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Applying openEHR’s Guideline Definition Language to the SITS international stroke treatment registry: a European retrospective observational study. BMC Medical Informatics and Decision Making BMC series – open, inclusive and trusted 2017 17:7

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Anani N. ; Mazya M.; Chen R.; Moreira T.; Bill O.; Ahmed N.; Wahlgren N.;Koch S.

“The successful application of a standard guideline formalism to a large patient registry dataset is an important step toward widespread implementation of computer-interpretable guidelines in clinical practice and registry-based research. Application of the methodology gave important results on the evolution of stroke care in Europe, important both for quality of care monitoring and clinical research.” (Anani N. et al, 2017)

Available from:

http://bmcmedinformdecismak.biomedcentral.com/articles/10.1186/s12911-016-0401-5

Building Chronic Kidney Disease Clinical Practice Guidelines Using the openEHR Guideline Definition Language. Methods Inf Med. 2016 Dec 7;55(6):495-505

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Lin CH, Lo YC, Hung PY, Liou DM.

“Based on the findings of this study, we identified some potential gaps that might exist during implementation between the GDL concept and reality. Three directions remain to be investigated in the future. Two of them are related to the openEHR GDL approach. Firstly, there is a need for the editing tool to be made more sophisticated. Secondly, there needs to be integration of the present approach into non openEHR-based hospital information systems. The last direction focuses on the applicability of guidelines and involves developing a method to resolve any conflicts that occur with insurance payment regulations.” (Lin CH, Lo YC, Hung PY, Liou DM, 2016)

Available from:

https://www.ncbi.nlm.nih.gov/pubmed/27588321

Publication, Discovery and Interoperability of Clinical Decision Support Systems: a Linked Data Approach. J Biomed Inform. 2016 Aug;62:243-64.

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Marco-Ruiz L. ; Pedrinaci C. ; Maldonado J.A. ; Panziera L. ; Chen R.; Gustav Bellika J.

“For example, openEHR GDL uses archetypes; the Arden Syntax links directly to the database encapsulating queries in its data section; SAGE uses a VMR based on HL7 RIM [6] and [36]; and recent developments such as the EU project Mobiguide [37] advocate for the use of HL7 vMR [38]. Both openEHR archetypes and HL7 templates (created from CDA or vMR) can be bound to terminologies to enrich the data structures with a certain level of clinical semantics.” (Marco-Ruiz L. et al, 2016)

Available from:

https://www.ncbi.nlm.nih.gov/pubmed/27401856

A semantic web based framework for the interoperability and exploitation of clinical models and EHR data. Knowledge-Based Systems, 1 August 2016, Vol.105, pp.175-189

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Legaz-García, María Del Carmen ; Martínez-Costa, Catalina ; Menárguez-Tortosa, Marcos ; Fernández-Breis, Jesualdo Tomás.

“In this paper we describe an OWL-based framework that leverages EHR and Semantic Web technologies for the interoperability and exploitation of archetypes, EHR data and ontologies. It also enables the secondary use of clinical data. This framework has been implemented in the Archetype Management System (ArchMS). We also describe how ArchMS has been used in a real study in the colorectal cancer domain.” (Legaz-Garcia et al, 2016)

Available from: 

http://www.sciencedirect.com/science/article/pii/S0950705116301058

Personalization and Patient Involvement in Decision Support Systems: Current Trends. IMIA Yearbook, 2015, pp.106-118.

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Quaglini S. ; Sacchi L. ; Lanzola G. ; Viani R. Röhrig D N. O´Sullivan ; S. Wilk ; W. Michalowski ; R. Slowinski ; R. Thomas ; M. Kadzinski ; K. Farion A. Geissbuhler.

“This highlights the current trend to replace specialized environments by inference engines built on top of standardized frameworks that allow managing ontologies (e.g. Protégé – http://protege.stanford.edu/) and data models (e.g., openEHR archetypes, and the related GDL-Guideline Definition Language – http://www.openehr.org/downloads/ds_and_guidelines). ” (Quaglini S. et al, 2015)

Available from: 

https://www.ncbi.nlm.nih.gov/pubmed/26293857

Computerized Clinical Decision Support: Contributions from 2014. Managing Editor for the Imia Yearbook Section on Sensors ; Signals ; and Imaging Informatics P. Ruch ; Managing Editor for the Imia Yearbook Section on Human Factors D. Kubias. IMIA Yearbook, 2015, pp.119-124.

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Bouaud J.;Koutkias V. Müller H.

“To summarize recent research and propose a selection of best papers published in 2014 in the field of computerized clinical decision support for the Decision Support section of the IMIA yearbook. Anani et al. [21] worked on the assessment of compliance with practice guidelines for acute stroke care. The study uses the openEHR’s Guideline Definition Language (GDL) as a mean to address the lack of commonly shared EHR models and terminology bindings, hampering CDS content sharing among different organizations. The study concluded with the successful representation of 14 out of 19 clinical rules on contraindications for thrombolysis and other aspects of acute stroke care by employing 80 GDL rules, and a complete match between manual and automated compliance results. In terms of applied systems, a number of studies focused on quite complex clinical conditions, such as the early recognition of sepsis [22-24], the prediction of periventricular leukomalacia in neonates after heart surgery [25], the detection of cervical intraepithelial neoplasia [26], and even the support for transcatheter aortic valve implantation [27]. ” (Bouaud J.;Koutkias V. Müller H., 2014)

Available from: 

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4587053/

Retrospective checking of compliance with practice guidelines for acute stroke care: a novel experiment using openEHR’s Guideline Definition Language. BMC Med Inform Decis Mak. 2014 May 10;14:39. doi: 10.1186/1472-6947-14-39

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Anani N, Chen R, Prazeres Moreira T, Koch S.

“Our aim was to explore in an experimental setting the practicability of GDL and its underlying archetype formalism. A further aim was to report on the artefacts produced by this new technological approach in this particular experiment. We modelled and automatically executed compliance checking rules from clinical practice guidelines for acute stroke care. Shareable guideline knowledge for use in automated retrospective checking of guideline compliance may be achievable using GDL. Whether the same GDL rules can be used for at-the-point-of-care CDS remains unknown.” (Anani N, Chen R, Prazeres Moreira T, Koch S, 2014)

Available from: 

http://bmcmedinformdecismak.biomedcentral.com/articles/10.1186/1472-6947-14-39

Early Experiences from a guideline-based computerized clinical decision support for stroke prevention in atrial fibrillation. Stud Health Technol Inform. 2013;192:244-7.

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Chen R, Valladares C, Corbal I, Anani N, Koch S.

“The compliance checking shows the cardiologist group has substantially higher percentage of compliant treatment compared with that of the general population group. Based on this important finding, we are now implementing at-point-of-care clinical decision support reusing the same computerized guideline knowledge in GDL format in order to increase the guideline adherence of the treatment.” (Chen R, Valladares C, Corbal I, Anani N, Koch S. , 2013)

Available from: 

https://www.ncbi.nlm.nih.gov/pubmed/23920553

OpenEHR-based representation of guideline compliance data through the example of stroke clinical practice guidelines. Studies in Health Technology and Informatics. 2012;180:487-491.

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Anani N, Chen R, Prazeres Moreira T, Koch S.

“We conclude that openEHR-based guideline and compliance data representations may be a promising first step in building future decision support applications that are well connected to the electronic health record, can be useful in locating discrepancies between different sets of guidelines within the same care context and provide a helpful tool for driving the archetype authoring and review process.” (Anani N, Prazeres T, Koch S., 2012)

Available from:

https://www.ncbi.nlm.nih.gov/pubmed/22874238