Querying Archetype-Based Electronic Health Records Using Hadoop and Dewey Encoding of openEHR Models.
Stud Health Technol Inform
; 235: 406-410, 2017.
Article
en En
| MEDLINE
| ID: mdl-28423824
ABSTRACT
Archetype-based Electronic Health Record (EHR) systems using generic reference models from e.g. openEHR, ISO 13606 or CIMI should be easy to update and reconfigure with new types (or versions) of data models or entries, ideally with very limited programming or manual database tweaking. Exploratory research (e.g. epidemiology) leading to ad-hoc querying on a population-wide scale can be a challenge in such environments. This publication describes implementation and test of an archetype-aware Dewey encoding optimization that can be used to produce such systems in environments supporting relational operations, e.g. RDBMs and distributed map-reduce frameworks like Hadoop. Initial testing was done using a nine-node 2.2 GHz quad-core Hadoop cluster querying a dataset consisting of targeted extracts from 4+ million real patient EHRs, query results with sub-minute response time were obtained.
Palabras clave
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Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Sistemas de Administración de Bases de Datos
/
Sistemas de Registros Médicos Computarizados
/
Registros Electrónicos de Salud
Tipo de estudio:
Prognostic_studies
Límite:
Humans
Idioma:
En
Revista:
Stud Health Technol Inform
Asunto de la revista:
INFORMATICA MEDICA
/
PESQUISA EM SERVICOS DE SAUDE
Año:
2017
Tipo del documento:
Article
País de afiliación:
Suecia