Ross Sparks *, Branko Celler , Chris Okugami , Rajiv Jayasena and Marlien Varnfield
Telehealth Monitoring of Patients in the Community
Abstract: This article outlines a decision support system that seeks to help community nurses monitor the
well-being of their chronically ill patients. It is designed for nurses to stay in contact with their patients
without spending unnecessary time on less productive aspects of community nursing, such as avoidable
driving to and from patients ’ houses and taking measurements of vital signs to assess their health condition.
It therefore allows the nurse to spend more time on managing the factors that could lead to a healthier patient.
The decision support system is developed for two levels of mathematical capability. Nurses with a statistical
background are provided with in-depth information allowing them to detect changes in mean, mean square
error (and hence variation), and correlations using a variation on dynamic principle components. Less mathematically
inclined nurses are offered information about trends, change points, and a simpler multivariate
view of a patient ’ s well-being involving parallel coordinate plots.
Keywords: surveillance, early detection, false discovery rate, well-being.