Towards Improving Modeling and Simulation of Clinical Pathways:
Lessons Learned and Future Insights
Mahmoud Elbattah and Owen Molloy
National University of Ireland Galway, Galway, Ireland
Keywords: Clinical Pathways, Conceptual Modeling, Simulation.
Abstract: Clinical pathways (CPs) have been increasingly recognised as an instrumental evidence-based artifact that
can support clinical decision making and care planning. However, research focusing on modeling and
simulation of CPs is still sparse, despite significant individual endeavours. Initially, the paper conducts a
systematic literature review with the aim of thoroughly inspecting the state-of-the-art in literature. Through
the review, potential improvements are investigated with regard to the application of modeling and simulation
within CPs. In view of that, we identify four thematic areas that emphasise how research in this space can be
further developed. Specifically, we propose the following directions: i) Development of a conceptual
reference model of CPs, ii) Adoption of a multi-perspective modeling approach that can integrate clinical,
operational, financial and demographic information of CPs, iii) Development of a generic semantic-based
model of CPs, and iv) Adoption of Linked Data concepts.
1 INTRODUCTION
Healthcare services are delivered in complex
environments involving interactions among many
care providers and stakeholders. In this regard,
numerous studies (Lowery et al., 1994; Lowery et al.,
1996; Harper et al., 2004; Brailsford et al., 2005,
Eldabi et al., 2009) aimed at identifying the particular
profile of healthcare problems and the way modeling
and simulation studies should approach them.
However, compared to non-healthcare sectors, there
is still an obvious shortcoming with respect to the
gains of simulation modeling for healthcare in
general, and for CPs in particular. A CP was defined
as a management plan that displays goals for patients
and provides the sequence and timing of actions
necessary to achieve these goals with optimal
efficiency (Pearson et al., 1995).The significance of
CPs substantially lies in the potential to standardise
the flow of information, processes and patients
through well-designed care plans (Every et al., 2000;
Renholm et al., 2002; De Bleser et al., 2006).
In this respect, this paper seeks to identify future
directions aiming to bridge some of the gaps exposed
in the literature. The proposed directions were
developed in accordance with an exhaustive
systematic review of the literature that addressed
modeling and simulation of CPs. In general, we argue
that there is an extensive need to embrace different
methodological approaches utilising CPs towards:
i) Developing new or improved models of patient-
centred care schemes, and ii) Building data-driven
decision models that can take advantage of the
massive amounts of clinical data. In particular, four
thematic arguments are discussed calling for
expanded attention from future studies towards
improving the practice of CPs modeling and
simulation.
Further, on the premise that healthcare can avail
of potentially applicable approaches or methods from
other matured business-oriented sectors, affirmative
exemplars from supply chains are invoked in line
with some of the proposed directions. We believe that
CPs and supply chains share the same problematic
characteristics of being highly dynamic, context-
sensitive, event-driven, knowledge-intensive,
distributed executed, and having multitude of
stakeholders.
2 REVIEW METHODOLOGY
The preliminary stage of the study adhered to a
systematic literature review using methods informed
by (Booth et al., 2011). The review endeavoured to
comprehensively include state-of-the-art approaches
and methods adopted for modeling and simulation of
CPs. To the best knowledge of the authors, existing
508
Elbattah M. and Molloy O..
Towards Improving Modeling and Simulation of Clinical Pathways: Lessons Learned and Future Insights.
DOI: 10.5220/0005568405080514
In Proceedings of the 5th International Conference on Simulation and Modeling Methodologies, Technologies and Applications (SIMULTECH-2015),
pages 508-514
ISBN: 978-989-758-120-5
Copyright
c
2015 SCITEPRESS (Science and Technology Publications, Lda.)
literature lacks a similar systematic review in this
context, which was an additional motivation.
2.1 Search Strategy
Initially, we posed the five investigative questions
presented in Table 1 in order to focus the review
process. However, the review process was
significantly challenged by the multiplicity of terms
associated with CPs. Acknowledged by many studies
(Every et al., 2000; Renholm et al., 2002; De Bleser
et al., 2006; Pearson et al., 1995; Vanhaecht et al.,
2010), CPs are also termed as “Integrated Care
Pathways”, “Care Pathways”, “Critical Pathways”,
and “Care Maps”. Therefore, all those terms had to be
incorporated within the search keywords in order to
ensure comprehensiveness. Specifically, the search
was conducted using five keywords as follows: i)
Clinical pathways modeling, ii) Critical pathways
modeling, iii) Care maps modeling, iv) Integrated
care pathways modelling, and v) Care pathways
modeling. The search process targeted four major
digital libraries, which also index the proceedings of
vital conferences (e.g. Winter Simulation Conf.),
including: i) IEEE Xplore, ii) ACM Digital Library,
iii) ScienceDirect – Elsevier, and iv) SpringerLink.
Table 1: Investigative Questions and Motivations.
Question Motivation
Q1: What are the modeling
methodologies used to
conceptually model CPs?
Identify state-of-the-art
modeling methodologies
adopted for CPs.
Q2: Are there formal standards
for modeling CPs?
Identify whether there are well-
established standards to formall
y
depict CPs models.
Q3: What types of semantic-
based models were developed
for CPs?
Identify methods used to
conceptualise the knowledge
within CPs.
Q4: Is there a form of
standardised ontology develope
d
for CPs?
Identify whether there are
common ontology models used
to formalise CPs.
Q5: What are the implications o
f
CPs modeling approaches for
building simulation models?
Identify how the conceptual
models of CPs contributed to
produce simulation studies.
2.2 Stages of Review Process
The review process was accomplished through four
stages. Stage (1) included searching digital libraries
for potential relevant studies using the afore-
mentioned search keywords. Stage (2) excluded
irrelevant studies based on titles. Stage (3) excluded
irrelevant studies based on abstracts, including
studies that directly addressed modeling and
simulation of CPs. Stage (4) involved inclusion and
critical appraisal of the significant studies. The stages
of the review process are sketched in Figure 1, where
the number of included papers is identified at each
stage.
Figure 1: Stages of the review process.
3 PROPOSED DIRECTIONS
3.1 Development of a Conceptual
Reference Model
The role of conceptual modeling was constantly
recognised to be pivotal in simulation studies.
According to (Shannon et al., 1976), simulation
modeling is both art and science with conceptual
modeling lying more at the artistic end. Furthermore,
development of conceptual models is a necessary
phase to achieve abstraction and simplification prior
to simulation.
Nevertheless, literature obviously lacks a formal
modeling structure of CPs, acknowledged by (Yang
et al., 2012; Gupta et al., 2013; Yao et al., 2013).
Based on reviewed studies (Michalowski et al., 2006;
Zhang et al., 2008.; Li et al., 2008; Du et al., 2008;
Du et al., 2009; Alexandrou et al., 2009; Zhen et al.,
2009; Ye et al., 2009; Ozcan et al., 2011; Abidi et al.,
2012; Hashemian et al., 2012; Yao et al., 2013;
Combi et al., 2014; Braun et al., 2014), diverse
approaches exist in the area of conceptual modeling
with respect to CPs. Although those studies
contributed to investigate CPs modeling regarding
different perspectives, they are best described as case
studies, apart from few studies (Michalowski et al.,
2006; Zhang et al., 2008). Hence, we argue that
literature clearly lacks a standard formalism for the
representation of CPs in general.
In addition, there is a pronounced multiplicity of
concepts, terms and relationships within developed
CPs models, evident by the plethora of adopted
modeling methodologies. Specifically, there is no
TowardsImprovingModelingandSimulationofClinicalPathways:LessonsLearnedandFutureInsights
509
single modeling methodology or framework that
thoroughly covered all of the following issues
necessary for modeling CPs:
Comprehensively consider the various activities
of CPs including assessments, treatments, tests,
medications, hygiene and education.
Explicitly provide structured descriptions of pre-
operative, operative and post-operative activities
through treatment courses.
Enable to structure interventions with different
types of simple, atomic or composite processes or
activities.
Provide performance metrics/indicators that allow
analysis of time and resources within CPs.
In this respect, we draw attention to the need to
establish a common conceptual modeling method-
logy through the development of a reference model
for CPs. A reference model can yield many benefits
including: i) Standardise the abstraction of CPs via
progressively building consensus over concepts,
terms and process relationships of CPs, ii) Serve as a
robust base for developing ontologies or sematic-
based models, iii) Enable flexible dissemination of
good practice within stakeholders on an institutional
level, endorsed as one of the key ingredients for
successful adoption of simulation techniques (Terry,
2005), and iv) Facilitate stakeholders involvement as
a part of conceptual modelling process, recognised to
increase potentials for a successful simulation
implementation (Lehaney et al., 1995; Tako et al.,
2010).
However, development of a reference model
should take into account that healthcare-oriented
problems are better approached by forms of
resolutions and consensus (Maliapen et al., 2010). In
other words, a standard model should strike a
reasonable balance between modeling accuracy and
consensus. More importantly, a reference model can
be useful only if sustainably developed and
maintained by an active community, such as the
European Pathway Association (EPA) (e-p-a.org) for
example.
In this context, we invoke a related exemplar from
supply chains. The presented exemplar is the SCOR
(Supply Chain Operations Reference) model
(Bolstorff, 2007), regarded as one of the most widely
accepted and shared reference models for supply
chains. The SCOR model also has the advantage of
being continuously developed and maintained by the
Supply Chain Council (SCC) (apics.org/sites/apics-
supply-chain-council).The SCOR model contributed
to found a basis for building either abstract or
simulation models for supply chains in considerable
studies (Hermann et al., 2003; Haung et al., 2005;
Persson et al., 2009).
3.2 Multi-perspective Modeling
”Only by developing a well-rounded picture of the
clinical, financial and patient characteristics, it can
be possible to proactively address issues for clinical
outcomes, reducing costs, and patient satisfaction”,
emphasised by (Pol et al., 2000).
In this regard, CPs should be effectively endorsed,
whereas they were originally introduced to
comprehensively capture clinical and operational
practice through care schemes (Pearson et al., 1995;
Campbell et al., 1998; Zander, 2002). Furthermore,
the pathway-attributable economic gains were
delineated in numerous studies (Huber et al., 1998;
Pritts et al., 1999; Pitt et al., 1999; Porter et al., 2000;
Vanounou et al., 2007). For instance, (Vanounou et
al., 2007) observed an overall cost savings of $5,542
per patient using deviation-based cost modeling that
compared a pathway group of patients to another non-
pathway group. Moreover, another economic impact
of CPs was highlighted in promoting and
complementing the implementation of Diagnostic
Related Groups (DRG’s) (Collier 1997; Maliapen
2010). Consequently, CPs can and should be used as
a pro-active method to support healthcare decision
making.
However, in order to adequately depict
operational and clinical features of CPs, a multi-
perspective modeling approach should be embraced.
Particularly, CPs models should incorporate clinical,
operational, financial and demographic information.
The multi-perspective modeling of CPs can facilitate
integration within Clinical Decision Support System
(CDSS). The integration of CPs into CDSS was
considered of significant importance (Fieschi et al.,
2003; Karsh, 2009; Kawamoto et al., 2005; Wears et
al., 2005) for delivering evidence-based recommen-
dations by examining behaviour of patients and
identifying service bottlenecks.
We argue that the literature lags behind taking
advantage of integrating CPs within CDSS due to
lack of a multi-perspective view. Obviously, little
research (Cole et al., 1999; Yao et al., 2013) aimed at
modeling CPs on that basis. For instance, (Cole et
al.1999) developed a framework that considered CPs
of chronic obstructive pulmonary disease (COPD)
patients in UK. The framework incorporated CPs to
model probability of progression to multiple
readmissions, as a way to help healthcare providers in
the management of care. While another (Yao et al.,
2013) proposed a data-driven approach for decision
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Applications
510
making to improve customisation of CPs. The
methodology applied semantic analysis and
reasoning to historical clinical data from the Navy
General Hospital in Beijing. Generally, the absence
of a multi-perspective modeling approach hampers to
conduct a robust analysis of raw healthcare data in
order to measure outcomes, cost and effectiveness of
care services.
3.3 Generic Semantic-based Modeling
It has become imperative to realise CPs-aware
healthcare systems involving the knowledge within
CPs as a centric component. In accordance with that,
the formalisation of CPs knowledge is inevitable to
attain knowledge sharing and interoperability among
heterogeneous stakeholders.
Based on literature, numerous studies (Abidi,
2009; Yang et al., 2012; Yao et al., 2013) embraced
ontology in order to develop semantic-based models
of CPs, as ontology is a formal explicit specification
of a shared conceptualization (Studer et al., 1998).
For instance, study (Daniyal et al., 2010) presented a
framework that formalised CPs using ontologies of
medical domain knowledge and workflow model,
separately. The medical domain knowledge was
captured as RDFS/OWL ontologies, while the
workflow model was described as an instantiation of
CPWMO, which is an OWL-based ontology for UML
activity diagrams. However, the framework lost sight
of the temporal relationships and variance-related
representations underlying CPs. Another important
study (Yao et al., 2013) proposed a novel framework,
referred as CONFlexFlow. The framework proposed
an integrated ontology model to capture contextual
knowledge and clinical guidelines using OWL and
SWRL rules. Additionally, adaptable clinical
processes were performed using Business Process
Execution Language (BPEL).
However, we argue that apart from very few
studies, such as (Yao et al., 2013), literature seldom
laid emphasis on developing a generic semantic
formalization of CPs. On the contrary, the produced
semantic models were mainly developed with regard
to disease-specific care plans or case studies.
Accordingly, the low-level conceptualisation of CPs
did not help to reach a semantic model that can
capture knowledge within CPs in a generic fashion.
Furthermore, semantic-based models should be
able to represent CPs in terms of: i) Common
concepts and terms of the medical domain, ii)
Structural and temporal relationships within
processes/activities, iii) Variance-related
representation, and iv) Contextual data that
characterise a specific clinical process or activity.
Literature endorsed those issues relatively
individually, and we could not identify a single
framework enabling all of them, to the best
knowledge of the authors.
3.4 Adoption of Linked Data Concepts
Healthcare-oriented problems have been always
characterised by the dilemma of process multi-
ownership and plurality of stakeholders, and CPs are
no exception. Generally, management of a patient’s
health involves dealing with a number of inter-related
CPs. Although a single CP can address a specific
clinical problem, it can be inter-dependent on
progress of other CPs.
Furthermore, the presence of “comorbidity”
through treatment schemes is an additional challenge
for CPs modeling. The term comorbidity refers to the
existence of medical conditions that concurrently co-
occur with a primary condition in the same patient
(Feinstein et al., 1970). For instance, Chronic Heart
Failure (CHF) is a common chronic condition that is
often associated with comorbidities such as Atrial
Fibrillation (AF), diabetes, chronic lung disease and
stroke (Abidi et al., 2012). Undoubtedly, the
complexity of CPs models can directly increase due
to the necessity of aligning activities/processes of
multiple disease-specific CPs, while ensuring clinical
suitability and patient safety.
However, the impacts of multiple CPs and
comorbidities have been slightly endorsed in
literature. Only studies (Abidi, 2009; Abidi et al.,
2012) considered the existence of comorbidities
within CPs. Specifically, (Abidi, 2009) presented a
framework for computerisation and merging of CPs
for comorbidities to provide point of care decision
support. The framework provided integration of
multiple CPs for comorbid diseases to realise a single
patient-specific trajectory.
In view of that, we propose the adoption of a
Linked Data approach in order to address the
challenges of multiple inter-related CPs. Generally,
Linked Data refers to a set of best practices for
publishing and connecting structured data on the Web
(Bizer et al., 2009). However, we see big chances for
CPs to avail of Linked Data practices. We argue that
knowledge within CPs can be best conceptually
conceived as Linked Data models. Particularly, the
network-based and context-intensive characteristics
of CPs information make it feasible to take advantage
of the Linked Data concepts and principles. In Figure
2, we conceive the knowledge stack of CPs models as
should be evolving towards Linked Data representa-
TowardsImprovingModelingandSimulationofClinicalPathways:LessonsLearnedandFutureInsights
511
tion.
Figure 2: Knowledge stack of CP Models.
We expect the following gains by embracing Linked
Data concepts:
Realising conceptual amalgamation of knowledge
within multiple disease-specific CPs towards a
full-scale vision of a patient’s health.
Having the inter-related information of CPs in a
Linked Data form can compose a significant
powerful source of recommendations for clinical
decision making.
Storing CPs information as Linked Data can
considerably facilitate diagrammatic
representations of CPs.
Enabling potential usage of CPs knowledge in the
Open Data cloud (LOD).
Once more, we invoke an affirmative exemplar from
supply chains. A recent Study (Robak et al., 2013)
analysed the capabilities of using Linked Data
principles in business process management within
supply chains to tackle problems of information
interchange between independently designed data
systems. The study expected that the application of
Linked Data can substantially contribute to: i) Data
integration between diverse formats from the network
participants ii) Support the automated extraction of
the information.
4 CONCLUSIONS
The paper aims to convey considerations in relation
to improving the modeling and simulation of clinical
pathways (CPs). We formulate our view based on
observations and findings stemming from a
systematic literature review. A clear finding of the
review is that there is a need to establish a common
research agenda for modeling and simulation of CPs,
and for future studies to pay particular attention to fit
their research methods to the state of prior work.
Through this paper, we draw from literature a
summary of future directions as follows:
Development of a conceptual reference model for
CPs.
Adoption of a multi-perspective modeling
approach that can integrate clinical, operational,
financial and demographic dimensions of CPs.
Development of a generic semantic-based
modeling that can realise higher semantic
abstraction of CPs.
Adoption of Linked Data concepts and principles.
The paper discusses the above-mentioned directions,
and how they can considerably boost the integration
of CPs within the Clinical Decision Support System
(CDSS) in order to yield improved quality and lower
costs of healthcare services.
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