Dear David, other colleague authors,

This is an excellent paper and a very valuable contribution on the practical 
adoption of archetypes.

With best wishes,

Dipak Kalra

On 19 Jun 2015, at 10:07, David Moner 
<[email protected]<mailto:[email protected]>> wrote:

Dear all,

My colleagues Luis Marco-Ruiz, Jos? A. Maldonado, Nils Kolstrup, Johan G. 
Bellika and myself have just published a paper titled "Archetype-based data 
warehouse environment to enable the reuse of electronic health record data" in 
the International Journal of Medical Informatics. I think this work can be of 
interest for many of you.

Best regards,
David

Link: http://www.sciencedirect.com/science/article/pii/S1386505615300058

Abstract:

- 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.


--
David Moner Cano
Grupo de Inform?tica Biom?dica - IBIME
Instituto ITACA
http://www.ibime.upv.es
http://www.linkedin.com/in/davidmoner

Universidad Polit?cnica de Valencia (UPV)
Camino de Vera, s/n, Edificio G-8, Acceso B, 3? planta
Valencia - 46022 (Espa?a)
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