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

Virginia LeBaron, James Hayes, Kate Gordon, Ridwan Alam, Nutta Homdee, Yudel Martinez, Emmanuel Ogunjirin, Tanya Thomas, Randy Jones, Leslie Blackhall, John Lach, Virginia LeBaron, James Hayes, Kate Gordon, Ridwan Alam, Nutta Homdee, Yudel Martinez, Emmanuel Ogunjirin, Tanya Thomas, Randy Jones, Leslie Blackhall, John Lach

Abstract

Background: An estimated 60%-90% of patients with cancer experience moderate to severe pain. Poorly managed cancer pain negatively affects the 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: This study will deploy a package of sensing technologies, known as Behavioral and Environmental Sensing and Intervention for Cancer (BESI-C), and evaluate its feasibility and acceptability among patients with cancer-family caregiver dyads. Our primary aims are to explore the ability of BESI-C to reliably measure and describe variables relevant to cancer pain in the home setting and to 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 health care providers).

Methods: This descriptive two-year pilot study will include dyads of patients with advanced cancer and their primary family caregivers recruited from an academic medical center outpatient palliative care clinic. Physiological (eg, heart rate, activity) and room-level environmental variables (ambient temperature, humidity, barometric pressure, light, and 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 mark and describe pain events and answer brief, daily ecological momentary assessment surveys. Preliminary analysis will explore the ability of the sensing modalities to infer and 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 and health care providers to seek their input regarding data display and content.

Results: Recruitment began in July 2019 and is in progress. We anticipate the preliminary results to be available by summer 2021.

Conclusions: 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.

International registered report identifier (irrid): DERR1-10.2196/16178.

Keywords: cancer; caregivers; opioids; pain; palliative care; sensors; smart health.

Conflict of interest statement

Conflicts of Interest: None declared.

©Virginia LeBaron, James Hayes, Kate Gordon, Ridwan Alam, Nutta Homdee, Yudel Martinez, Emmanuel Ogunjirin, Tanya Thomas, Randy Jones, Leslie Blackhall, John Lach. Originally published in JMIR Research Protocols (http://www.researchprotocols.org), 09.12.2019.

Figures

Figure 1
Figure 1
Overview of BESI-C study design. BESI-C: Behavioral and Environmental Sensing and Intervention for Cancer.
Figure 2
Figure 2
Health variables measured by Behavioral and Environmental Sensing and Intervention for Cancer and related sensing modalities.
Figure 3
Figure 3
The Behavioral and Environmental Sensing and Intervention for Cancer assessment model. EMA: ecological momentary assessment.
Figure 4
Figure 4
The Behavioral and Environmental Sensing and Intervention for Cancer system architecture for passive data collection: (left to right) Bluetooth Estimote beacons, patient and caregiver smart watches, base station, and sensor relay stations. EMA: ecological momentary assessment.
Figure 5
Figure 5
The Behavioral and Environmental Sensing and Intervention for Cancer system architecture for active data collection, examples of smart watch ecological momentary assessments for patient pain events (top), and caregiver pain events (bottom). See Multimedia Appendix 1 for more details.

References

    1. Lemay K, Wilson KG, Buenger U, Jarvis V, Fitzgibbon E, Bhimji K, Dobkin PL. Fear of pain in patients with advanced cancer or in patients with chronic noncancer pain. Clin J Pain. 2011 Feb;27(2):116–24. doi: 10.1097/AJP.0b013e3181f3f667.
    1. Smyth JA, Dempster M, Warwick I, Wilkinson P, McCorry NK. A Systematic Review of the Patient- and Carer-Related Factors Affecting the Experience of Pain for Advanced Cancer Patients Cared for at Home. J Pain Symptom Manage. 2018 Feb;55(2):496–507. doi: 10.1016/j.jpainsymman.2017.08.012.
    1. Martín JM, Olano-Lizarraga M, Saracíbar-Razquin M. The experience of family caregivers caring for a terminal patient at home: A research review. Int J Nurs Stud. 2016 Dec;64:1–12. doi: 10.1016/j.ijnurstu.2016.09.010.
    1. American Cancer Society. 2019. [2019-11-11]. Cancer Facts & Figures .
    1. Web statement on pain management guidance. 2019. [2019-11-11]. World Health Organization
    1. National Academies Press. 2014. [2019-11-11]. Dying in America: improving quality and honoring indivudal preferences at the end of life .
    1. National Academies Press. Washington, DC: National Academies Press (US); 2011. Relieving pain in America: a blueprint for transforming prevention, care, education and research.
    1. ASCO. 2016. [2019-11-11]. ASCO Policy Statement on Opioid Therapy: Protecting Access to Treatment for Cancer-Related Pain .
    1. American Society of Clinical Oncology The State of Cancer Care in America, 2017: A Report by the American Society of Clinical Oncology. J Oncol Pract. 2017 Apr;13(4):e353–e394. doi: 10.1200/JOP.2016.020743.
    1. National Institutes of Health. 2004. [2019-11-11]. NIH State-of-the-Science Conference Statement on Improving End-of-Life Care .
    1. Goodwin PJ, Bruera E, Stockler M. Pain in patients with cancer. J Clin Oncol. 2014 Jun 01;32(16):1637–9. doi: 10.1200/JCO.2014.55.3818.
    1. Deandrea S, Montanari M, Moja L, Apolone G. Prevalence of undertreatment in cancer pain. A review of published literature. Ann Oncol. 2008 Dec;19(12):1985–91. doi: 10.1093/annonc/mdn419.
    1. Ferrell B, Wittenberg E. A review of family caregiving intervention trials in oncology. CA Cancer J Clin. 2017 Jul 08;67(4):318–325. doi: 10.3322/caac.21396. doi: 10.3322/caac.21396.
    1. Stenberg U, Ruland CM, Miaskowski C. Review of the literature on the effects of caring for a patient with cancer. Psychooncology. 2010 Oct;19(10):1013–25. doi: 10.1002/pon.1670.
    1. Mehta A, Cohen SR, Ezer H, Carnevale FA, Ducharme F. Striving to respond to palliative care patients' pain at home: a puzzle for family caregivers. Oncol Nurs Forum. 2011 Jan;38(1):E37–45. doi: 10.1188/11.ONF.E37-E45.
    1. Dumont S, Turgeon J, Allard P, Gagnon P, Charbonneau C, Vézina L. Caring for a loved one with advanced cancer: determinants of psychological distress in family caregivers. J Palliat Med. 2006 Aug;9(4):912–21. doi: 10.1089/jpm.2006.9.912.
    1. Tagami K, Okizaki A, Miura T, Watanabe YS, Matsumoto Y, Morita T, Fujimori M, Kinoshita H. Breakthrough Cancer Pain Influences General Activities and Pain Management: A Comparison of Patients with and without Breakthrough Cancer Pain. J Palliat Med. 2018 Nov;21(11):1636–1640. doi: 10.1089/jpm.2017.0675.
    1. Mehta A, Chan LS, Cohen SR. Flying blind: sources of distress for family caregivers of palliative cancer patients managing pain at home. J Psychosoc Oncol. 2014;32(1):94–111. doi: 10.1080/07347332.2013.856057.
    1. McGuire DB, Grant M, Park J. Palliative care and end of life: the caregiver. Nurs Outlook. 2012;60(6):351–356.e20. doi: 10.1016/j.outlook.2012.08.003.
    1. National Academies of Sciences, Engineering, and Medicine . Pain Management and the Opioid Epidemic: Balancing Societal and Individual Benefits and Risks of Prescription Opioid Use. Washington, DC: The National Academies Press; 2017.
    1. CDC: Centers for Disease Control and Prevention. 2019. [2019-11-11]. Opioid overdose .
    1. Paice JA. Cancer pain management and the opioid crisis in America: How to preserve hard-earned gains in improving the quality of cancer pain management. Cancer. 2018 Jun 15;124(12):2491–2497. doi: 10.1002/cncr.31303. doi: 10.1002/cncr.31303.
    1. Badr H, Carmack CL, Kashy DA, Cristofanilli M, Revenson TA. Dyadic coping in metastatic breast cancer. Health Psychol. 2010 Mar;29(2):169–80. doi: 10.1037/a0018165.
    1. Badr H, Shen MJ. Pain catastrophizing, pain intensity, and dyadic adjustment influence patient and partner depression in metastatic breast cancer. Clin J Pain. 2014 Nov;30(11):923–33. doi: 10.1097/AJP.0000000000000058.
    1. Shaffer KM, Jacobs JM, Nipp RD, Carr A, Jackson VA, Park ER, Pirl WF, El-Jawahri A, Gallagher ER, Greer JA, Temel JS. Mental and physical health correlates among family caregivers of patients with newly-diagnosed incurable cancer: a hierarchical linear regression analysis. Support Care Cancer. 2017 Mar;25(3):965–971. doi: 10.1007/s00520-016-3488-4.
    1. Marcolino MS, Oliveira JAQ, D'Agostino M, Ribeiro AL, Alkmim MBM, Novillo-Ortiz D. The Impact of mHealth Interventions: Systematic Review of Systematic Reviews. JMIR Mhealth Uhealth. 2018 Jan 17;6(1):e23. doi: 10.2196/mhealth.8873.
    1. Slev VN, Mistiaen P, Pasman HRW, Verdonck-de Leeuw Irma M, van Uden-Kraan Cornelia F, Francke AL. Effects of eHealth for patients and informal caregivers confronted with cancer: A meta-review. Int J Med Inform. 2016 Mar;87:54–67. doi: 10.1016/j.ijmedinf.2015.12.013.
    1. National Institute of Nursing Research, National Institutes of Health. 2017. [2019-11-11]. The science of caregiving: bringing voices together summit .
    1. MacKenzie Greenle M, Morgan B, Sayani S, Meghani SH. Identifying Mobile Apps Targeting Palliative Care Patients and Family Members. J Palliat Med. 2018 Oct;21(10):1380–1385. doi: 10.1089/jpm.2018.0157.
    1. Nwosu AC, Quinn C, Samuels J, Mason S, Payne TR. Wearable smartwatch technology to monitor symptoms in advanced illness. BMJ Support Palliat Care. 2018 Jun;8(2):237. doi: 10.1136/bmjspcare-2017-001445.
    1. Theile G, Klaas V, Tröster G, Guckenberger M. mHealth Technologies for Palliative Care Patients at the Interface of In-Patient to Outpatient Care: Protocol of Feasibility Study Aiming to Early Predict Deterioration of Patient's Health Status. JMIR Res Protoc. 2017 Aug 16;6(8):e142. doi: 10.2196/resprot.7676.
    1. Darlow S, Wen K. Development testing of mobile health interventions for cancer patient self-management: A review. Health Informatics J. 2015 Apr 27; doi: 10.1177/1460458215577994.
    1. Berry DL, Hong F, Halpenny B, Partridge AH, Fann JR, Wolpin S, Lober WB, Bush NE, Parvathaneni U, Back AL, Amtmann D, Ford R. Electronic self-report assessment for cancer and self-care support: results of a multicenter randomized trial. J Clin Oncol. 2014 Jan 20;32(3):199–205. doi: 10.1200/JCO.2013.48.6662.
    1. Kessel KA, Vogel MM, Schmidt-Graf F, Combs SE. Mobile Apps in Oncology: A Survey on Health Care Professionals' Attitude Toward Telemedicine, mHealth, and Oncological Apps. J Med Internet Res. 2016 Nov 24;18(11):e312. doi: 10.2196/jmir.6399.
    1. Northouse LL, Katapodi MC, Song L, Zhang L, Mood DW. Interventions with family caregivers of cancer patients: meta-analysis of randomized trials. CA Cancer J Clin. 2010;60(5):317–39. doi: 10.3322/caac.20081. doi: 10.3322/caac.20081.
    1. Richardson JE, Reid MC. The promises and pitfalls of leveraging mobile health technology for pain care. Pain Med. 2013 Nov;14(11):1621–6. doi: 10.1111/pme.12206.
    1. Phongtankuel V, Adelman RD, Reid MC. Mobile health technology and home hospice care: promise and pitfalls. Prog Palliat Care. 2018;26(3):137–141. doi: 10.1080/09699260.2018.1467109.
    1. Alam R, Dugan J, Homdee N, Gandhi N, Ghaemmaghami B, Meda H, Bankole A, Anderson M, Gong J, Smith-Jackson T, Lach J. BESI: Reliable and heterogeneous sensing and intervention for in-home health applications. Proceedings of the Second IEEE/ACM International Conference on Connected Health: Applications, Systems and Engineering Technologies; 2017; Philadelphia, PA. 2017. pp. 147–156.
    1. Alam R, Gong J, Hanson M, Bankole A, Anderson M, Smith-Jackson T, Lach J. Motion biomarkers for early detection of dementia-related agitation. Proc of ACM Workshop on Digital Biomarkers; Jun 23, 2017; Niagara Falls, NY. 2017. pp. 15–20.
    1. Alam R, Anderson M, Bankole A, Lach J. Inferring physical agitation in dementia using smartwatch and sequential behavior models. 2018 IEEE EMBS International Conference on Biomedical & Health Informatics; Mar 4, 2018; Las Vegas, NV. 2018. pp. 170–173.
    1. McLeroy KR, Bibeau D, Steckler A, Glanz K. An ecological perspective on health promotion programs. Health Educ Q. 1988;15(4):351–77.
    1. Kayser K, Acquati C, Reese JB, Mark K, Wittmann D, Karam E. A systematic review of dyadic studies examining relationship quality in couples facing colorectal cancer together. Psychooncology. 2018 Jan;27(1):13–21. doi: 10.1002/pon.4339.
    1. NIH: National Institutes of Health. [2019-11-11]. Patient-reported outcomes measurement information system (PROMIS) .
    1. Dodd MJ, Miaskowski C, Lee KA. Occurrence of symptom clusters. J Natl Cancer Inst Monogr. 2004;(32):76–8. doi: 10.1093/jncimonographs/lgh008.
    1. Dodd MJ, Miaskowski C, Paul SM. Symptom clusters and their effect on the functional status of patients with cancer. Oncol Nurs Forum. 2001 Apr;28(3):465–70.
    1. Barsevick AM. The concept of symptom cluster. Semin Oncol Nurs. 2007 May;23(2):89–98. doi: 10.1016/j.soncn.2007.01.009.
    1. Sagha Zadeh R, Eshelman P, Setla J, Kennedy L, Hon E, Basara A. Environmental Design for End-of-Life Care: An Integrative Review on Improving the Quality of Life and Managing Symptoms for Patients in Institutional Settings. J Pain Symptom Manage. 2018 Mar;55(3):1018–1034. doi: 10.1016/j.jpainsymman.2017.09.011.
    1. Addington-Hall J. Research sensitivities to palliative care patients. Eur J Cancer Care (Engl) 2002 Sep;11(3):220–4.
    1. Bove La. Increasing Patient Engagement Through the Use of Wearable Technology. The Journal for Nurse Practitioners. 2019 Sep;15(8):535–539. doi: 10.1016/j.nurpra.2019.03.018.
    1. Shiffman S, Stone AA, Hufford MR. Ecological momentary assessment. Annu Rev Clin Psychol. 2008;4:1–32.
    1. Friedman C, Rubin J, Brown J, Buntin M, Corn M, Etheredge L, Gunter C, Musen M, Platt R, Stead W, Sullivan K, Van HD. Toward a science of learning systems: a research agenda for the high-functioning Learning Health System. J Am Med Inform Assoc. 2015 Jan;22(1):43–50. doi: 10.1136/amiajnl-2014-002977.
    1. Sledge GW, Hudis CA, Swain SM, Yu PM, Mann JT, Hauser RS, Lichter AS. ASCO's approach to a learning health care system in oncology. J Oncol Pract. 2013 May;9(3):145–8. doi: 10.1200/JOP.2013.000957.
    1. Smith M, Saunders R, Stuckhardt L, McGinnis J. Institute of Medicine. Washington, DC: The National Academies Press; 2013. Best Care at Lower Cost: The Path to Continuously Learning Health Care in Americahealth care in America.
    1. Lötsch J, Ultsch A. Machine learning in pain research. Pain. 2018 Apr;159(4):623–630. doi: 10.1097/j.pain.0000000000001118.
    1. Nwosu AC, Collins B, Mason S. Big Data analysis to improve care for people living with serious illness: The potential to use new emerging technology in palliative care. Palliat Med. 2018 Jan;32(1):164–166. doi: 10.1177/0269216317726250.
    1. Krippendorff K. Content Analysis: An introduction to its methodology. 4th edition. Los Angeles: Sage Publications; 2018.
    1. National Consensus Project for Quality Palliative Care. 2018. [2019-11-11]. Clinical practice guidelines for quality palliative care, 4th Edition
    1. Sun Yunheng, Jiang Feng, Gu Juan J, Wang Y Ken, Hua Hongwei, Li Jing, Cheng Zhijun, Liao Zhijun, Huang Qian, Hu Weiwei, Ding Gang. Development and Testing of an Intelligent Pain Management System (IPMS) on Mobile Phones Through a Randomized Trial Among Chinese Cancer Patients: A New Approach in Cancer Pain Management. JMIR Mhealth Uhealth. 2017 Jul 25;5(7):e108. doi: 10.2196/mhealth.7178.
    1. Bender JL, Yue RYK, To MJ, Deacken L, Jadad AR. A lot of action, but not in the right direction: systematic review and content analysis of smartphone applications for the prevention, detection, and management of cancer. J Med Internet Res. 2013;15(12):e287. doi: 10.2196/jmir.2661.
    1. Lalloo C, Jibb LA, Rivera J, Agarwal A, Stinson JN. "There's a Pain App for That": Review of Patient-targeted Smartphone Applications for Pain Management. Clin J Pain. 2015 Jun;31(6):557–63. doi: 10.1097/AJP.0000000000000171.
    1. Chi N, Demiris G, Pike KC, Washington K, Oliver DP. Pain Management Concerns From the Hospice Family Caregivers' Perspective. Am J Hosp Palliat Care. 2018 Apr;35(4):601–611. doi: 10.1177/1049909117729477.

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