Towards Knowledge Sharing and Patient Privacy in a Clinical Decision Support System
Copyright © 2009 IEEE. Reprinted from Proceedings of the 31st International Conference on Information Technology Interfaces (ITI’09), pp.99-104, IEEE Computer Society Press, 2009. This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of the Royal College of Surgeons in Ireland products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to firstname.lastname@example.org. By choosing to view this document, you agree to all provisions of the copyright laws protecting it.
Patient records and their disease and treatment history can be scattered among healthcare providers. Sharing the knowledge effectively and, at the same time, respecting patient privacy is crucial in providing safe and accurate clinical decision support systems (CDSSs). In this paper we reflect upon our experience in the HealthAgents project wherein a prototype system was developed and a novel approach employed that supports data transfer and decision making in human brain tumour diagnosis. Here we examine the capability of the Lightweight Coordination Calculus (LCC), a process calculus-based language, in combining together distributed healthcare services and meeting security challenges in pervasive settings. The result is that various clinical specialisms, being captured in representational abstractions and making contribution to patient diagnosis and management, retain their autonomy. However, at the same time, the behaviour of specialists in sharing clinical knowledge about their patients and providing clinical support is constrained by policies and rules in respect of their own clinical duties and responsibilities. Being introduced into the programme of the HRB Centre for Primary Care Research, this novel approach has the potential to help the provision of optimal solutions in data linkage and sharing across the Primary and Secondary Care interface. As added value, its application also advances the process of integrating clinical prediction rules and implementing CDSSs in practice and, ultimately, the improvement of quality of care.
Liang Xiao, Bo Hu, Lucy Hederman, Paul Lewis, Borislav D Dimitrov, Tom Fahey, "Towards Knowledge Sharing and Patient Privacy in a Clinical Decision Support System", Proceedings of the 31st International Conference on Information Technology Interfaces (ITI’09), pp.99-104, IEEE Computer Society Press, 2009.