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

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:

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

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:

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

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:

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

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:

Integration of Data with Quality Registries using Semantic EHR and CDS Technologies: A case study of the quality registry Senior Alert in Sweden. Master thesis. Karolinska Institutet; 2016

Nielsen O.

“The study showed that these semantic EHR and CDS technologies can be used for the integration of data to registries, where they provide reusable and accurate data to the registry in the format and structure that it requires. The solution presented in this study shows that the quality of data can be improved and that double documentation can be reduced in the context of registration of data to quality registries.”(Nielsen O, 2016)

Available from:

Comparative Analysis of HL7 FHIR and openEHR for Electronic Aggregation, Exchange and Reuse of Patient Data in Acute Care. Master thesis. Karolinska Institutet; 2016

Allwell-Brown E.

“openEHR captures an outstanding level of detail and it delivers on its mandate of defining EHR structure, albeit in a tedious and complicated way. FHIR is lightweight and agile, has better terminology support, is easier to learn, maintain and rapidly deploy either as an interface for data aggregation, exchange and reuse, or as standalone EHR.” (Allwell-Brown E, 2016)

Available from:

Exploring openEHR-based clinical guidelines in acute stroke care and research. Thesis for doctoral degree. Karolinska Institutet; 2016

Anani N.

“Several findings are that i) the Care Entry-Network Model facilitates an intermediate step between narrative guideline text and computer-interpretable guidelines to be deployed in openEHR systems, ii) the Guideline Definition Language is practicable for creating and automatically running openEHR-based computer-interpretable guidelines, where we also provide detailed accounts of our employed GDL technologies, and iii) the Guideline Definition Language combined with real patient data from patient data registries can generate new clinical knowledge, which in our case has benefited stroke carers and researchers working with acute stroke thrombolysis. In conclusion, using our methodology, health care stakeholders would get evidence-based knowledge components in their electronic health records based on shareable, well maintainable information and knowledge models in the form of archetypes and GDL rules respectively. However, our approach still needs to be tested at the point of clinical decision making and compared to other approaches for providing exchangeable computer-interpretable guidelines.”(Anani, N, 2016)

Available from:

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

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 – and data models (e.g., openEHR archetypes, and the related GDL-Guideline Definition Language – ” (Quaglini S. et al, 2015)

Available from:

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.

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:

Design and development of a decision support system for screening of Lynch syndrome using openEHR. Master thesis. Karolinska Institutet; 2015

Flores B.

“OpenEHR and GDL offer the capabilities of developing a CDSS that can model a patient’s screening process and support accurate referral of Lynch Syndrome. The architecture of OpenEHR provides the flexibility of further adapting the system to new requirements and additional features.”(Flores B, 2015)

Available from: