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.

Public Health Relevance

Uncontrolled cancer pain remains a critical health issue, especially for patients and family caregivers coping with advanced, late-stage disease. Leveraging innovative mobile and wireless technology (`smart health') can help improve symptom care in the home setting, empower patients and family caregivers in the safe and effective management of cancer pain, and support the work and care management decisions of healthcare providers.

National Institute of Health (NIH)
National Institute of Nursing Research (NINR)
Research Project (R01)
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Special Emphasis Panel (ZRG1)
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Kehl, Karen
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University of Virginia
United States
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