Evaluating new telemedicine interventions for chronic disease is not easy and it remains unclear how to use the existing evidence to inform the design of new telemedicine programs. In particular, there are not structured methods to define relevant aspects of a new home monitoring intervention as frequency of monitoring (daily vs weekly), complexity of monitoring (symptoms vs biopotentials) and the severity of target population (age, pathology severity). This paper describes a second order polynomial model that has been used to define the target population for the clinical protocol of the UE-funded research project titled “Smart health and artificial intelligence for Risk Estimation” (SHARE).
|Titolo:||A preliminary model to choose the most appropriate target population for home monitoring telemedicine interventions basing on the best available evidence|
|Autori interni:||MELILLO, Paolo|
|Data di pubblicazione:||2014|
|Rivista:||LECTURE NOTES IN COMPUTER SCIENCE|
|Appare nelle tipologie:||4.1 Contributo in Atti di convegno|