TY - GEN
T1 - A decision support architecture for telecare patient management of chronic and complex disease
AU - Basilakis, J.
AU - Lovell, N. H.
AU - Celler, Branko
PY - 2007
Y1 - 2007
N2 - A major challenge facing designers of telecare systems today is providing decision support to enhance the health carer's review of remotely acquired monitoring data and to support clinical decision-making for the management of chronic and complex disease in this setting. We are implementing a decision support framework to analyze clinical information generated from subjects at their place of residence (home, residential care settings) and from other clinical environments. The telecare information generated from these environments is both substantial and multi-modal (physiological, questionnaire, medication data, etc.). Using the JBoss Application Server, a rules engine is used to analyze these data. The health carer will be alerted to any deterioration in the health status of a patient by way of a Web page that will stratify a clinical data summary into high, medium and low risk groups. In this way, outputs from the decision support system can be used to assist in the efficient review and risk stratification of multiple patient records, and ultimately influence changes in work flow by targeting scarce human resources to patients of most need.
AB - A major challenge facing designers of telecare systems today is providing decision support to enhance the health carer's review of remotely acquired monitoring data and to support clinical decision-making for the management of chronic and complex disease in this setting. We are implementing a decision support framework to analyze clinical information generated from subjects at their place of residence (home, residential care settings) and from other clinical environments. The telecare information generated from these environments is both substantial and multi-modal (physiological, questionnaire, medication data, etc.). Using the JBoss Application Server, a rules engine is used to analyze these data. The health carer will be alerted to any deterioration in the health status of a patient by way of a Web page that will stratify a clinical data summary into high, medium and low risk groups. In this way, outputs from the decision support system can be used to assist in the efficient review and risk stratification of multiple patient records, and ultimately influence changes in work flow by targeting scarce human resources to patients of most need.
UR - http://www.scopus.com/inward/record.url?scp=57649201914&partnerID=8YFLogxK
U2 - 10.1109/IEMBS.2007.4353296
DO - 10.1109/IEMBS.2007.4353296
M3 - Conference Paper
C2 - 18002962
AN - SCOPUS:57649201914
SN - 1424407885
SN - 9781424407880
T3 - Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings
SP - 4335
EP - 4338
BT - 29th Annual International Conference of IEEE-EMBS, Engineering in Medicine and Biology Society, EMBC'07
T2 - 29th Annual International Conference of IEEE-EMBS, Engineering in Medicine and Biology Society, EMBC'07
Y2 - 23 August 2007 through 26 August 2007
ER -