Integration of Recommendation Systems Into Connected Health for Effective Management of Chronic Diseases

Abstract

An important trend in meeting the needs of modern caregiving is providing a well-rounded care delivery. In doing this, access to data of care receiver is important. This, however, has been shown to be possible with connected health with the aid of modern technology. In this paper, we are presenting a design that will expand on the opportunities for better data accessibility and use, by integrating the recommendation system into connected health. In order to ensure a design that meets the needs of care receivers, we conducted two independent surveys with a view to gathering requirements for the design. The result has shown the relevance of timeliness in caregiving along with what the care receivers are interested in such as what their data say about their conditions, the immediate and future expectation of their conditions, and collaborative efforts in managing their conditions. The requirements gathered were used in the design and implementation of the mobile app called Recommendations Sharing Community for Aged and Chronically Ill People (ReSCAP). The benefits of this solution have been real-time recommendations' availability, cost saving, adequate care, and access to health data and information for better care decision-making.INDEX TERMS Recommender systems, connected health real-time recommendations, ReTReSCAP, ReSCAP, healthcare.

Towards a Reference Architecture for Female-Sensitive Drug Management

“…The described recommender systems mostly use a hybrid collaborative filtering technique to overcome the cold start problem [42]. According to these contributions, mobile applications differentiate themselves from others by their high flexibility and acceptance, enabling the elicitation of sensor and fitness data as an additional source of information [43].…”

Multidimensional Group Recommendations in the Health Domain

“…For example, the authors of [34,35] propose web-based recommender systems that provides individualized nutritional recommendations according to the user's health profile defined, by following the main guidelines furnished by a medical specialist, whereas the authors of [36] suggest messages relevant to the user to support the smoking cessation process. The work in [37] is a recommender system proposing physical activities using only user's history and employing machine learning, whereas for chronic conditions, other works focus on integrating recommender systems with electronic health records [38,39], proposing the best course of treatment. Other approaches adapt past recommendations to the current state of the user for Diabetes patients [40] or propose context-aware recommendation methods [41] to establish personalized healthcare services.…”

“Nomen Omen”: Exploring Connected Healthcare through the Perspective of Name Omen

“…Connected health has its roots in telemedicine [26]. It was initially used only for serving people in remote areas and has now expanded to cater to those who have chronic conditions [27]. Many pilot schemes have been applied in Veteran Health Affairs [1,28].…”