M.D. Lytras et al. (Eds.): WSKS 2008, LNAI 5288, pp. 79–87, 2008.
© Springer-Verlag Berlin Heidelberg 2008
Combining OpenEHR Archetype Definitions with SWRL
Rules – A Translation Approach
Leonardo Lezcano1, Miguel-Angel Sicilia1, and Pablo Serrano-Balazote2
1
Information Engineering Research Unit
Computer Science Dept., University of Alcalá
Ctra. Barcelona km. 33.6 – 28871 Alcalá de Henares (Madrid), Spain
{leonardo.lezcano,msicilia}@uah.es
2
Medical Director, Fuenlabrada Hospital
Cº del Molino, nº2, 28942, Fuenlabrada, Madrid, Spain
pserrano.hflr@salud.madrid.org
Abstract. The interoperability of electronic healthcare information systems is
critical for a more effective healthcare management. Several specifications and
standards have been created for facilitating such interoperability at different
levels. Among them, the OpenEHR initiative emphasizes the sharing of flexible
specifications of healthcare information pieces in the form of archetypes. How-
ever, the OpenEHR ADL language does not provide support for rules and infer-
ence which are important pieces of clinical knowledge. This paper reports on an
approach to convert ADL definitions to OWL and then attach rules to the se-
mantic version of the archetypes. This allows for an automated means to reuse
knowledge expressed in the form of rules which is also flexible and follows the
same philosophy of sharing archetypes.
Keywords: Electronic healthcare records, clinical archetypes, ontologies,
OWL, SWRL.
1 Introduction
Clinical practice can be represented as an iterative, care delivery process that starts
with observations of the status of the patient. Such observations lead to informed
opinions on the part of a health care professional, including assessment of the current
situation, goals for a future situation and plans for achieving the goals. Then those
plans become into detailed instructions for clinical practice that eventually trigger the
appropriate actions. At this stage, we may need to repeat the whole iteration until the
problem is solved (Elstein et al., 1987). These four kinds of information are the
breakpoints where communication between independent systems is frequently lost
because of data ambiguity and incompatibility. Several specifications and standards
have been created for facilitating such interoperability at different levels. Among
them, the OpenEHR1 model proposes their modular definition in the form of
archetypes that restrict their format and describe their possible values, as Qamar and
Rector (2007) explained. Observation concepts like blood pressure, evaluations like
pregnancy, and instructions like intravenous fluid administration are quite known

1
http://www.openehr.org/

80 L. Lezcano, M.-A. Sicilia, and P. Serrano-Balazote
clinical statements that have already been specified as archetypes. Archetypes are
mainly targeted to data interoperability among heterogeneous systems.
The OpenEHR Archetype Definition Language (ADL), provides an open con-
straint-based data interchange model. However, it does support neither formal rules
nor any kind of specifications for automated inference.
This paper reports on an approach to combine ontology and rule languages with ar-
chetype definitions as a way to seamlessly integrate rules and reasoning in open,
modular clinical information models. Concretely, ADL archetypes are translated to
the Web Ontology Language (OWL2) and rules expressed in SWRL can be attached
to specific concepts in the archetype definition. By merging SWRL rules with OWL
ontologies, parts of the decision making process can be specified formally and exe-
cuted automatically. SWRL is a W3C submission developed to improve semantic
limitations of OWL which is already a W3C recommendation. In combination, they
add considerable expressive power to the Semantic Web.
The rest of this paper is structured as follows. Section 2 describes the approach to
translate ADL archetypes to OWL. Then, Section 3 describes how clinical data can be
fetched into the ontology created. The paper continues with Section 4, where the
process of using SWRL rules to obtain inferred alerts is elucidated. Section 5 finishes
the article with a conclusions and further work explanation.
2 Translating ADL to OWL
Bicer et al. (2005) described an approach in which archetypes are translated to OWL
in order to achieve interoperability of Web Service messages exchanged in the health
care domain. The approach presented here is based on similar translation principles.
Our point of departure has been the mapping of the OpenEHR Reference Model
(RM)3 which defines a logical EHR information architecture for the interoperability
of EHR compatible systems. The RM ontology contains classes whose instances rep-
resent neither constraints nor archetypes but samples of real data.
That mapping was developed by Román et al. (2006) according to openEHR speci-
fications. Maps are split into five ontologies which are: DataTypes, DataStructures,
Demographic Model, Common and EHR Information Model. They have been defined
using the Protégé-OWL editor.
The translation merges an OpenEHR archetype definition with abovementioned on-
tologies to create a new OWL file4 that reuses them as parents of new (child) concepts.
Archetype definitions start with an Entry subtype like EVALUATION, INSTRUC-
TION, ACTION or OBSERVATION. Essentially, an archetype restricts the instances of
such categories, so a main translation principle is having those Entry categories as
classes and each archetype definition becoming a subclass depending on the subtype.
From now on this section will take as example the translation process of the In-
travascular Pressure archetype5. It’s an OBSERVATION to get the pressure in a

2
http://www.w3.org/TR/owl-guide/
3
http://www.openehr.org/releases/1.0.1/architecture/overview.pdf
4
The code of the translator is available under open source license at
http://code.google.com/p/ehr2ont/
5
http://www.openehr.org/svn/knowledge/archetypes/dev/html/en/openEHR-EHR-OBSERVA
TION.intravascular_pressure.v1.html