caregiver dyads, will display a unique `digital fingerprint' (or phenotype) of the advanced cancer pain experience – that if better understood can be utilized to inform and deliver personalized, timely interventions. The purpose of this study, which builds upon preliminary pilot work, is to deploy an unobtrusive smart health system, the Behavioral and Environmental Sensing and Intervention for Cancer (BESI-C), to monitor and describe – and ultimately to predict and help manage – the experience of advanced cancer pain in the home setting. BESI-C is comprised of wearable (smart watch) and environmental sensors that collect physiological, behavioral, and contextual data at the individual, dyad and home level that can be integrated to provide a comprehensive picture of a health related phenomenon. A unique feature of the BESI-C system is the ability of patients and caregivers to record and characterize cancer pain events from their own perspective using a custom application on their respective smart watch. Specifically, this observational research will analyze data collected via BESI-C from patient-family caregiver dyads recruited from an outpatient oncology palliative care clinic and a home hospice program, to develop comprehensive `digital phenotypes' of advanced cancer pain in the home setting. These digital phenotypes will characterize the frequency, intensity and impact on quality of life of pain events; monitor the use of pharmacological and non-pharmacological strategies and self-reported effectiveness; correlate environmental, contextual, behavioral and physiological sensor data with reported pain events; and evaluate concordance of patient and caregiver data. This research will also explore preferences for communicating collected data with patients, family caregivers and healthcare providers by creating and sharing data visualizations. Additionally, we will explore which sensing data are most predictive of breakthrough pain events to build parsimonious pain prediction algorithms.

项目摘要 癌症疼痛很复杂，普遍，对患者，家庭护理人员和 医疗保健系统不足以治疗癌症疼痛 患有晚期转移性疾病。 护理人员通常在帮助管理癌症疼痛方面发挥关键作用 癌症疼痛管理复杂性是阿片类药物的现实 用于控制严重的癌症疼痛，受到对审查的审查，鉴于对 国家流行病，现在比以往任何时候都更加了解 护理人员试图在家管理癌症疼痛，以便我们可以为他们提供个性化的支持以有效 安全减轻疼痛。 在家庭环境中的管理，但必须经过精心设计以说明患者的现实 家庭护理应对晚期疾病。 二元组将显示出晚期癌症疼痛体验的独特的“数字指纹”（或表型） - 如果 更好地理解可以用来告知和提供个性化的及时干预。 基于初步试验工作的研究是部署一种不引人注目的智能卫生系统，即 癌症的行为和环境传感和IND介入（BESI-C） 最终，预测和帮助管理家庭环境中晚期癌症疼痛的经验。 由可穿戴（智能手表）和环境传感器组成，这些传感器收集生理，行为和 可以集成的个人，二元组和家庭级别的上下文数据 与健康有关的现象的图片。 护理人员使用自定义从角度记录和表征癌症疼痛事件 在各自的智能手表上应用。 从门诊肿瘤学palliative Care诊所招募的患者家庭护理人员二元组的通过BESI-C的通过 一项家庭临终关怀计划，以开发家庭中晚期癌症疼痛的全面“数字表型” 设置这些数字表型将表征痛苦质量的频率，强度和影响 事件； 有效性； 事件和评估患者和护理人员的一致性。 用于与患者，家庭护理人员和提供和创建的医疗保健传达收集数据 共享数据可视化。 突破性的疼痛事件，以建立简约的疼痛预测算法。