PhD Thesis online: Detailed clinical models and their relation with Electronic Health Records

Mate Beštek mate.bestek at gmail.com
Thu Jan 28 07:13:12 EST 2016


Congratulations!

Regards,Mate

On 28 January 2016 at 11:22, Nadim Anani <Nadim.Anani at ki.se> wrote:

> Dear Diego,
>
> Congratulations and Thank you!!!! Very impressive work (that is visible
> without reading every detail, which I have not had the time for yet)!!!!
>
> Sincerely,
> Nadim
>
> -----Original Message-----
> From: openEHR-technical [mailto:
> openehr-technical-bounces at lists.openehr.org] On Behalf Of Diego Boscá
> Sent: den 27 januari 2016 21:41
> To: For openEHR clinical discussions; For openEHR technical discussions;
> For openEHR implementation discussions
> Subject: PhD Thesis online: Detailed clinical models and their relation
> with Electronic Health Records
>
> Hello all,
>
> My thesis "Detailed clinical models and their relation with Electronic
> Health Records" is now available online. Until the university publishes it
> on the public repository, here is a link to it.
>
> https://www.dropbox.com/s/rqmmh9b541u7wpr/TesisDiego_v2.pdf?dl=0
>
> The slides are also available just in case anyone wants a quick summary
>
>
> http://www.slideshare.net/yampeku/detailed-clinical-models-and-their-relation-with-electronic-health-records
>
> I also attach the abstract below
>
> Best Regards
>
> Diego Boscá
>
> Abstract
> Healthcare domain produces and consumes big quantities of people’s health
> data. Although data exchange is the norm rather than the exception, being
> able to access to all patient data is still far from achieved. Current
> developments such as personal health records will introduce even more data
> and complexity to the Electronic Health Records (EHR).
> Achieving semantic
> interoperability is one of the biggest challenges to overcome in order to
> benefit from all the information contained in the distributed EHR. This
> requires that the semantics of the information can be understood by all
> involved parties. It has been established that three layers are needed to
> achieve semantic interoperability: Reference models, clinical models
> (archetypes), and clinical terminologies.
>
> As seen in the literature, information models (reference models and
> clinical models) are lacking methodologies and tools to improve EHR systems
> and to develop new systems that can be semantically interoperable. The
> purpose of this thesis is to provide methodologies and tools for advancing
> the use of archetypes in three different scenarios:
>
> - Archetype definition over specifications with no dual model architecture
> native support. Any EHR architecture that directly or indirectly has the
> notion of detailed clinical models (such as HL7 CDA templates) can be
> potentially used as a reference model for archetype definition. This allows
> transforming single-model architectures (which contain only a reference
> model) into dual-model architectures (reference model with archetypes). A
> set of methodologies and tools has been developed to support the definition
> of archetypes from multiple reference models.
>
> - Data transformation. A complete methodology and tools are proposed to
> deal with the transformation of legacy data into XML documents compliant
> with the archetype and the underlying reference model. If the reference
> model is a standard then the transformation is a standardization process.
> The methodologies and tools allow both the transformation of legacy data
> and the transformation of data between different EHR standards.
>
> - Automatic generation of implementation guides and reference materials
> from archetypes. A methodology for the automatic generation of a set of
> reference materials is provided. These materials are useful for the
> development and use of EHR systems. These reference materials include data
> validators, example instances, implementation guides, human-readable formal
> rules, sample forms, mindmaps, etc.
> These reference materials can be combined and organized in different ways
> to adapt to different types of users (clinical or information technology
> staff). This way, users can include the detailed clinical model in their
> organization workflow and cooperate in the model definition.
>
> These methodologies and tools put clinical models as a key part of the
> system. The set of presented methodologies and tools ease the achievement
> of semantic interoperability by providing means for the semantic
> description, normalization, and validation of existing and new systems.
>
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