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-boun...@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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