ADAPTIVE CLINICAL PATHWAYS WITH
SEMANTIC WEB RULES
Dimitrios Alexandrou, Fotis Xenikoudakis and Gregoris Mentzas
Information Management Unit, Electrical and Computer Engineering, National Technical University of Athens
9 Iroon Politechniou Street, Athens, Greece
Keywords: Adaptive clinical pathways, semantic web, semantic rules, pathway adaptation, ontology, workflow engine.
Abstract: The increase of treatment quality offered by the healthcare organizations is one of the main challenges of
the modern health informatics. The personalization of treatment presupposes the real-time adaptation of
treatment schemes since the clinical status of the patient and circumstances inside a healthcare organization
constantly change. In this paper we present SEMPATH prototype which aims at providing a solution
concerning the real-time adaptation of healthcare business processes. The prototype consists of a healthcare
process execution engine assisted by a semantic framework for the adaptation. The semantic framework
consists of an ontology enclosing the required knowledge based on which a semantic rule set was created.
During the execution time of the clinical pathways, the system reasons over the rules, the knowledge and
information collected, and provides decisions and recommendations for the next steps of the treatment.
Moreover, the results of the rule-set execution may produce new knowledge objects which are inserted in
the ontology.
1 INTRODUCTION
One of the main challenges of modern healthcare
organizations is to increase the treatment quality. In
order to achieve their goal, they need to utilize
standardized clinical protocols used in many
domains of medicine. Such a protocol contains
detailed medical plans for diagnosis, therapy scheme
and follow-up. Moreover, it encloses the information
required so as to deal with exceptional situations,
which occur during the treatment execution time and
require quick and appropriate modifications of the
treatment of a patient, thus increasing the flexibility
of the treatment processes. One valuable tool to
achieve the above-mentioned objectives is “Clinical
Pathways”.
Clinical pathways can be utilized for the
implementation of medical guidelines in a specific
healthcare environment and decrease undesired
variability of medical practice (Campbell et al.,
1998). In contradiction with the medical guidelines,
clinical pathways enclose multidisciplinary valuable
resources like personnel, education level, medical
equipment availability and other operational and
administrative information. Medical guidelines
require the consensus between medical experts. On
the other hand, clinical pathways require a
consensus between multidisciplinary groups of
hospital personnel taking actions during the
treatment execution. Clinical pathways constitute
treatment process patterns which aim to increase
both the healthcare process quality and the
utilization of resources. Consequently, a clinical
pathway may deviate from a clinical guideline due
to administrative reasons, and a treatment scheme
may deviate from the clinical pathway due to
patient’s symptoms during its execution.
In order to support the execution of treatment
schemes based on clinical pathywas and to relief the
medical personnel, a software system is required
which will handle the healthcare business processes
in an efficient manner (Greiner et al., 2004). Such a
system would be responsible for the observation of
the execution and the current status of the apllied
clinical pathways, offer the characteristic of
automatic recognition of exceptional events and
provide decision support services in order to handle
the exceptions in an efficient and effective way.
Moreover, the software system should be capable to
dynamically adapt the treatment process so as to
control the appropriate modifications.
140
Alexandrou D., Xenikoudakis F. and Mentzas G. (2008).
ADAPTIVE CLINICAL PATHWAYS WITH SEMANTIC WEB RULES.
In Proceedings of the First International Conference on Health Informatics, pages 140-147
Copyright
c
SciTePress
In this paper we propose an approach which
includes a workflow management system combined
with a rule base in order to handle the
abovementioned requirements. The workflow
environment handles the execution of treatment
schemes and the incorporation of user types, data
and peripheral applications. Additionally, the
specific software system needs to support the
dynamic adaptation of clinical pathways in order to
handle the flexibility of treatment schemes (Dadam
et al., 2000), (Miksch et al., 2001). The rule base is
responsible for the handling of the required streams
of knowledge enclosed in the clinical pathways and
is utilized for the detection of exceptional events and
their confrontation.
In this paper we present our software prototype,
SEMPATH, which follows this approach and has all
the required functionality to support adaptive
clinical pathways. SEMPATH performs a rule-based
exception detection with semantic rules (SWRL) and
dynamic clinical pathway adaptation during the
execution time of each pathway.
The rest of the paper is organised as follows.
Section 2 refers to our motivations and related work
performed in the area of our interest. Section 3
overviews the proposed Semantic Approach the
SEMPATH follows, while Section 4 outlines the
SEMPATH conceptual framework and technical
architecture which is being implemented. In section
5 we present our experimental scenario and the
SEMPATH walkthrough. Finally, section 6
concludes the paper combined with our thoughts for
future work.
2 MOTIVATIONS AND RELATED
WORK
At this section we present the motivations, the
related work and our contribution in the area of the
adaptive clinical pathways. The motivations
presented led to the research stream of adaptive
clinical pathways. Moreover, a significant amount of
work has been realized towards the direction of the
optimal handling of the exceptions occurring during
the execution of treatment schemes of a patient.
Finally, our research in the area and the development
of SEMPATH prototype tries to contribute in
specific and focused issues.
2.1 Motivations
The trends in healthcare business processes and their
establishment and utilization in the healthcare
routine are up to now quite mature. Nevertheless,
there are several open issues / challenges that further
motivate our effort (Song et al., 2006):
Clinical Pathways Adaptability: The
traditional clinical pathways are normally
static and lack of dynamicity. Moreover, they
are standard procedures applicable to a patient
taxonomy not addressing the case of each
patient. Moreover, they do not take under
consideration the most current medical,
operational, and financial knowledge (Colaert,
2007).
Maintenance: The implementation of Clinical
Pathways is based on medical guidelines and
additional types of knowledge. The
maintenance of the healthcare business
process suffers from the continuous update,
since both the medical guidelines and the
circumstances inside a healthcare organization
change constantly.
Medical Guidelines Formalization: The
formalization of medical guidelines is being
performed in a specific and per case manner.
Their formalization is required since their
parameters will be able to be processed by an
IT infrastructure that supports their execution.
Clinical Pathways Modelling: The modelling
of Clinical Pathways lacks a formal structure.
Different approaches exist in the area of
modelling. Their interoperation could be of
major importance since the Clinical Pathway
exchange between healthcare organizations
could facilitate the execution of the treatment
schemes utilized.
Real-time information capturing:
Information capturing consists one of the
major factors for success of the treatment
scheme executed for each patient. The lack of
real-time information feed to the clinical
pathway creates a major need, since the
information collected could lead to major
reconfigurations of the executed Clinical
Pathway.
Real-time knowledge recycling: The
knowledge recycling during the execution of a
Clinical Pathway constitutes one of the major
challenges for the area. The knowledge
feedback would be valuable since the
knowledge update is able to redefine the
Clinical Pathway and the model of the
exception rules.
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141
2.2 Related Work – State of the Art
As (Lenz et al., 2006) states, “healthcare processes
require interdisciplinary cooperation and
coordination”. Towards this direction, he divides the
processes inside a healthcare organization into two
categories: the organizational processes and the
medical treatment processes. The organizational
processes are of equal importance to the medical
treatment ones, since they heavily affect their
execution and effectiveness. Moreover, the medical
treatment processes are influenced by the medical
knowledge and the patient information. So, he
introduces the need for WfMS (Workflow
Management System) inside a healthcare
organization so as to handle the intra-organizational
processes. Moreover, the addition of the appropriate
web-services could lead to the inter-organizational
healthcare processes. The abovementioned concerns
led to the implementation of ADEPT system
(
Reichert et al., 2003) which focuses on the healthcare
processes execution. The ADEPT system enables the
execution, monitoring and management of the
healthcare process running inside a healthcare
organization. Moreover, it offers the functionality of
dynamic changes in the predefined healthcare
processes on execution time. The development of
the specific system lasted for some years and
provided valuable information and experience from
its pilot and productive periods (Lenz et al., 2007),
(Blaser et al., 2007).
Additionally, (Colaert, D., 2007) introduces the
term of adaptive clinical pathways and presents the
research work performed inside Agfa Healthcare. He
stresses out that Adaptive Clinical Workflows are
based on a) Medical, b) Practice, c) Clinical and d)
Operational Knowledge. Agfa constitutes one of the
active members of W3C Semantic Web Health Care
and Life Sciences Interest Group (W3C) which
encloses the “Adaptive Healthcare Protocols and
Pathways Task Force” which aims at the utilization
of semantic web technologies in order to enhance
the adaptable clinical protocols and pathways.
(Abidi and Chen, 2006) introduce another IT
platform that enables the adaptivity of clinical
pathways based on a semantic framework.
CAREPLAN system (Abidi and Chen, 2006) tries to
combine heterogeneous healthcare knowledge
sources with the available patient information. The
system reasons over the knowledge and adapts
standard pathways towards personalized healthcare
plans, utilizing the technology of web-services for
the composition of the integrated pathways.
2.3 Our Contribution
Our approach led to the creation of the SEMPATH
software system which enables the adaptation of
clinical pathways in order to serve the
personalization of the treatment plans for each
patient. Our contribution concerning the state-of-the-
art in the specific domain could be summarized in
the following axes:
Real-time adaptation of clinical pathways:
SEMPATH approach is based on continuous
reasoning over the current knowledge so as to
adapt each step of the clinical pathway under
execution.
SWRL Rule Base: SEMPATH encloses a rule-
set created by utilizing SWRL (SWRL)
language in order to integrate the rule-base
with the ontology. The rule-base is able to
create new facts and update the ontology
accordingly, thus creating new knowledge as
each pathway evolves. This feedback
constantly updates the knowledge stored in the
ontology and leads to better results concerning
the adaptation of the pathway.
Establishment of a meta-model for each
clinical pathway: in our approach, we define
a meta-model for each clinical pathway to be
executed. The meta-model encloses atomic
and complex sub-pathways which are fed to
the process execution engine. The integration
of discrete parts and connections results to the
establishment of the meta-model of the
pathway to be executed.
3 THE SEMPATH APPROACH
The SEMPATH approach followed during the
implementation of the software prototype includes
the design and creation of the Adaptive Clinical
Pathway Ontology. The created ontology is utilized
for the implementation of the semantic web rules.
The implemented rules are inserted into the JESS
System to comprise the rule-base in order to be
executed and extract the appropriate facts that
influence the adaptation of the clinical pathways.
3.1 Adaptive Clinical Pathway
Ontology
The Adaptive Clinical Pathway Ontology constitutes
the main infostructure of the semantic layer of the
implemented architecture. The core of the ontology
is based on the ACPP Ontology (ACPP Ontology)
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that is implemented by ACPP Task Force (ACPP
Task Force).
The core of the ontology was further extended
and broadened both in subdomains and existing
concepts and instances. The specific ontology is
divided into four (4) main knowledge streams.
The main stream refers to the representation of
the medical knowledge. It contains the semantics
utilized for the description and structure of the
medical part of the clinical pathway. The specific
concepts describe the medical domain knowledge
that semantically enhances each clinical pathway.
Moreover, the second stream of the ontology
comprises the operational knowledge structure. It
contains the concepts utilized for the description of
the operational issues that arise during the execution
of the clinical pathway and may affect its
evolvement. Each healthcare organization encloses
specific procedures and resources which are
combined in order to offer its services.
Consequently, the operational knowledge is one of
the main elements of a clinical pathway since it
affects its execution and success.
Additionally, the third knowledge stream refers
to the concepts and terms that define the financial
issues that affect the execution of a clinical pathway.
The utilization of a clinical pathway aims at the
optimization of the financial resources required for
the treatment path of a patient. Each healthcare
organization aims at both the reduction of its costs
and the increment of the quality of healthcare
services provided. Consequently, the financial part
of the ontology models the financial resources and
rules utilized during the execution of each clinical
pathway.
Finally, the fourth knowledge stream refers to the
modelling of the clinical pathway itself. It contains
the concepts and terms that describe the building
blocks of the clinical pathway. It is utilized by the
software prototype for the design of the treatment
workflow.
SEMPATH Ontology is available online at:
http://www.imu.iccs.gr/index.php?option=com_cont
ent&task=view&id=206&Itemid=90/sempath_onto.
zip.
3.2 SWRL Rules Modelling
The rules implemented for our prototype refer to the
execution of a clinical pathway, and more
specifically to the exception handling procedure.
The exception management procedure constitutes
one of the every-day routine of healthcare
professionals (Kobayashi et al, 2005), (Tucker et al,
2002). As (Han et al., 2006) states, “an exception,
constitutes an abnormal behaviour from the normal
workflow”. The handling of exceptions occurring
during the execution of a clinical pathway encloses
three major issues: a) exception management
representation, b) implementation and execution of
exception management and c) exception analysis.
Concerning SEMPATH prototype, the rules for
exception management are designed in SWRL
format. SWRL enables the integration of the
modelled rules with the Clinical Pathway Ontology.
The interaction between rules and ontology leads to
new knowledge. An indicative set of implemented
rules for the SEMPATH prototype is presented
below:
Rule-1:
TriageAdmission(?t)
DiagnosedNeurologicalDeficit(?s)
hasTask(?a, ?t)
hasPatient(?a, ?p)
hasPatientState(?p, ?s)
EvaluationForThrombolysisEligibility(?t2)
hasNextTask(?a, ?t2)
Rule-1 describes the following situation: if the
patient is admitted in the healthcare organization and
there is a diagnosis of Neurological Deficit, then the
patient has to be evaluated for Thrombolysis
eligibility.
Rule-2:
EvaluationForThrombolysisEligibility(?t)
ThrombolysisCandidate(?s)
hasTask(?a, ?t)
hasPatient(?a, ?p)
hasPatientState(?p, ?s)
ConfirmationOfAcuteStroke(?t2)
hasNextTask(?a, ?t2)
Rule-2 describes the following situation: if the
Evaluation for Thrombolysis Eligibility is confirmed
and the patient is Thrombolysis Candidate, then the
next examination has to confirm or not the Acute
Stroke episode.
Rule-3:
EvaluationForThrombolysisEligibility(?t)
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143
AcuteCVA(?s)
hasTask(?a, ?t)
hasPatient(?a, ?p)
hasPatientState(?p, ?s)
EmergentHeadCT(?t2)
CBC-PT-PTT_stat(?t3)
hasNextTask(?a, ?t2)
hasNextTask(?a, ?t3)
Rule-3 describes the following situation: if the
Evaluation for Thrombolysis Eligibility is confirmed
and the patient’s state is Acute CVA, then the
patient has to be forwarded to the CT department for
Emergent CT and for CBC-PT-PTT examination.
The above-mentioned and explained SWRL rules
are indicative elements from rule-base which is
utilized by the SEMPATH infostructure. As seen
above, the rules contain classes from the ontology,
both in the antecedent and the consequent parts of
the rules. Any new facts deriving from the rules
execution are being added in the ontology as new
knowledge objects for future utilization.
3.3 Adaptation Methodology
SEMPATH adaptation methodology is based on a
meta-model clinical pathway establishment. Each
clinical pathway to be executed is a meta-model of a
set of atomic and complex sub-processes. The
atomic processes are executable parts of the
healthcare business process forwarded to the
execution engine. The complex processes are sub-
workflows which contain atomic processes and a set
of decisions. The atomic and the complex processes
are interconnected in the meta-model level. Their
connections are based on SWRL rules. Once an
atomic or complex process is executed, the rule-base
is triggered. The knowledge existing inside the
ontology, the current clinical status of the patient
and the rule-set are interoperating in order to select
the next executable part of the clinical pathway.
Thus, the adaptation occurs during each step of the
pathway execution.
During each cycle of execution, the triggering of
the rule-base may result to new knowledge creation
that will be utilized in next steps during the
execution. This fact ensures the constant update of
medical, organizational and operational knowledge
stored inside the ontology and consequently to the
rule-base.
4 SEMPATH PROTOTYPE
The following sections present the conceptual
framework and technical architecture of the software
system prototype that executes the clinical pathways
and performs the required dynamic adaptation.
4.1 Conceptual Framework
As depicted in Figure 1, the conceptual framework
of the SEMPATH system comprises three (3)
distinct architectural layers. The upper layer of the
architecture is called “Semantic Layer” since it
encloses the required semantic infrastructure.
Figure 1: Conceptual Framework.
The core of Semantic Layer is the Adaptive
Clinical Pathway Ontology which encloses the
appropriate knowledge streams required for the
modeling of the clinical pathways, in terms of
structure and content. Moreover, the specific layer
encloses the semantic modeling of the rules that
handle the exceptions inside the clinical pathway
during its execution. These rules are the cornerstone
of the dynamic adaptation performed in the clinical
pathways.
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The second layer constitutes the “Clinical
Pathway Adaptation Layer”. The specific layer
encloses the components required for the adaptation
of the clinical pathway. The rule engine is
responsible for the execution of the semantic rules
concerning the exception handling of the pathway.
Once the result is produced the “Adaptive Clinical
Pathway” manager is the software module that
updates accordingly the structure of the pathway.
Finally, the last layer of our conceptual
framework is the “Clinical Pathway Layer”. It
contains the workflow – part of the clinical pathway.
The execution of the clinical pathway happens inside
a workflow engine since is constitutes a healthcare
business process (Lenz, 2006). A clinical pathway
repository contains a set of available clinical
pathways so as to select the most appropriate for
each patient.
4.2 Technical Architecture
The technical architecture of the implemented
prototype is presented in Figure 2. The Adaptive
Clinical Pathway Prototype technical architecture
comprises three (3) major components. These three
major components are described in full detail in the
following sections:
a. Semantic Infostructure: The core of Semantic
Infostructure component is the Clinical Pathway
Ontology. As depicted in the following diagram, the
ontology is implemented in OWL (OWL) format.
The ontology encloses the abovementioned streams
of knowledge to be utilized for (1) the creation of
rules, (2) the modelling of Clinical Pathways and (3)
the recycling of knowledge through the dynamic
production of facts by the rule engine.
The Protégé API has been utilized concerning
the implementation and maintenance of the specific
ontology. Moreover, the SWRL designer of the
semantic rules is a Protégé Plugin (SWRLTab)
which enhances the integration between the
Ontology and SWRL rules. Consequently, each rule
created by the specific plugin is consistent in
semantic terms, since the semantics required come
directly from the ontology.
b. Rule Execution Environment: This component
handles the maintenance of the semantic rules as
well as the Rule Engine implemented. The SWRL
rules implemented with the Protégé Plugin are stored
as a SWRL repository. Once the system is triggered,
the appropriate rule set is selected. The SWRL rules
are initially converted into JESS rules in order to be
executed by the rule engine. Once the semantic rules
are executed, the result of the rule engine is
produced in XML format.
The specific XML file is a custom structure
which is utilized by the prototype so as to proceed to
the adaptation of the clinical pathway.
Figure 2: Technical Architecture.
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145
Moreover, once the rule set is executed, despite
the production of the XML result, a feedback
message is generated which contains new facts and
conclusions that update accordingly the knowledge
stored inside the ontology.
c. Clinical Pathway Execution Environment:
Finally, the last technical component of the
prototype architecture is the Execution Environment.
The core of the specific component is the workflow
execution engine which in our case is ActiveBPEL
workflow environment. The interface between the
workflow engine and the rest of the components is
the Clinical Pathway Manager. Firstly, the specific
component triggers the system once an exception
occurs during the execution of the pathway. The
message produced is forwarded to the Rule Engine
in order to run the complete rule-set for the pathway
and produce the result for the adaptation. Moreover,
the Clinical Pathway Manager interoperates with the
Result Analyser which is responsible for the
processing of the result structure.
The SEMPATH Prototype Software that we have
developed can be found here:
http://www.imu.iccs.gr/index.php?option=com_cont
ent&task=view&id=206&Itemid=90/sempath.zip.
4.3 Experimental Scenario
According to the real-life scenario, a patient
confronts a health problem and decides to be
admitted to a healthcare organization for treatment.
Once the admission is performed, an initial set of
medical examinations is decided to be performed.
The result set of the initial examinations provides
valuable information for the clinical status of the
patient which leads to the decision concerning the
selection of the appropriate clinical pathway to be
executed. The execution of the treatment scheme
produces exceptions which are handled on real-time
basis by the implemented software prototype.
More specifically, once the patient is admitted to
the healthcare organization, its IT infrastructure
should become aware of the data accompanying the
specific patient. So, an initial data entry for the
medical record dataset is performed. This procedure
is performed either manually or automatically if the
patient’s medical record is received from another
healthcare organization.
Once the clinical status of the patient is set,
SEMPATH proposes an initial set of examinations
to be performed. Afterwards, the result set of the test
is inserted into the medical record of the patient. The
system proposes an appropriate clinical pathway
according to the diagnosis. So, the execution of the
treatment scheme begins, under the constant
inspection of SEMPATH prototype. Once an
exception occurs, SEMPATH receives the exception
information, executes the required rule-set and
proposes the next ”step” of the treatment scheme.
The “step” derives from the following two
categories:
Atomic process: a single step procedure,
executable by the process execution engine.
Complex process: a multiple step procedure. It
is a set of atomic processes without decision making.
A complex process may contain parallel execution
paths leading to a unified result.
The above-mentioned procedure is repeated during
the execution of the treatment scheme of the patient.
This way, the personalization of treatment for each
patient is highly ensured, increasing the possibilities
for the most suitable treatment.
After the implementation of the SEMPATH
prototype, we are now in close cooperation with a
University Hospital (LAIKO Hospital). We have
modelled five (5) clinical pathways, defined the
corresponding rules and we are in the process of
real-life scenario execution.
5 CONCLUSIONS & FUTURE
WORK
The existing practices and work performed in the
area of clinical pathways has led to significant
results. Nevertheless, clinical pathways are static
procedures based on medical guidelines and
organizational and operational knowledge. The
current trend focuses on the adaptation of these
static structures in case of exception occurrence.
The introduction of semantic technology
provides further opportunities for clinical pathway
adaptation. Semantics enable the representation of
all required types of knowledge by the utilization of
the corresponding ontologies. A significant amount
of work has been done in the area of ontology
creation. The developed ontologies cover several
streams of medical knowledge.
However, this knowledge has to be combined
with rules in order to handle the pathway exceptions.
In this paper we presented SEMPATH prototype, a
software platform based on semantics. SEMPATH
introduces the creation of semantic rules in SWRL
format which provide the basis for the rule-engine
that handles the pathway exceptions. SWRL rules
were created by the utilization of the SEMPATH
ontology. The execution of the semantic rules
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provides new knowledge objects that can be added
to the existing ontology. Consequently, the
knowledge enclosed in SEMPATH prototype is
constantly updated and maintained by its routine
operation.
Our intensions for further work can be presented
in a three-fold structure:
Semantics Infrastructure: our main aim
concerning the evolution of SEMPATH semantics
infrastructure is to proceed with the ontology
enhancement. The enhancement will focus on
organizational issues modelling and medical
knowledge representation. Furthermore, our
intention is to integrate existing medical ontologies
so as to enrich our ontology model.
Pathway Modelling: in the field of pathway
modelling we plan to concentrate on simultaneous
execution activities management and on providing
different views of the pathway for each type of user.
Moreover, our intention is to add semantic
information in activities that will establish a priority
weight model in order to perform more intelligent
resource and activity management.
System evaluation and usability: since the
SEMPATH prototype is finalized and functional, we
intend to perform real-life stress tests concerning its
performance inside a healthcare organization. A
real-life test will provide valuable results concerning
the usability of the system, the performance and
further enhancement of the implemented ontology
and the further enhancement of the semantic rule-
set.
ACKNOWLEDGEMENTS
This work has been partially funded by the European
Commission with the IST 027065 contract (RIDE: A
Roadmap for Interoperability of e-Health Systems in
Support of COM 356 with Special Emphasis on
Semantic Interoperability).
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