DEVELOPMENT OF A FRAMEWORK MATURITY MODEL
FOR THE CONTINUED QUALITY IMPROVEMENT
OF A LOCALLY CUSTOMISED CLINICAL INFORMATION
SYSTEM USED IN CRITICAL CARE MEDICINE
Frank Kirrane
1
, Anne Mulvey
2
1
Department of Medical Physics and Bioengineering, Galway University Hospitals, Newcastle Road, Galway, Ireland
2
Department of Critical Care, Galway University Hospitals, Newcastle Road, Galway, Ireland
Michael Campion
J. E. Cairnes School of Business & Economics, College of Business, Public Policy and Law
National University of Ireland, Galway, Ireland
Keywords: Clinical Information System, Maturity model, Continuous Quality Improvement, Critical care, IT success.
Abstract: This study examines the development of a maturity model (MM) to help determine and monitor perceived
improvement areas that would support the ongoing development of a locally customised hospital critical
care Clinical Information System (CIS). The model arose from qualitative data collected from a critical care
service in a large teaching hospital. The method involved a first principles examination of the priorities of a
critical care service through a textual analysis of the documents considered by the hospital to underpin the
strategic, professional and operational priorities of the service. These priorities form the dimensions of a
MM, where a series of interviews with staff examine how the CIS can facilitate improvement along each
dimension. The MM developed consists of seven dimensions, each illustrated along a percentage scale of
increasing sophistication. This model is piloted in the critical care department which has been using a CIS
for over four years. Results show that the method proposed is suitable for the development of a CIS MM.
The results of the pilot study highlight different individual perceptions on the current level of CIS maturity.
The MM is also demonstrated as a tool to assess current performance, and guide ongoing CIS customisation
effort.
1 INTRODUCTION
The Galway University Hospital (GUH) is a
university teaching hospital 545-bed capacity and
tertiary referral centre for the western seaboard of
Ireland.
A core component of any acute hospital, and
wider health system, is the critical care service. At
GUH, the critical care service is divided into an 18
bed ICU (Intensive care unit), where the highest
level of care is given to the sickest patients, and a 16
bed HDU (High Dependency Units), where an
intermediate level of care is provided for those who
are not well enough to go back to general wards.
The critical care service at GUH is a tertiary
referral centre for the west of Ireland. In 2008 there
were over 1300 admissions to the service.
There are approximately 200 practitioners
working in, or who provide clinical support to the
critical care units. There are at least 40 on duty at
any one time. These practitioners include consultant
intensivists/anaesthetists, consultant surgeons,
specialist medical and surgical registrars, clinical
nurse managers and specialists, critical care staff
nurses, clinical pharmacists, dieticians,
physiotherapists, occupational therapists,
microbiologists, and range of referring medical
teams, along with technical and scientific support
staff.
286
Kirrane F., Mulvey A. and Campion M..
DEVELOPMENT OF A FRAMEWORK MATURITY MODEL FOR THE CONTINUED QUALITY IMPROVEMENT OF A LOCALLY CUSTOMISED
CLINICAL INFORMATION SYSTEM USED IN CRITICAL CARE MEDICINE.
DOI: 10.5220/0003163902860294
In Proceedings of the International Conference on Health Informatics (HEALTHINF-2011), pages 286-294
ISBN: 978-989-8425-34-8
Copyright
c
 2011 SCITEPRESS (Science and Technology Publications, Lda.)

During the stay of a critically ill patient in a
critical care area, approximately 1500-2000 data
items (medical notes, physiological signals,
parameters, test results, medical orders) are
documented and derived daily. Effective patient care
may be limited by the difficulty in managing this
large amount of data and contributes to an increased
risk to the patient. Improving the workflow and
presentation of information can lead to
improvements in outcome in critical care areas
(Breslow and Stone, 2005; Scales, 2004).
The traditional paper based critical care medical
record, recognised as the most complex and
expansive in acute care, is no longer sustainable as
an adequate means to manage information (Frassica,
2004).
Information Technology, such as Clinical
Information Systems (CIS) solutions exist so as to
offer greater potential to enhance the quality and
safety of patient care, and increase provider
effectiveness. A critical care CIS was first defined
by Morris (1998) as a means to integrate clinical
information at the point-of-care. A CIS allows the
capture of the entire patient generated clinical and
physiological data, and presents it in a form that
makes it available as useful information. The real
power of the CIS, which facilitates real patient
benefits, is that it can become a clinical decision
support tool that supports evidence based practice
(Bates and Gawande, 2003; Crane and Raymond,
2003).
Galway University Hospital (GUH) undertook
the procurement and implementation of a Clinical
Information System (CIS) for these reasons. The
Critical Care service at GUH is at the forefront of
medical technology, and implemented a CIS to 18
bed critical care complex March 2005. The CIS was
expanded by an additional 20 beds of the new
Cardiothoracic surgery service in September 2007.
The CIS purchased by GUH is a commercially
available system, known as Metavision MVICU
TM
(iMDSoft; Needham; Massachusetts; USA), and has
been customised to suit the needs of the hospital
over the past five years
2 BACKGROUND
System designs have become more sophisticated,
such that they allow flexibility within a design
framework, that provide for safe localisation and
customisation by the clinical end user.
At GUH a group of critical care practitioners and
support staff find time during part of normal clinical
duties to be part of the ‘CIS team’ responsible for
system customisation and user training
The process of CIS customization is brought
about by continuous quality improvement initiatives
that are driven by the ‘evidence based medicine’
philosophy of care. High performing critical care
departments are constantly improving and refining
procedures, technology, policies, and so on. It is this
drive to keep abreast of the latest technological and
practice developments that fuels the need for
continuous improvement of the CIS platform.
The CIS has a dual role; to facilitate the change
process through design of the CIS application
workflow; and to assess performance through
measurement and audit of key indices (Higgins,
2007).
Orlikowski (2000) notes that “this process of
“change” never stops; even when implementation is
‘formally’ finished, users will still shape and craft
the information system to fit their particular
requirements or interests”. This provides for the
notion that implementation of a CIS solution is not a
one time event for the project team and end-users;
the project essentially does not end. The post-
implementation phase becomes one of continuous
development and improvement. It may even be
necessary to distinguish successful ‘installation’ (a
one time event), from successful ‘implementation’ (a
more longitudinal perspective)
Berg writes that CIS implementation is best
considered a process of ‘mutual transformation’,
where the organisation and the technology transform
each other during the implementation process. What
determines successful implementation is “decided on
the work floor, by middle management, by top
managers-and it is the outcome of these interactions
that settles on the systems fate” (2001 p.144)
Atkinson and Peel provide the useful metaphor
that the CIS and the wider socio-technical
organisation must “grow together in stages towards a
vision created and shared by all” (1998, p.285)
Much of the CIS evaluation literature limits data
collection up to the months following
implementation (Byrd et al., 2006), and after this
point assumes the CIS remains ‘a success’. Van der
Meijden, in his review of the DeLone and McLean
(1992) model of success applications to Health
Information Technology success, notes that
evaluation of such systems should start before the
development and should have “no fixed end point”
(2003). He notes that “formative evaluation” –
aimed at improving information systems during
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development or implementation- were difficult to
locate in a review of the literature.
This adds to this research that successful
installations can essentially become unsuccessful
systems in the absence of a continuous evaluation,
improvement and feedback mechanisms (van der
Meijden et al., 2003).
This is essentially the ‘gap in the literature’ that
this research attempts to address. For an institution
that has successfully installed CIS technology into
routine clinical use, there is scant advice in the
literature on ‘how’ the hospital should organise itself
to maintain the momentum required to continually
‘grow’ and improve the CIS in the years post
implementation.
This research attempts to provide a roadmap for
ongoing success. Thomas and Fernandez (2008)
make a pertinent point; “having a well defined
perception of what has to be achieved to attain
success may indeed contribute to achieving the
evasive target of project success”
3 RESEARCH OBJECTIVES
The day to day role of the CIS team is to continually
develop and improve CIS functionality. This is
achieved through a suite of tools; along with
specialist training members of the team receive from
the CIS manufacturer. Team members received
change requests via a number of routes. The typical
routes of change requests are:
• Scheduled quality improvement initiatives from
individual staff members.
• Ad-hoc daily interaction between CIS users
(clinical staff) and the CIS Team members.
• New features released from the CIS
manufacturer.
• Data quality and clinical audit work.
• Hospital management requests for service
activity data.
In the four years since the first phase of
installation, it has become clear to the CIS team, that
in order to continually improve the CIS towards
optimisation of potential benefits, it requires a shift
in emphasis from the ad-hoc to a more strategic
approach to how the CIS team and critical care unit
are “organised” for continued success. This is
particularly the case because, as a member of the
CIS team put it, “we have picked all the low hanging
fruit”.
Another important issue that is increasingly
relevant is that the resources, principally personnel
expertise and time, employed for CIS customisation
projects are becoming more constrained in the
tightening healthcare fiscal environment. It has
become increasingly important to the critical care
service to demonstrate efficient use of its resources
and to strategically leverage those areas of CIS
potential to greatest patient and business benefits.
This research seeks to address these issues by;
(a) providing a framework that provides a basis for a
more strategic, targeted approached to CIS
development, and (b) pilot the model that will
provide a means guide resources to both improving
and disseminating the actual and potential value of
the CIS to critical care delivery.
The primary Research Question that this work
seeks to address is:
“How may a ‘maturity model’ be developed, for
the continued quality improvement of a locally
customised critical care Clinical Information
System?”
4 LITERATURE REVIEW
The wider business and organisational development
literature may provide advice on the socio-technical
factors that underpin efforts to drive continued
success in high performing, high technology
environments such as the use of CIS technology in
critical care medicine.
Business process management (BPM) is a
systematic approach to improving an organization's
business processes. It is considered a “holistic
management” approach that promotes business
effectiveness and efficiency while striving for
innovation, flexibility, and integration with
technology. BPM attempts to improve processes
continuously. It is often described as a "process
optimization process" (Andersen, 2007)
At the core of BPM is the concept of process
maturity. The term “maturity” is defined by Fraser et
al. (2002) by its literal meaning; “ripeness”. It
conveys a notion of development or progression
from some initial state to a more advanced state.
First published in 1989 by Watts Humphrey, and
later by the software Engineering Institute at
Carnegie Mellon, the Capability Maturity Model
(CMM) – later superseded by CMM integrated - has
become an established model in the field of IS
development. The CMM provides software
organisations with guidance in the form of a
framework on how to gain control of their processes
(developing and maintaining software). It can help
improve the maturity of these processes. The CMM
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model comprises five levels; each defined as an
evolutionary plateau of process improvement and
includes a checklist to evolve on to the next level
(van de Wetering and Batenburg, 2009).
A maturity level is a way to characterise the
dimensions that describe the process, system or
organisation, by assigning a level of performance
with regard to the activities contained within each
dimension. These levels range from the ad-hoc, or
depend on the initiative of an individual so that the
outcome is less likely to be repeatable, or as the
level increases, to one where the activities are
performed systematically, and are well defined and
managed (Farrukh et al., 2003b)
Fraser, Moultrie et al (2002) make the point that
in practice, maturity models are used as part of an
improvement process, and not primarily as absolute
measures of success or performance. Its principle
function is to identify gaps which can be targeted in
subsequent improvement actions, along a pre-
defined scale.
In particular, maturity models can be used for
three purposes including:
• as a descriptive tool enabling an ‘as-is’
assessment of strengths and weaknesses;
• as a prescriptive tool enabling the
development of roadmap for improvement;
and
• as a comparative tool enabling benchmarking
framework to assess against industry
standards and other organisations.
More recently, maturity models (also termed
‘maturity frameworks’ by some authors) have been
used in the healthcare IS research. Van de Wetering
and Batenburg (2009) provide a maturity model for
the technological sophistication of Picture Archiving
and Communication Systems (PACS) in hospitals.
The focus of the van de Wetering and Batenburg
(2009) work is to examine a staged approached to
the technical and technological dimensions of a
PACS system, and places less emphasis on the
cultural, socio-political and organisational aspects of
such implementations.
On the other hand, Elwyn, Rhydderch et al.
(2004) focus predominantly on the organisational
development aspects of health care provision. In this
research, the authors describe the development of a
‘Maturity Matrix’ for assessing the organisational
development in primary medical care group of
practices. The assessment tool takes the traditional
framework maturity model format.
The dimensions in this study include key process
areas (KPA) that consider how the GP practice
network organises itself with regard to; clinical
records, audit of clinical performance, access to
clinical information, use of guidelines, prescribing
monitoring, practice communication and
collaboration, patient-clinician interaction, and
patient feedback systems. (Elwyn et al., 2004)
Common threads from both the PACS (van de
Wetering and Batenburg, 2009) and the General
Practice (Elwyn et al., 2004) maturity models, that
are of particular relevance to healthcare are that; (a)
the process of developing the model is itself a useful
tool for fostering effective intra-professional
collaboration, (b) the model provides a useful self
assessment or benchmarking tool for an
“as-is” assessment of performance, (c) it
provided a forum to develop ex-ante perspective or
vision of the more mature, and sophisticated “to-be”
state, (d) it facilitates a “bottom up” approach to
quality improvement, (e) aligns the strategic and
tactical priorities of the organisation and (f) the
group assessment process encourages the concept of
“double loop learning”, where “the organisation
‘learns how to learn’ so that the concepts of change
management are second nature” (Elwyn et al.,
2004).
5 METHODOLOGY
Due to the exploratory nature of this research, a
qualitative orientation that addresses the research
questions is most relevant.
The research philosophy taken in this study is
empirical in nature. The research design may be
described as a cross-sectional case study. The
sampling technique is defined as “purposeful
sampling”, which is the dominant strategy in the
qualitative research literature. A grounded theory
approach guides the data analysis (Strauss and
Corbin, 1998).
The study participants chosen for this research
were taken from a team previously assembled by the
hospital to implement and manage ongoing CIS
quality improvement and use development work.
The group was a multidisciplinary team consisting
of consultant anaesthetists (n=3), clinical pharmacist
(n=1), clinical nurse managers (n=3), and hospital
management (n=1).
The data collection was performed in three
phases, as illustrated graphically in figure 1.
The first phase was a Qualitative Content
Analysis (QCA) of three texts to determine the
themes or categories that describe the dimensions of
the critical care service. QCA is a specialised form
of qualitative research, which is an extensively
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Figure 1: QCA findings for each document, and final dimensions. The top part, Phase I, illustrates the outcome of the QCA
on each text . Also shown is Phase II, the circular interview process used to build the model detail; and Phase III, pilot
testing among the eight participants in the case study.
Table 1: Maturity Framework dimensions, along with description, developed in this case study.
Dimension Description
Risk and Quality Management
How the CIS facilitates efforts to reduce risk to patient, staff and organisation.,
along with how the CIS contributes to increasing quality of care and service delivery
Multi-Disciplinary Team (MDT)
Collaboration and
Communication
How the CIS can facilitate and foster good inter profession communication and collaboration
Guideline, Policy and Practice
Development
How the CIS contributes to good compliance with implementation of unit guidelines,
best practices and policies
External Benchmarking
How the CIS generates good quality data that allows the service performance to be
benchmarked against national and international best practice indicators
Business Efficiency and
Reporting
How the CIS facilitates efficient work practices, and monitors efficiency
Leadership and staff
Empowerment
How the CIS helps staff feel empowered in their professional duties, with good quality
information and control over CIS functionality and the direction system changes and use
takes.
Research and Training
How the CIS contributes, or initiates, medical, nursing and allied health research
employed analytical tool for the systematic analysis
of documents (Krippendorff, 1980).
The texts chosen for examination were originally
prepared by the critical care team leaders and staff,
as part of normal service delivery. These texts were
chosen by the study participants as being
representative of the Strategic (Hospital National
Accreditation report), Professional (Critical Care
Practice development accreditation submission), and
Operational (meeting minutes from previous year of
monthly critical care management team meetings)
The second phase was a series of semi-structured
interviews with the eight participants, based on the
results of phase I. The objective was to give the
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Maturity
Dimension
Level 1
5% 25%
Level 2
50%
Level 3
75%
Level 4
100%
MDT
Collaboration and
Communication
Paper notes continue
to be used by critical
care providers.
Individual paper
notes, and
workarounds evident-
mismatch of doc.
Media formats
Isolated professions
notes evident
Little evidence of
collaborative links or
ongoing
communications with
external CIS users
Significant proportion
of providers use CIS
for documentation, mix
of paper and CIS still
evident
Ad hoc approach to
coding of disease and
treatments.
CIS used as an
auditable
communication tool of
hospital and critical
care safety and risk
notices
Coding difficult to use
and search
Some evidence of
collaborative efforts to
infuse coding with
documentation process
Ad hoc or opportunity
link with external CIS
users and organisations
Good collaboration
between different care
units in place
Majority of
professions access
CIS for daily
documentation.
CIS documentation
easily accessible and
presented to all users
Some disease and
treatment coding
models used.
HIPE coding used for
a majority of patients.
Existence of in roads
to integrated coding –
pet projects
Some evidence of
collaborative problem
solving of CIS issues
with external users.
Comparative exercise
in place
Some evidence of
joint CIS
customisation and use
efforts presentations
at conferences.
Management
collaborate on CIS
related efforts that are
strategically
important
All anaesthesia,
referring, nursing, ICD,
ICNARC and SAPII are
integrated to CIS.
Referring teams have a
customised views and
input particular to their
needs
Close links with "sister"
units for co-development
of CQI initiatives with
CIS.
CIS team active
members of Informatics
organisations.
Coding used is an
integral part of the
documentation
Doctors not physically in
unit have remote access
to CIS during telephone
consultation with nurse
at bed.
Figure 2: Maturity model for the “MDT Collaboration and Communication” dimension developed by the study participants
(n=8) in this case study.
participants an opportunity to validate the results of
QCA, to provide depth, to enrich, and to add vitality
to these dimensions. Through the course of these
interviews the detail of the maturity model
developed
The third and final phase was a pilot of the final
version of the maturity model, where each
participant was asked to provide any comments, and
score the CIS project along each dimension from
each individual perspective.
6 RESULTS
The QCA of the three texts, that in this case study
provide an accepted proxy for the strategic,
operational, and the professional aspects of critical
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care delivery provided seven dimensions, or key
practice activities, to which the CIS should
positively contribute to continuous improvement.
These are shown in Table 1.
Each dimension is described by the four columns
of the traditional maturity matrix. Each column, or
level of maturity, was further divided into cells of
detailed statements that articulated a level of
sophistication of CIS use or functionality that were
accepted as consistent for each maturity level.
An example of the maturity model developed for
the “MDT Collaboration and Communication”
dimension is shown in Figure 2. The framework
maturity models for all seven dimensions described
in Table 1 were completed in this fashion.

Figure 3: Graphical representation of the scores retuned
from raters used in this pilot study (n=8). The target
symbol represents the median score (50
th
percentile) for
each dimension, bounded by the 25
th
and 75
th
percentile
(solid line). The multi-rater free marginal Kappa, K
free
(Randolph, J. J. (2008), used as a measure of inter-rate
agreement, is shown for each dimension.
The final maturity model was piloted
individually with the eight study participants. Each
was requested to review each dimension, and score
their perception of where the CIS maturity currently
lay along a scale from 0% to 100% in increments of
5%. The scale was divided equally to illustrate four
levels, level 1 (‘ad hoc’) through to level 4
(‘optimised’). All statements that describe a lower
level must first be satisfied before moving up to the
start of the next higher level.
Figure 3 presents the results of the pilot phase in
this case study in a “dash-board” type format.
7 DISCUSSION
The dashboard style presentation of the maturity
model points to key messages about how the study
participants believe the CIS contributes to critical
care service delivery.
Taking a simple visual interpretation of the
dashboard, the current state of CIS “maturity” at
GUH is approximately half-way on a journey
towards the ideal optimised (level 4) state. This
indicates that this group believe there remains scope
for continued improvement or maturity for all
dimensions.
When considering individual dimensions, it
seems clear that after five years of CIS use, moving
up the maturity levels is difficult. For example, how
the CIS contributes to “external efficiency and
reporting”, lags behind how this group perceives the
CIS facilitates improvements in “risk and quality
management”.
The broad spread of results within each
dimension, seen in the results of this pilot study
point to interesting issues. By performing a free-
marginal multi-rater Kappa, K
free
(Randolph, 2005),
it may be shown that, in this pilot study, different
perspectives exist, even when the members of the
group work cohesively on CIS development. A K
free
greater that 0.7 indicates adequate agreement. The
differences between individuals have a bearing on
the direction improvement initiatives the CIS will
take. Uncovering, and understanding the reasons for
difference of opinion are an important step first in
any improvement initiative.
Another possible explanation for spread of
scoring (or divergence of opinion) may be because
individuals have different understanding of what the
dimensions mean, or more particularly, what role the
individual believes CIS technology could have on
each in any improvement initiative.
‘Maturity’ implies that the “process is well
understood, supported by documentation and
training, is consistently applied through
improvement projects and is continually being
monitored and improved by its users” (Fraser et al.,
2002). Difference of opinion, say between different
leaders, is an issue that warrants attention in any
improvement initiative, so that the basis for action is
strategically sound, and understood by all.
Hammer and Champy (1993), in the context of
Business Process Re-engineering, make the point
that a consensus based understanding within the
organisation of the current state is the critical first
step in an improvement initiative. This would be
especially the case in complex organisational
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structures in critical care. A model that highlights
differences between individuals, or between
professions, has proved useful in this pilot study.
It could also be argued that the spread of
maturity framework scores across all dimensions in
this pilot test, point to a model that lacks
discriminatory power. This is an issue that has also
been considered in the wider maturity model
literature. For example, lack of discrimination has
been blamed for lack of bottom line results in
industrial new product development processes (Kahn
et al., 2006).
These authors suggest that this is principally
because such frameworks can be too subjective, and
lack concrete measures indicators of success (Kahn
et al., 2006). Efforts to quantify the proposed
framework will facilitate the measurement effort and
may offer more concrete results.
One way to achieve this would be to construct
the detail of statement or criteria in each column, or
dimension, as a series of Guttman scales, also
known as cumulative scaling, where greater levels of
achievement were dependent on the attainment of
previous steps (Elwyn et al., 2004, Trochim, 2000).
By this method is possible to provide a more
objective means of level and sub-level selection.
The literature shows that for correctly configured
maturity frameworks, moving up the maturity levels
is difficult (Kahn et al., 2006). In the case of a
critical care CIS, improvement and change
initiatives are more than just customisation
programming and testing work, but a complex mix
of socio-political and socio-technical factors that
mediate both the prospect of success, and pace of
progress. The practice of critical care medicine in an
acute hospital is recognised in the literature as one of
the more complex environments in which to effect
change and improvement (Callen, 2008).
8 CONCLUSIONS
The motivation for this research is to address a gap
in the health information technology literature by
evaluating the usefulness of a maturity model to
guide the ongoing improvement of a locally
customised critical care Clinical Information
System.
The method by which this CIS maturity model
has been developed provides for a path that is
grounded in the tactical, strategic and professional
requirements of the critical care service, in which it
operates. These paths focus on seven general
themes, or dimensions, that would be the focus for
CIS facilitated continuous quality improvement.
The portrayal of CIS customisation and
improvement initiatives from a multidimensional
construct is important because it guides the course of
action the critical care unit can take to improve the
sophistication of its CIS customisation, as part of the
overall continuous quality improvement efforts. This
research provides a methodology that has been pilot
tested for such a construct.
A limitation of this methodology employed in
this case study is that the findings extracted, the
dimensions chosen along with the details of each
model, are based on the subjective opinions of a
relatively small group of professionals from one
institution, using the CIS of one manufacturer.
Further work envisaged moving from the pilot phase
to larger participant group.
One of the practical benefits of the maturity
mode presented in this paper is that, in the six
months since it was developed, it has been used to
shape and prioritise customisation effort. For
example, the perceived low score awarded for
“Business efficiency and reporting” dimension has
steered efforts to using the CIS database to monitor
patient throughput and resource utilisation issues
more closely, and to report these key performance
indicators on monthly basis to hospital
management.
Similarly, with regard to the “MDT
Collaboration & Communication” dimension, the
authors are involved in research to examine how the
CIS can be further improved to foster and detect
better interdisciplinary communication between its
different user types
Leveraging the potential of the CIS is not a one
time event that is focussed on installation, but a
continuous and dynamic process of improvement.
This research provides a mechanism that culminates
with a maturity model which guides this unit to
continually customise and improve both the
functions of the CIS, and its use, along a pre-defined
strategically driven path. The pilot phase of this
research demonstrates that the model does point to
those areas that should be the focus for
improvement.
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