Pathways Home Project: Patient Self-management and Self-efficacy through the Deployment of ICTs

This research-in-progress paper presents an examination of, and reflections on, the challenges of using information and communication technologies (ICTs) to support patients suffering chronic respiratory conditions to achieve increased levels of selfmanagement and self-efficacy. These research insights arise as part of the planning and on-going implementation of the Pathways Home for Respiratory Illness project (Pathways). This project seeks to assist patients with either chronic obstructive pulmonary disease (COPD) or cystic fibrosis (CF) to acquire skills that empower them to comprehend and initiate action in relation to alterations in their conditions. The overall aim of Pathways is to evaluate the impact of these newly acquired skills for improving health outcomes at individual and population levels and is due for completion in 2008. Achieving benefits from the introduction of ICTs as part of processes aimed at building sustainable self-efficacy and self-management is very difficult, not least because of a desire to avoid simply replacing patient dependency on health professionals with dependency on technology. Reflections on the challenges and experiences within the project to-date illuminate some implicit assumptions underpinning existing IS models for evaluating impact in terms of adoption, usage and benefit and the end-points we presume in our system development processes

Kolmogorov-Sinai entropy from recurrence times

Observing how long a dynamical system takes to return to some state is one of the most simple ways to model and quantify its dynamics from data series. This work proposes two formulas to estimate the KS entropy and a lower bound of it, a sort of Shannon's entropy per unit of time, from the recurrence times of chaotic systems. One formula provides the KS entropy and is more theoretically oriented since one has to measure also the low probable very long returns. The other provides a lower bound for the KS entropy and is more experimentally oriented since one has to measure only the high probable short returns. These formulas are a consequence of the fact that the series of returns do contain the same information of the trajectory that generated it. That suggests that recurrence times might be valuable when making models of complex systems