An Electronic Healthcare Record Server Implemented in PostgreSQL

Austin, Tony; Sun, Shanghua; Lim, Yin Su; Nguyen, David H.; Lea, Nathan; Tapuria, Archana

doi:10.1260/2040-2295.6.3.325

Cited by 16 publications

(11 citation statements)

References 10 publications

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“…The EN13606 archetypes use ADL as the preferred format. The CDISC ODM has data stored as XML files and the commonly used databases with EN13606 are MySQL, PostGreSQL, 49 Oracle and SQL server.…”

Section: Discussionmentioning

confidence: 99%

Comparison and transformation between CDISC ODM and EN13606 EHR standards in connecting EHR data with clinical trial research data

et al. 2018

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ObjectivesIntegrating Electronic Health Record (EHR) systems into the field of clinical trials still contains several challenges and obstacles. Heterogeneous standards and specifications are used to represent healthcare and clinical trial information. Therefore, this work investigates the mapping and data interoperability between healthcare and research standards: EN13606 used for the EHRs and the Clinical Data Interchange Standards Consortium Operational Data Model (CDISC ODM) used for clinical research.MethodsBased on the specifications of CDISC ODM 1.3.2 and EN13606, a mapping between the structure and components of both standards has been performed. Archetype Definition Language (ADL) forms built with the EN13606 editor were transformed to ODM XML and reviewed. As a proof of concept, clinical sample data has been transformed into ODM and imported into an electronic data capture system. Reverse transformation from ODM to ADL has also been performed and finally reviewed concerning map-ability.ResultsThe mapping between EN13606 and CDISC ODM shows the similarities and differences between the components and overall record structure of the two standards. An EN13606 archetype corresponds with a group of items within CDISC ODM. Transformations of element names, descriptions, different languages, datatypes, cardinality, optionality, units, value range and terminology codes are possible from EN13606 to CDISC ODM and vice versa.ConclusionIt is feasible to map data elements between EN13606 and CDISC ODM and transformation of forms between ADL and ODM XML format is possible with only minor limitations. EN13606 can accommodate clinical information in a more structured manner with more constraints, whereas CDISC ODM is more suitable and specific for clinical trials and studies. It is feasible to transform EHR data in the EN13606 form to ODM to transfer it into research database. The attempt to use EN13606 to build a study protocol (that was already built with CDISC ODM) also suggests the possibility of using EN13606 standard in place of CDISC ODM if needed to avoid transformations.

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Section: Discussionmentioning

confidence: 99%

Comparison and transformation between CDISC ODM and EN13606 EHR standards in connecting EHR data with clinical trial research data

et al. 2018

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“…There are some proposals that use a relational representation. Austin et al [48] developed an EHR server inside a relational database using CEN/ISO 13606 as the information basis for the design of the server. In this case, the choice of a relational representation imposes limits that impede the representation of many features of the standard.…”

Section: Discussionmentioning

confidence: 99%

OntoCR: A CEN/ISO-13606 clinical repository based on ontologies

Lozano-Rubí

Carrero

Balazote

et al. 2016

Journal of Biomedical Informatics

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“…Other openEHR solutions include yourEHRM [49] by Atos Research that uses MongoDB as internal DBMS and a piece of software cited in paper by Austin et al [50] that adopts PostgreSQL and it's the core inside both an academic product named Cortext and a commercial one called HeliconHeart.…”

Section: Related Workmentioning

confidence: 99%

A Scalable Data Access Layer to Manage Structured Heterogeneous Biomedical Data

Delussu¹,

Lianas²,

Frexia³

et al. 2016

Preprint

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This work presents a scalable data access layer, called PyEHR, designed to support the implementation of data management systems for secondary use of structured heterogeneous biomedical and clinical data. PyEHR adopts the openEHR's formalisms to guarantee the decoupling of data descriptions from implementation details and exploits structure indexing to accelerate searches. Data persistence is guaranteed by a driver layer with a common driver interface. Interfaces for two NoSQL Database Management Systems are already implemented: MongoDB and Elasticsearch. We evaluated the scalability of PyEHR experimentally through two types of tests, called "Constant Load" and "Constant Number of Records", with queries of increasing complexity on synthetic datasets of ten million records each, containing very complex openEHR archetype structures, distributed on up to ten computing nodes.

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An Electronic Healthcare Record Server Implemented in PostgreSQL

Cited by 16 publications

References 10 publications

Comparison and transformation between CDISC ODM and EN13606 EHR standards in connecting EHR data with clinical trial research data

Comparison and transformation between CDISC ODM and EN13606 EHR standards in connecting EHR data with clinical trial research data

OntoCR: A CEN/ISO-13606 clinical repository based on ontologies

A Scalable Data Access Layer to Manage Structured Heterogeneous Biomedical Data

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