Development and evaluation of a holistic surgical head and neck cancer post-treatment follow-up clinic using touchscreen technology-Feasibility study.
Cherith Jane SempleD LannonE QudairatE McCaughanR McCormacPublished in: European journal of cancer care (2018)
The efficacy of traditional follow-up care is being challenged, as cancer survivors' supportive and psychological needs are often neither identified, nor addressed. This study's aim was to develop a holistic surgical follow-up clinic for oral and oropharyngeal cancer patients were participants completed a disease-specific health-related quality of life tool (UWQOLv4) and item prompt list (Patient Concern Inventory) on a touchscreen computer. Information generated was used to focus the consultation on patient's identified needs and concerns. By means of a prospective non-randomised, pre-test post-test design, this follow-up clinic was evaluated using the patient enablement instrument (PEI) and patient content checklist (PCC). Feasibility was explored from the patient perspective (satisfaction survey) and clinician perspective (qualitative interview). Forty-four consecutive patients were recruited. Findings demonstrating five of the eight topics (overall QOL, emotions, head and neck symptoms, side-effects of treatment, chronic non-specific) on PCC were discussed more frequently, but changes were not statistically significant. The PEI highlighted a trend towards perceived improvement in four of the six items. Using touchscreen computers to aid communication during routine follow-up was reported as both feasible and beneficial by patients and clinicians. Providing a patient-focused follow-up consultation can facilitate the identification of unmet needs, permitting timely and appropriate intervention being initiated.
Keyphrases
- case report
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- primary care
- newly diagnosed
- randomized controlled trial
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- chronic kidney disease
- prognostic factors
- young adults
- machine learning
- patient reported outcomes
- depressive symptoms
- physical activity
- mental health
- deep learning
- chronic pain
- pain management
- double blind
- smoking cessation