DocumentCode :
3472928
Title :
Peer-to-peer data discovery in health centers
Author :
Mirto, Maria ; Cafaro, Massimo ; Aloisio, Giovanni
Author_Institution :
Euro Mediterranean Center on Climate Change (CMCC), Univ. of Salento, Lecce, Lecce, Italy
fYear :
2013
fDate :
20-22 June 2013
Firstpage :
343
Lastpage :
348
Abstract :
The sharing and integration of health care data such as medical history, pathology, therapy, radiology images, etc., is a key requirement for improving the patient diagnosis and in general the patient care. Today, many EPR (Electronic Patient Record) systems are present both in the same or different health centers and record a huge amount of data regarding a patient. In most cases the care treatment of a patient involves different healthcare facilities, including the cares provided by the family doctors. Managing these data, typically petabytes or terabytes in size, and optimizing the applications (image analysis, data mining, etc.) for these architectures is one of the challenges that must be tackled. Therefore, there is a clear need for the design and implementation of new scalable approaches to deal with the associated information overload and cognitive complexity issues. A possible solution involves considering a simplification of data coming from different EPRs, in a structured schema, typically called a meta-EPR. Owing to the security of patient data, each health center manages its own meta-EPR whereas a framework integrates these data among different sites. This work addresses the issue of sharing and integrating health care data, proposing a meta-EPR, based on Peer-to-peer (P2P) technology for data fusion. We describe an implementation of a distributed information service, that shares meta-EPRs and provides aggregation of relevant clinical information about patients based on a structured P2P overlay.
Keywords :
data mining; health care; medical diagnostic computing; medical information systems; patient care; patient diagnosis; peer-to-peer computing; P2P technology; associated information overload; cognitive complexity issues; data fusion; data mining; distributed information service; electronic patient record systems; health care data integration; health care data sharing; health centers; image analysis; medical history; pathology; patient care; patient care treatment; patient data security; patient diagnosis; peer-to-peer data discovery; radiology images; structured P2P overlay; therapy; Biomedical imaging; Data mining; Data models; Information services; Medical services; Peer-to-peer computing; Security;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer-Based Medical Systems (CBMS), 2013 IEEE 26th International Symposium on
Conference_Location :
Porto
Type :
conf
DOI :
10.1109/CBMS.2013.6627813
Filename :
6627813
Link To Document :
بازگشت