3. Three major conceptual frameworks: TITT,

3. Three major conceptual frameworks: TITT,

3.
Three major conceptual frameworks: TTF, FITT, and ISTA.

Order Description
Discovery Question

In a minimum of 400 words, compare and contrast the three major conceptual frameworks concerning technology and task: TTF,
FITT, and ISTA.

1.Fit between Individuals Task and Technology – FITT – Ammenwerth et al.

2.Interactive Sociotechnical Analysis – ISTA – Harrison et al.

3.Clinical Adoption Meta-Model – CAMM – Price & Lau

BioMedCentral
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BMC Medical Informatics and
Decision Making
Research article Open Access
IT-adoption and the interaction of task, technology and individuals:
a fit framework and a case study
Elske Ammenwerth*1, Carola Iller2 and Cornelia Mahler3
Address: 1Institute for Health Information Systems, UMIT – University for Health Sciences, Medical Informatics and
Technology, Hall in Tyrol,
Austria, 2Institute for Educational Science, University of Heidelberg, Germany and 3Dept. of Psychiatry, University Hospitals
of Heidelberg,
Germany
Email: Elske Ammenwerth* – elske.ammenwerth@umit.at; Carola Iller – iller@ews.uni-heidelberg.de;
Cornelia Mahler – cornelia_mahler@med.uni-heidelberg.de
* Corresponding author
Abstract
Background: Factors of IT adoption have largely been discussed in the literature. However,
existing frameworks (such as TAM or TTF) are failing to include one important aspect, the
interaction between user and task.
Method: Based on a literature study and a case study, we developed the FITT framework to help
analyse the socio-organisational-technical factors that influence IT adoption in a health care setting.
Results: Our FITT framework (“Fit between Individuals, Task and Technology”) is based on the
idea that IT adoption in a clinical environment depends on the fit between the attributes of the
individual users (e.g. computer anxiety, motivation), attributes of the technology (e.g. usability,
functionality, performance), and attributes of the clinical tasks and processes (e.g. organisation, task
complexity). We used this framework in the retrospective analysis of a three-year case study,
describing the adoption of a nursing documentation system in various departments in a German
University Hospital. We will show how the FITT framework helped analyzing the process of IT
adoption during an IT implementation: we were able to describe every found IT adoption problem
with regard to the three fit dimensions, and any intervention on the fit can be described with regard
to the three objects of the FITT framework (individual, task, technology). We also derive
facilitators and barriers to IT adoption of clinical information systems.
Conclusion: This work should support a better understanding of the reasons for IT adoption
failures and therefore enable better prepared and more successful IT introduction projects. We
will discuss, however, that from a more epistemological point of view, it may be difficult or even
impossible to analyse the complex and interacting factors that predict success or failure of IT
projects in a socio-technical environment.
Background
It is hard to imagine health care without Information and
Communication Technology (ICT). Information technology
in health care has existed for about four decades, and
has gained widespread usage. Electronic patient records
offer health care professionals access to vast amounts of
patient-related information; decision support systems
support clinical actions; and knowledge servers allow
Published: 09 January 2006
BMC Medical Informatics and Decision Making 2006, 6:3 doi:10.1186/1472-6947-6-3
Received: 16 June 2005
Accepted: 09 January 2006
This article is available from: http://www.biomedcentral.com/1472-6947/6/3
© 2006 Ammenwerth et al; licensee BioMed Central Ltd.
This is an Open Access article distributed under the terms of the Creative Commons Attribution License
(http://creativecommons.org/licenses/by/2.0),
which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
BMC Medical Informatics and Decision Making 2006, 6:3 http://www.biomedcentral.com/1472-6947/6/3
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direct access to state-of-the-art clinical knowledge to support
evidence-based medical practice [1].
Introduction of ICT can radically affect health care organisation
and health care delivery and outcome. It is evident
that the use of modern ICT offers tremendous opportunities
to support health care professionals and to increase
the efficiency, effectiveness and appropriateness of care
[2,3].
However, not all projects introducing IT in health care are
successful. It is estimated that up to 60 – 70% of all software
projects fail (e.g. [4]), leading to enormous loss of
money within healthcare and also to loss of confidence on
IT from the side of users and managers.
It is interesting to recognize that the same IT system can be
seen as success by one department or professional group,
but as a failure or at least as problematic by another
department or professional group. Various interconnected
factors seem to exist that influence success or failure. In
fact, the notion of success and failure has been largely discussed
in the literature in the last years. We will not try to
repeat the overall discussion here, but just refer to some
good references ([5-11]).
What we observe in any case is that the objective effects of
the same IT system can largely differ in different settings.
This is not surprising if we understand information systems
as technical systems embedded in a social-organizational
environment (see also [12]). The technology we are
introducing in different clinical settings can be largely
equal (e.g. the same PACS software in various radiological
departments). But the socio-organizational setting may be
quite different (e.g. different organization of workflow,
different patient profiles, different motivation of staff, different
management support, different IT history etc.),
leading to different adoption processes of the same IT system,
and thus to different effects (e.g. increased efficiency
on one ward, user boycott on the other ward).
What does this mean for a systematic IT management in
hospitals? We argue that it would be helpful to know
more about the factors influencing IT adoption, success
and failure, and to be able to predict the effects in a certain
setting.
Therefore, at least two questions arise which should be
answered by medical informatics research:
1. What are the “socio-organizational” factors that influence
adoption of an IT system in a given socio-organizational
context?
2. Based on the answers to question 1: Is there any way to
predict the effects of an IT system in a certain context?
The aim of this paper
The aim of this paper is to present an approach to answer
the first question. Based on a literature study, we will
present a framework (the FITT framework) to better analyse
the socio-organisational-technical factors that influence
IT adoption. We will present the application of this
framework in the analysis of a case study, describing the
adoption of a nursing documentation system in several
departments of a German University Hospital.
With regard to the second question, we will argue that
from some more philosophical point of view, the exact
prediction of success and failure may not be possible at
all.
Previous work on IT adoption
Analysis of the factors influencing adoption (and thus
also success and failure) of IT systems in health care has
been an issue in research for many years. We will define IT
adoption as follows, based on the discussion in [13]: for
voluntary used system, IT adoption is reflected in the
usage of the IT system; for mandatory used systems, IT
adoption is reflected in the overall user acceptance. In the
next paragraph, we will analyse some research results on
factors for IT adoption, focussing on general valid frameworks.
Analysing the concept of information system (IS) success,
DeLone [5] developed an information success model for
management information systems. This model describes
that the effects of IT on the user (the individual impact)
and thus on the overall organization depends on the use
and the user satisfaction. Those two aspects themselves
depend on the quality of the IT system and the quality of
the information in this system (Figure 1). This model was
used to structure a broad literature review, but seems not
to be further validated. The authors discuss that IS success
is a multidimensional construct based on the interaction
of factors, and that a corresponding measurement instrument
should therefore include not only the described criteria,
but also their interaction.
IFnifgourmrea t1ion success model by DeLone [5]
Information success model by DeLone [5].
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The information success model is quite interesting as it
describes the interaction of various factors. However, its
shortcoming seems to be the isolated focus on IT quality
and system quality, indicating that only the system’s quality
itself determines the overall impact. This does not help
to explain why the same IT system can be adopted in a different
way, and have rather different effects, in various settings.
The technology acceptance model (TAM) of Davis [14]
tries to analyse why users adopt or reject a system. It
defines the constructs “perceived ease of use” and “perceived
usefulness” to predict attitude towards using and
actual system use. Both factors themselves depend on features
of the system (Figure 2).
While trying to verify his model by questioning 112 users
of one company, Davis [14] could partly confirm the
expected links in his model. In his discussion, he stresses
that this model is only usable for voluntary use of IT system,
and that further factors should be included in his
model, such as extrinsic motivation, user experiences with
the system, and characteristics of the task to be supported
by IT (e.g. complexity of a task).
This TAM model was adopted and extended by other
researchers such as [15,16] and [17]. For example, Dixon
[16] extended it to the Information Technology Adoption
Model (ITAM). He tried to refine the “system design
features” of the TAM model by describing that an IT system
has requirements (such as required IT knowledge of
the users, or necessary technical infrastructure) that must
be matched with the knowledge and skills of the users and
with the available technical infrastructure. He called this
“fit” and argued that perceived usefulness and perceived
ease of use are not dependent on the system design features,
but on this fit of user and system design features.
The paper stays unclear whether the ITAM model was
more formally validated. It is also unclear why those
points already discussed as missing by Davis [14] (such as
extrinsic motivation or task characteristics) were not
included.
All of the presented models seem to concentrate rather
strongly on individual attribute of the users and of the
technology, neglecting attributes of the clinical environment
and of the supported clinical tasks that in our opinion
are of high importance to understand IT adoption
processes. ITAM is however interesting as it introduced the
notion of fit, explaining that it is not individual attributes
which are important, but the quality of fit between e.g. IT
complexity and IT knowledge.
The idea of fit is more comprehensively elaborated in the
task-technology-fit model (TTF) of Goodhue [8,13,18].
He takes into account not only technology and user, but
he also considers the complexity of the clinical tasks
which have to be supported by an IT system. He examines
the influence of the three factors – individual abilities,
technology characteristics, and task requirements – on
performance and on user evaluation of IT systems, highlighting
the significance of the interaction (fit) of those
three factors (Figure 3). He argues that TTF (task-technology
fit, or more correct task-individual-technology fit, as
explained by [13]) is the extent to which technology functionality
matches task requirements and individual abilities.
Goodhue argues that user evaluation is a sufficient
surrogate of TTF, and that it is appropriate for both mandatory
and voluntary used IT system. The TTF model was
used in the area of management information systems, and
many of the proposed links within the model could be
validated in studies in various studies with hundreds of
users.
TTF extends the other described models by concentrating
on the fit. IT also includes the object of clinical task (e.g.
task complexity, organization of tasks, interdependence
with other tasks) to be supported by IT. However, TTF
only focuses on the fit between user and technology, and
between task and technology (see Figure 3). It does not
consider the interaction of user and task – which is, however,
in our opinion an important success factor for IT
introduction projects. For example, introduction projects
may fail because nurses are not sufficiently motivated for
nursing process documentation at all, independent of the
tool used, or physicians may not be motivated to do a
complete order entry themselves, instead of ordering a
nurse to complete the order, because of the additional
time it will take them. In addition, TTF and derived models
do not reflect on the dynamics of introduction
projects. Attributes of users, task and technology frequently
change over time in a clinical environment, and
thus also their interaction and their fit change.
However, the notion of fit has been found useful in many
other studies, too. For example, Folz-Murphy [19]
described problems of the fit between user requirements
and available IT functionality. Zigurs [20] examined the
fit between task and technology in the area of group supports
systems. Dishaw et.al. [21] extended the TTF – com-
FTeigcuhrneo l2ogy acceptance model (TAM) by Davis [14]
Technology acceptance model (TAM) by Davis [14].
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bined with the TAM model – with the construct of
computer self-efficacy. With reference to the domain specific
of users abilities the developed model of Dishaw
et.al. also implied a relation between the attributes of user
and task. The idea of fit seems thus to be helpful in various
contexts.
Overall, the presented approaches present a good basis for
the analysis of the IT adoption; however, all of them show
some limitations.
Bases on this analysis of the literature, we will now present
a framework of fit between individuals, task and technology
(FITT framework), taking into account the processoriented
character of an IT introduction. We will use our
framework in a retrospective analysis of a corresponding
case study.
Methods: The FITT framework
Based on the literature review, we found it useful to use
the interaction (fit) of users, tasks and technology as the
basis to better understand IT adoptions.
Our FITT framework (“Fit between Individuals, Task and
Technology”) is based on the idea that IT adoption in a
clinical environment depends on the fit between the
attributes of the users (e.g. computer anxiety, motivation),
of the attributes of the technology (e.g. usability, functionality,
performance), and of the attributes of the clinical
tasks and processes (e.g. organisation, task
complexity) (Figure 4).
An “Individual” can represent an individual user or a user
group. “Technology” can stand for the interaction of various
tools needed to accomplish a given tasks (e.g. hardware,
software, network). But the technology does not
only comprise computer-based tools, but all tools used by
the individuals to execute the tasks, therefore including
also paper-based tools. “Task” comprises the wholeness of
tasks and working processes that have to be completed
(e.g. nursing documentation, order entry etc.) by the user
and that are supported by the given technology.
Many researchers focus on the aspect of “organisation”.
Organisational aspects in our model are either part of the
individual aspect (individuals work in various roles and
various groups in an organization), or they are considered
in the task aspect (the clinical tasks and processes are
organized in a given way, with defined responsibilities).
The objective of IT management can now be defined as
reaching an optimal fit between technology, user and task.
This means that e.g. user involvement in the selection
process or a good user support can improve the fit
between the three aspects. Individuals must therefore be
sufficiently motivated and knowledgeable to execute a certain
task. The technology must offer sufficient functionality
and performance to support a given clinical task. And
the user must be sufficiently trained to use a given technology
adequately. An insufficient fit will probably lead to
problems during implementation projects.
The quality of fit depends on the attributes of the objects.
The following list presents some examples on attributes
that affect the various fit dimensions:
• Attributes on individual level: IT knowledge, motivation
and interest in the task to be completed, flexibility and
openness to new ways of working, team culture, organizational
context, cooperation within a team, and politics
within an organisation.
• Attributes on task level: Organisation of the tasks to be
completed, activities and their interdependence, complexity
of tasks.
• Attributes on technology level: Stability and usability of
a software or hardware tool, costs of a tool, functionality,
available technical infrastructure, integration of tools,
availability of tools in a certain clinical situation.
In order to influence and improve the fit, management
can directly influence those attributes of task, individual,
and technology. For example, a reorganization of docu-
FTiagsku-rTee 3chnology-Fit model (TTF) by Goodhue [8], [13], [18]
Task-Technology-Fit model (TTF) by Goodhue [8], [13],
[18].
TbFehigtewu FreIeeTn T4 i nfrdaimvideuwaol,r tka s(1k) a: nITd- atedcohpntoiolong dyepends on the fit
The FITT framework (1): IT-adoption depends on the fit
between individual, task and technology.
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mentation processes may improve the fit between task
and technology; training sessions for users may improve
the fit between technology and individuals; a software
update may influence both the fit between technology
and task (e.g. new functionality being implemented) and
between individual and technology (e.g. usability being
improved). Here are some examples for possible deliberate
interventions on the three objects to influence and
optimize the fit:
• Intervention on the individual level: user involvement
in system selection and introduction (change management),
user training sessions, good user support, motivation
by the management (leadership issues).
• Intervention on the task level: Reorganisation of task
and working processes (e.g. new ways for order entry),
clarification of the responsibilities (e.g. for nursing documentation).
• Intervention on the technology level: Hardware and
software updates, redesign of paper-based forms, network
upgrade.
Besides the direct interventions on the three objects, there
are also external factors that may influence the fit, but
which cannot easily be controlled by the IT management.
The following list presents examples for those external
influencing factors:
• Intervention on the individual level: Staff changes (e.g.
reducing IT knowledge), workload of staff (e.g. reducing
time for IT use), changes of hospital strategy (e.g. IT is now
seen to contribute to competitiveness of the hospital).
• Intervention on the task level: Rising complexity of the
task (e.g. by new legal documentation requirements), general
organisational changes in the organisation, changes
in patient profiles.
• Intervention on the technology level: New software
standards, new technological achievements.
Due to those external factors, there will never be a complete
static situation with regard to the three fit dimension
and therefore to IT adoption. The external factors can
improve or deteriorate the fit, while the deliberate interventions
of IT management will be aimed at steadily
improving the fit. There may only be a partly stable situation
where the positive and negative changes are mostly
balanced. It is helpful to describe this fit management and
fit dynamics as a loop-back system (Figure 5).
The overall aim is to have an optimal fit to allow an easy
IT adoption. As described, the fit model allows us to
describe what we can do to influence and balance the fit.
The larger the difference between the actual fit and the
planned fit, the higher the problems during an IT introduction.
For example, low fit between users and technology
may lead to user frustration and finally to user boycott
if no interventions (e.g. IT training sessions) are organized.
We assume that this basic theoretical approach can help
analyzing the process of IT adoption during an IT implementation
project in a clinical environment in the following
ways (Figure 6):
1. Any disruptions during an introduction project can be
described and analysed with regard to the disruption in
one of the three fit dimensions (task-technology, technology-
individual, or individual-task). This should help
plan projects, as problems can be anticipated in advance,
or can help to analyse problems in a project retrospectively
in order to learn from them.
2. Any intervention that is taken to improve a project, to
make it successful, can be analysed and described with
regard to one of the three objects (task, individual, or
technology). Any of those interventions on the objects
will thereby indirectly affect the fit dimensions.
We will now present a case study where the FITT framework
was applied in a retrospective analysis, to show how
it can help describe and analyse an implementation
project.
Reanalysis of a case study: IT adoption and FITT
framework in a German university hospital
A computer-based nursing process documentation system
was introduced on several wards of the University Hospitals
of Heidelberg between 1998 and 2001. This introduction
was accompanied by various evaluation activities
which among others investigated the following aspects:
• General computer knowledge and attitudes to computers
in nursing before, during and after system introduction.
• Nurses acceptance of the nursing care process (the task
to be supported by the IT) before, during and after system
introduction.
• User satisfaction with the nursing documentation system
before, during and after introduction.
• Quality of nursing documentation before, during and
after system introduction.
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• Overall affects of the nursing documentation systems on
nursing workflow.
These evaluations were done e.g. based on standardized
and validated psychometric questionnaires (given to all
nurses, with return rates around 80%), standardized documentation
quality audits (analysing the nursing records
of 20 patients per ward at three points of time), and focus
group interviews with 1 – 2 nurses per ward and with
nursing and project management. Methods and results of
the evaluation studies have been published e.g. in [22-
25]. More details on all studies can be found in the corresponding
German research reports [26-28] as well as in
[29].
In general, the evaluation results showed high user acceptance
of the IT system, and positive effects e.g. on documentation
quality. A detailed analysis, however, showed
differences in the reactions of the wards with regard to the
new IT system. On one (somatic) ward, user acceptance
was much lower than on the other wards, and several
problems during IT introduction occurred here. On this
ward (ward C), user acceptance was very low shortly after
the introduction, and remained rather low even months
after it (Figure 7).
The FITT framework was used to analyse the differences
on the wards, the process of IT adoption, and the effects of
interventions taken by the project and IT management to
improve IT adoption. This analysis was based on the available
results of the already mentioned various specific evaluation
studies.
In this paragraph, we will present the result of this analysis
for two somatic and two psychiatric wards. As already discussed,
three of them showed a quick IT adoption, one of
them showed a more problematic introduction (Figure 7).
A complete report of this analysis has been published in a
German project report [27].
All wards had used a paper-based documentation system
prior to IT introduction which was now in part replaced
by a computer-based system. This new IT system covered
all steps of the nursing process (nursing anamnesis, care
planning, documentation and evaluation of care – for a
detailed explanation of the nursing process, see e.g. [30]).
However, all functionalities were only used on the psychiatric
wards where all steps of the nursing process were
documented. The documentation on the somatic wards
concentrated on the documentation of nursing anamnesis,
care planning, nursing tasks, and omitting the evaluation
of care. Nursing notes were written on all wards in the
IT system.
Dermatological ward
The dermatological ward had 20 beds, around 12 nurses
and a mean length of stay of about 10 days in 2000. The
IT system was introduced in Sept. 2000. Questionnaires
and documentation analysis were conducted three
months before IT introduction and again in Dec. 2000
and in June 2001. A focus group interview study was conducted
in February 2002.
The analysis on this ward found a rather uncomplicated
and quick adoption of the new IT system. We will present
the reanalysis of this case on the three fit dimensions:
• Fit between individuals and task: This fit was mostly
uncomplicated from the very beginning. Both ward managers
and nurses stated in the interviews that they were
tnFThaihegle riu neFrfbIleTuy e T6in fcdreiarsme wcetiwllyl o aarfffkfee c(c2tt )ian: tgDt rteihblieub tetehrsar etoeef
itfnaitts ekdr,i vmteeencnthisnoionnlso sagnyd a nedx tfeitr,-
The FITT framework (2): Deliberate interventions and external
influences will affect attributes of task, technology and fit,
thereby indirectly affecting the three fit dimensions.
PFliagnunrineg 5, directing and assessment of the fit
Planning, directing and assessment of the fit. While the fit can
be managed by deliberate active interventions (e.g. by IT
management), continuous external factors may influence it,
too.
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convinced of the necessity of a high-quality nursing documentation,
for legal reasons and for the reputation of
nursing. The nursing process was mostly well accepted, as
the questionnaires showed. Documentation analysis and
interviews confirmed that nursing documentation was
more complete after IT introduction than before. However,
as the intensive documentation audits showed, not
all steps of the nursing process were well documented,
and the documentation was in part not adequately
adapted to the individual patient.
• Fit between individuals and technology: This fit was
uncomplicated from the very beginning. The young, motivated
team with high IT skills had no problems in learning
the new technology. Computer acceptance and computer
security levels were found to be high from the very beginning
both in the questionnaires and the interviews.
• Fit between task and technology: This fit was a bit problematic
at the beginning, as the documentation analysis
showed. The pre-defined nursing care plans offered by the
IT system were at first not sufficiently adapted to the need
of this ward. In addition, the computer equipment was
first insufficient (to small number of computers, too slow
hardware) to support a timely documentation process.
Because documentation has always been done in the ward
headquarters, no mobile or bedside computers were
found necessary.
Summarizing, on the dermatologic ward, we found a
good individual-technology fit after the IT introduction.
The individual-task as well as the task-technology fit were
not optimal at the very beginning (Figure 8).
In order to improve the problematic fit dimensions,
project management intervened as follows during the
introduction period:
• Intervention with regard to task: None.
• Intervention with regard to user: Several onsite discussion
to increase nurses’ knowledge of the nursing process
and how to correctly use pre-defined standardized nursing
care plans, to increase fit between individual and task.
• Intervention with regard to technology: The predefined
standardized nursing care plans were refined, to
improve adaptation to the individual patient; hardware
was updated and extended, thereby increasing fit between
task and technology.
Those interventions seem to have improved the fit. The
nurses judge the support of documentation by the software
and hardware equipment as rather good after two
years both in the interviews as well in the standardized
questionnaires. The documentation analysis also show an
improvement in documentation quality.
Paediatric wards
The paediatric ward had 15 beds, around 13 nurses, and a
mean length of stay about 5 days in 2000. The nursing
documentation system was introduced in Oct. 2000.
Questionnaires and documentation analysis were conducted
three months before IT introduction and again in
Jan. 2001 and in July 2001. A focus group interview study
was conducted in February 2002.
Compared to the other wards this ward showed rather low
user satisfaction values with the nursing documentation
system during the introduction phase. An analysis structured
according to the FITT framework showed several
problematic areas:
• Fit between individuals and task: Th

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