Situational awareness and services acceptance in home care treatments

PhD student: 
Director(s): 
Co-supervisor(s): 
External supervisors: 

Grasset Olivier - Linde Homecare France

Starting date: 
March 2019
Tags: 
Host institution: 
Other institution: 
Linde Homecare France

Context
Obstructive Sleep Apnea Syndrome (OSA) is a respiratory sleep disorder in which the upper airways temporarily close during sleep. The goal treatment for this pathology is the Continuous Positive Airway Pressure Device (CPAP). This research work focuses on the issue of acceptance of treatment for OSA.

This CIFRE thesis project is the result of a collaboration between the Linde Homecare company and the DISP laboratory. The thesis takes place in a well defined industrial context with essential issues for the company. On the other hand, interest in research is also crucial since the compliance to OSA treatments is one of the lowest compared to other treatments. Besides, with the advent of telemedicine and the massive collection of data, new possibilities are opening up. Thus, a new data-driven approach, we want to improve adherence to OSA treatments.


Research issue
The research issue concerns the means of consolidating clinical monitoring data necessary for defining patient profiles and proposing personalized services impacting the compliance to OSA therapy. The three scientific and technological obstacles to which we are responding are:

  1. Data exploration and analytics Identifying the variables that characterize the adhesion is intricate work. Therefore the choice of the data set is essential in our case. This selection is all the more important to build a relevant analysis.
  2. Construction of the patient profile: Understanding the interactions of the various events that may occur in the patient's life. Thus, we can measure the impact of these interactions on patient adherence by doing a retrospective analysis of the data.
  3. Deliver personalized services: Provide personalized services according to the patient. This personalization will be attainable by utilizing the individual data of each patient in order to understand the precise needs of each patient.