A Digital Platform to Support Self-management of Multiple Chronic Conditions (ProACT): Findings in Relation to Engagement During a One-Year Proof-of-Concept Trial.

Background: Populations globally are ageing, resulting in higher incidence rates of chronic diseases. Digital health platforms, designed to support those with chronic conditions to self-manage at home, offer a promising solution to help people monitor their conditions and lifestyle, maintain good health, and reduce unscheduled clinical visits. However, despite high prevalence rates of multimorbidity or multiple chronic conditions, most platforms tend to focus on a single disease.

KITE: An Analytics Platform for Multimorbidity Management.

Managing multimorbidity entails processing distributed, dynamic and heterogeneous data using diverse analytics tools. We present KITE, a Cloud-based infrastructure allowing the aggregation and processing of health data using a dynamic set of analytical components. We showcase KITE in the context of the ProACT project, aiming at advancing home-based integrated care though IoT, analytics and a behavior change framework.

An Analytical Method for Multimorbidity Management Using Bayesian Networks.

This paper describes an application of Bayesian Networks to mo-del persons with multimorbidity using measurements of vital signs and lifestyle assessments. The model was developed as part of a project on the use of wearable and home sensors and tablet applications to help persons with multimorbidity and their carers manage their conditions in daily life. The training data was extracted from TILDA, an open dataset collected from a longitudinal health study of the older Irish population.

Using Semantic Technologies to Extract Highlights from Care Notes.

We propose a cognitive system for patient-centric care that leverages and combines natural language processing, semantics, and learning from users over time to support care professionals working with large volumes of patient notes. The proposed methods highlight the entities embedded in the unstructured data to provide a holistic semantic view of an individual. A user-based evaluation is presented, showing consensus between the users and the system.