Ein Modell für Pretreatment Assessment und Prähabilitation bei Kopf-Hals-Tumoren
摘要
The treatment of patients with head and neck tumors, particularly in the context of radio(chemo)therapy, R(C)T, often leads to impairments in swallowing function, nutritional status, and quality of life. At the University Hospital Zurich (USZ), a logopedic and phoniatric outpatient clinic was introduced for pretherapeutic assessment and treatment to potentially prevent or reduce the (late) effects of cancer treatment. Although the model was not initially designed for adaptation by other institutions, it could serve as an example for similar concepts in other clinics.
ObjectiveThis article presents an outpatient clinic model that provides structured logopedic care before and after R(C)T or surgery. The focus is on practical aspects, including resource planning, patient numbers, and challenges to implementation.
MethodsThe model was developed based on a literature review and practical experience. It defines timepoints for initial assessments, follow-up examinations, and therapeutic interventions. Since 2019, it has been part of the interdisciplinary head and neck cancer center at the USZ.
ResultsSince 2019, over 400 patients have been treated. A representative analysis of data from 2024 shows that approximately 70% of patients attended logopedic sessions during R(C)T. Three months after R(C)T, the attendance rate for follow-up assessments was 76%, and it was 94% for postoperative assessments. These high attendance rates reflect the model’s acceptance. Challenges related to integration and implementation primarily concern resource planning and interdisciplinary collaboration.
ConclusionThe presented outpatient clinic model provides a structured approach to logopedic care for head and neck cancer patients. Its successful implementation at the USZ demonstrates that it can serve as an example for similar models in other clinics. The described challenges and practical considerations offer valuable insights for the implementation of such models in other settings.