Literature DB >> 24001923

A new tool for sharing and querying of clinical documents modeled using HL7 Version 3 standard.

Vasil Slavov1, Praveen Rao, Srivenu Paturi, Tivakar Komara Swami, Michael Barnes, Deepthi Rao, Raghuvarun Palvai.   

Abstract

We present a new software tool called CDN (Collaborative Data Network) for sharing and querying of clinical documents modeled using HL7 v3 standard (e.g., Clinical Document Architecture (CDA), Continuity of Care Document (CCD)). Similar to the caBIG initiative, CDN aims to foster innovations in cancer treatment and diagnosis through large-scale, sharing of clinical data. We focus on cancer because it is the second leading cause of deaths in the US. CDN is based on the synergistic combination of peer-to-peer technology and the extensible markup language XML and XQuery. Using CDN, a user can pose both structured queries and keyword queries on the HL7 v3 documents hosted by data providers. CDN is unique in its design--it supports location oblivious queries in a large-scale, network wherein a user does not explicitly provide the location of the data for a query. A location service in CDN discovers data of interest in the network at query time. CDN uses standard cryptographic techniques to provide security to data providers and protect the privacy of patients. Using CDN, a user can pose clinical queries pertaining to cancer containing aggregations and joins across data hosted by multiple data providers. CDN is implemented with open-source software for web application development and XML query processing. We ran CDN in a distributed environment using Amazon EC2 as a testbed. We report its performance on real and synthetic datasets of discharge summaries. We show that CDN can achieve good performance in a setup with large number of data providers and documents.
Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Entities:  

Keywords:  HL7 v3; P2P; Query processing; Security; XML

Mesh:

Year:  2013        PMID: 24001923     DOI: 10.1016/j.cmpb.2013.07.002

Source DB:  PubMed          Journal:  Comput Methods Programs Biomed        ISSN: 0169-2607            Impact factor:   5.428


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