Reducing the psychological burden of isolated oncological patients by means of decision trees

This century has seen several outbreaks of epidemics caused by a common sub-family of coronaviruses such as the responsible for COVID-19 outbreak. The most ominous variants have developed a peculiar viral mechanisms that allows the virus to directly attack the pulmonary tissues often causing a set of dangerous symptoms. It made quite evident that we need a global response to prepare health systems for future epidemics. Unfortunately, during such kind of diseases’ outbreaks a large amount of time is required to the caregivers for sanitization and cleaning operations, therefore tampering with number and duration of visits to patients, especially in oncology wards. Such patients are then left alone for a long time, it follows that their perceived quality of service is greatly diminished, often determining ill-fated consequences also on the psychological side, with significant fallbacks on the recovery possibilities and speed. In this paper we explore an algorithmic approach to automatic communication interfaces that could enhance and enforce the perceived quality of care by the patients in in order to reduce predisposing factors that could potentially tamper with the patient’s ability to recover, also preventing the occurrence of precipitating factors that could lead a therapy to complete failure. The proposed interface could be used to connect the patients with a psychological support when it is most needed, and, moreover, to connect them with their physicians and families, and also to the outside world. In particular we aim to provide the psychological support that is actually excluded in pandemics such as the COVID-19 emergency, mainly in order to enforce the healthcare and sanification protocols, due to its potential unsafety related to the introduction of more personnel into the hospital.