A guideline-based decision support system for generating referral recommendations from routinely recorded home telehealth measurement data

The objectives of this paper are to present a guideline-based decision support system (GBDSS) design for supporting patient telehealth management of chronic disease and to test its performance in correctly making referral recommendations using routinely recorded measurement data from home telehealth recordings. The GBDSS has been developed to manage lung disease patients in a home telehealth environment. The system operates by checking the availability of home telehealth measurement data on a daily basis, interprets these data using a rule-based decision tree classification, and ultimately generates referral recommendations based on these measured data. The system has demonstrated discriminative power when applied in the analysis of retrospective telehealth data, as a surrogate for realtime referral generation. To this end a telehealth dataset comprising 16 chronic obstructive pulmonary disease (COPD) patients monitored over a 12 month period was used. It was shown that GBDSS referral recommendations could help reduce the number of cases that required a carer´s urgent attention by 72.1%, with 81.9% accuracy, 80.8% specificity and 90.4% sensitivity.