Quality of data computational models and telemedicine treatment effects

Clinical decision-support functions of telemedicine systems use patient's monitored clinical data to support treatment of outpatients. However, the quality of monitored clinical data may vary due to performance variations of technological resources inside a deployed telemedicine system. This paper discusses models to compute quality of clinical data affected by quality of service provided by technological resources along the data processing and delivery chain between the point of monitoring and point of decision. We discuss prospective effects of quality of clinical data degradation on outpatient treatment with medical practitioners, and implement these effects in the clinical decision-making process during design time. Consequently, the designed telemedicine system is technological context and quality-aware and preserves patient's safety and treatment efficacy.

[1]  Richard Y. Wang,et al.  Anchoring data quality dimensions in ontological foundations , 1996, CACM.

[2]  Yuval Shahar,et al.  Temporal Information Systems in Medicine , 2010 .

[3]  Anind K. Dey,et al.  Understanding and Using Context , 2001, Personal and Ubiquitous Computing.

[4]  Nicola Zannone,et al.  Data reliability in home healthcare services , 2013, Proceedings of the 26th IEEE International Symposium on Computer-Based Medical Systems.

[5]  I. Romero,et al.  Comparative study of algorithms for Atrial Fibrillation detection , 2011, 2011 Computing in Cardiology.

[6]  Ing Widya,et al.  QoC-based Optimization of End-to-End M-Health Data Delivery Services , 2006, 200614th IEEE International Workshop on Quality of Service.

[7]  Klaus Fuglsang Kofoed,et al.  Effect of physical exercise training on muscle strength and body composition, and their association with functional capacity and quality of life in patients with atrial fibrillation: a randomized controlled trial. , 2012, Journal of rehabilitation medicine.

[8]  Hermie Hermens,et al.  Early phase telemedicine requirements elicitation in collaboration with medical practitioners , 2013, 2013 21st IEEE International Requirements Engineering Conference (RE).

[9]  G. Guyatt,et al.  Going from evidence to recommendations , 2008, BMJ : British Medical Journal.

[10]  R A Bruce,et al.  Exercise testing for evaluation of ventricular function. , 1977, The New England journal of medicine.

[11]  Minho Shin.  Secure Remote Health Monitoring with Unreliable Mobile Devices , 2012, Journal of biomedicine & biotechnology.

[12]  Hermie Hermens,et al.  Making medical treatments resilient to technological disruptions in telemedicine systems , 2014, IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI).

[13]  Ing Widya,et al.  On the End-User QoS-Awareness of a Distributed Service Environment , 2001, PROMS.

[14]  Stuart E. Madnick,et al.  Data quality requirements analysis and modeling , 2011, Proceedings of IEEE 9th International Conference on Data Engineering.