A Preliminary Validation of an Optimal Cutpoint in Total Number of Patient-Reported Symptoms in Head and Neck Cancer for Effective Alignment of Clinical Resources with Patients' Symptom Burden.

Background: Patients with head and neck cancer (HNC) often experience high symptom burden leading to lower quality of life (QoL).

Objective: This study aims to conceptually model optimal cutpoint by examining where total number of patient-reported symptoms exceeds patients' coping capacity, leading to a decline in QoL in patients with HNC.

Methods: Secondary data analysis of 105 individuals with HNC enrolled in a clinical usefulness study of the NYU Electronic Patient Visit Assessment (ePVA)©, a digital patient-reported symptom measure.

The usefulness of the Electronic Patient Visit Assessment (ePVA) as a clinical support tool for real-time interventions in head and neck cancer.

Background: Patients with head and neck cancer (HNC) experience painful, debilitating symptoms and functional limitations that can interrupt cancer treatment, and decrease their health-related quality of life (HRQoL). The Electronic Patient Visit Assessment (ePVA) for head and neck is a web-based mHealth patient-reported measure that asks questions about 21 categories of symptoms and functional limitations common to HNC. This article presents the development and usefulness of the ePVA as a clinical support tool for real-time interventions for patient-reported symptoms and functional limitations in HNC.

The development, usability, and reliability of the Electronic Patient Visit Assessment (ePVA) for head and neck cancer.

Background: Annually, over 65,000 persons are diagnosed with head and neck cancer in the United States. During treatment, up to 50% of patients become severely symptomatic with pain, fatigue, mouth sores, and inability to eat. Long term complications are lymphedema, fibrosis, dysphagia, and musculoskeletal impairment.