Archetype-based data warehouse environment to enable the reuse of electronic health record data.
BACKGROUND
The reuse of data captured during health care delivery is essential to satisfy the demands of clinical research and clinical decision support systems. A main barrier for the reuse is the existence of legacy formats of data and the high granularity of it when stored in an electronic health record (EHR) system. Thus, we need mechanisms to standardize, aggregate, and query data concealed in the EHRs, to allow their reuse whenever they are needed.


OBJECTIVE
To create a data warehouse infrastructure using archetype-based technologies, standards and query languages to enable the interoperability needed for data reuse.


MATERIALS AND METHODS
The work presented makes use of best of breed archetype-based data transformation and storage technologies to create a workflow for the modeling, extraction, transformation and load of EHR proprietary data into standardized data repositories. We converted legacy data and performed patient-centered aggregations via archetype-based transformations. Later, specific purpose aggregations were performed at a query level for particular use cases.


RESULTS
Laboratory test results of a population of 230,000 patients belonging to Troms and Finnmark counties in Norway requested between January 2013 and November 2014 have been standardized. Test records normalization has been performed by defining transformation and aggregation functions between the laboratory records and an archetype. These mappings were used to automatically generate open EHR compliant data. These data were loaded into an archetype-based data warehouse. Once loaded, we defined indicators linked to the data in the warehouse to monitor test activity of Salmonella and Pertussis using the archetype query language.


DISCUSSION
Archetype-based standards and technologies can be used to create a data warehouse environment that enables data from EHR systems to be reused in clinical research and decision support systems. With this approach, existing EHR data becomes available in a standardized and interoperable format, thus opening a world of possibilities toward semantic or concept-based reuse, query and communication of clinical data.
['Marco-Ruiz|Luis|L|', 'Moner|David|D|', 'Maldonado|José A|JA|', 'Kolstrup|Nils|N|', 'Bellika|Johan G|JG|']
D016208:Databases, Factual D020000:Decision Support Systems, Clinical D003695:Delivery of Health Care D057286:Electronic Health Records D006801:Humans D016247:Information Storage and Retrieval D008498:Medical Record Linkage D016347:Medical Records Systems, Computerized D009664:Norway D012660:Semantics D012984:Software D018511:Systems Integration D014584:User-Computer Interface
Data warehouse Electronic health record Data reuse Semantic interoperability openEHR