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ORBDA: An &ITopen&ITEHR benchmark dataset for performance assessment of electronic health record servers
University of Estado Rio de Janeiro, Brazil; Swiss Institute Bioinformat, Switzerland; HEG Geneva, Switzerland.
Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering.
University of Estado Rio de Janeiro, Brazil.
Swiss Institute Bioinformat, Switzerland; HEG Geneva, Switzerland.
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2018 (English)In: PLoS ONE, ISSN 1932-6203, E-ISSN 1932-6203, Vol. 13, no 1, article id e0190028Article in journal (Refereed) Published
Abstract [en]

The openEHR specifications are designed to support implementation of flexible and interoperable Electronic Health Record (EHR) systems. Despite the increasing number of solutions based on the openEHR specifications, it is difficult to find publicly available healthcare datasets in the openEHR format that can be used to test, compare and validate different data persistence mechanisms for openEHR. To foster research on openEHR servers, we present the openEHR Benchmark Dataset, ORBDA, a very large healthcare benchmark dataset encoded using the openEHR formalism. To construct ORBDA, we extracted and cleaned a de-identified dataset from the Brazilian National Healthcare System (SUS) containing hospitalisation and high complexity procedures information and formalised it using a set of openEHR archetypes and templates. Then, we implemented a tool to enrich the raw relational data and convert it into the openEHR model using the openEHR Java reference model library. The ORBDA dataset is available in composition, versioned composition and EHR openEHR representations in XML and JSON formats. In total, the dataset contains more than 150 million composition records. We describe the dataset and provide means to access it. Additionally, we demonstrate the usage of ORBDA for evaluating inserting throughput and query latency performances of some NoSQL database management systems. We believe that ORBDA is a valuable asset for assessing storage models for openEHR-based information systems during the software engineering process. It may also be a suitable component in future standardised benchmarking of available openEHR storage platforms.

Place, publisher, year, edition, pages
PUBLIC LIBRARY SCIENCE , 2018. Vol. 13, no 1, article id e0190028
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Computer Systems
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URN: urn:nbn:se:liu:diva-144560DOI: 10.1371/journal.pone.0190028ISI: 000419101600054PubMedID: 29293556OAI: oai:DiVA.org:liu-144560DiVA, id: diva2:1178286
Note

Funding Agencies|CNPq [150916/2013-2]; INCT-MACC [15/2008]

Available from: 2018-01-29 Created: 2018-01-29 Last updated: 2018-01-29

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