Personalising Symptoms Reporting in Telemonitoring Applications for Cancer Patients

Abstract

Patient reported outcomes have been shown to be predictive of cancer patients' prognosis, and their monitoring through electronic applications have been shown to positively impact survival. On the other hand, patient apps in general show a number of criticalities that often lead patients to abandon their use. One of them is usability. A scarce attention to usability during app development leads to unsatisfactory user experience. In this work, we present an algorithm to facilitate patient symptoms reporting, by personalising the list of symptoms according to their probability of occurrence in the specific patient. This avoids searching long lists of items, thus decreasing the patients' burden in symptom reporting.