Telemedicine Nurse-Led Intervention for Rural Cancer Survivors

Plain-language summary

This study will evaluate the impact, cost-effectiveness, and patient perspectives of Comprehensive Assistance: Rural Intervention, Nursing, and Guidance (CARING), a nurse-led supportive care protocol delivered using telemedicine videoconferencing aimed at reducing unmet needs in a rural head and neck cancer population. Specific aims: 1) Test the efficacy of CARING, delivered with and without telemedicine, compared to a control group. 2) Conduct a cost-effectiveness analysis of a nurse-led telemedicine visit. 3) Evaluate patient perceptions of a telemedicine intervention. Design: We will use a three-arm randomized control design to determine the efficacy of CARING delivered face-to-face, vs. CARING over telemedicine, vs. usual care. Costs will be determine for incremental cost effectiveness analysis, with quality of life years as the effectiveness variable. Patient perceptions will be evaluated qualitatively using the Practical, Robust Implementation and Sustainability Model (PRISM), designed to evaluate translation of research into practice and quantitatively using the Telemedicine Satisfaction and Usefulness Questionnaire (TSUQ). Sample: We will enroll 450 head and neck cancer survivors of any stage who have completed treatment within the last 6 weeks (address over sampling of rural). Procedures: Following randomization, those in the intervention arm will either receive the nurse-led intervention in a clinic setting or over telemedicine videoconferencing 6 weeks following their in-person, end of treatment medical visit. Assessments at baseline, 6 weeks following the intervention, and 6 months following the intervention will document unmet needs using the Short Form Survivorship Unmet Needs (SF-SUNS) and quality of life using the Functional Assessment of Cancer Therapies- Head and Neck (FACT-HN) and the TSUQ and PRISM-guided questionnaires immediately following intervention. Health utilization costs at the societal and health system levels will be collected from the electronic medical record and patient interviews.

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