Leveraging Smart Health Technology to Empower Patients and Family Caregivers in Managing Cancer Pain: Protocol for a Feasibility Study

Abstract

Journal of Medical Internet Research - International Scientific Journal for Medical Research, Information and Communication on the Internet #Preprint #PeerReviewMe: Warning: This is a unreviewed preprint. Readers are warned that the document has not been peer-reviewed by expert/patient reviewers or an academic editor, may contain misleading claims, and is likely to undergo changes before final publication, if accepted, or may have been rejected/withdrawn. Readers with interest and expertise are encouraged to sign up as peer-reviewer, if the paper is within an open peer-review period. Please cite this preprint only for review purposes or for grant applications and CVs (if you are the author). Background: An estimated 60-90% of patients with cancer experience moderate to severe pain. Poorly managed cancer pain negatively affects quality of life for both patients and their family caregivers and can be a particularly challenging symptom to manage at home. Mobile and wireless technology (‘Smart Health’) has significant potential to support patients with cancer and their family caregivers and empower them to safely and effectively manage cancer pain. Objective: To deploy a package of sensing technologies, known as Behavioral and Environmental Sensing and Intervention for Cancer (BESI-C), and evaluate feasibility and acceptability with cancer patient—family caregiver dyads. Our primary aims are to explore the ability of BESI-C to: 1) reliably measure and describe variables relevant to cancer pain in the home setting; and 2) better understand the dyadic effect of pain between patients and family caregivers. A secondary objective is to explore how to best share collected data among key stakeholders (patients, caregivers, and healthcare providers). Methods: Design: Descriptive 2-year pilot study. Sample: Dyads of patients with advanced cancer and their primary family caregiver recruited from an academic medical center outpatient palliative care clinic. Data Collection: Physiological (e.g., heartrate) and room-level environmental variables (ambient temperature; humidity; barometric pressure; light; noise) will be continuously monitored and collected. Behavioral and experiential variables will be actively collected when the caregiver or patient interacts with the custom BESI-C ‘app’ on their respective Smart Watch to: 1) mark a pain episode and describe the event, and 2) answer brief, daily ecological momentary assessment surveys. Data Analysis: Preliminary analysis will explore the ability of the sensing modalities to infer and/or detect pain events. Feasibility will be assessed by logistic barriers related to in-home deployment; technical failures related to data capture and fidelity; Smart Watch wearability issues; and patient recruitment and attrition rates. Acceptability will be measured by dyad perceptions and receptivity to BESI-C through a brief, structured interview and surveys conducted at deployment completion. We will also review summaries of dyad data with participants to seek their input regarding data display and content. Results: Recruitment began April 2019 and is in progress. We anticipate preliminary results available by Spring 2020. Conclusion: BESI-C has significant potential to monitor and predict pain while concurrently enhancing communication, self-efficacy, safety, and quality of life for patients and family caregivers coping with serious illness, such as cancer. This exploratory research offers a novel approach to deliver personalized symptom management strategies, improve patient and caregiver outcomes, and reduce disparities in access to pain management and palliative care services.