UNDERSTANDING AND ADDRESSING THE ‘FIT’ BETWEEN

USER, TECHNOLOGY AND ORGANIZATION IN EVALUATING

USER ACCEPTANCE OF HEALTHCARE TECHNOLOGY

Noor Azizah K. S-Mohamadali

1,2

and Jonathan M. Garibaldi

Intelligent Modelling and Analysis Research Group (IMA), School of Computer Science

University of Nottingham, Nottingham, U.K.

Department of Information Systems, Faculty of Information and Communication Technology

International Islamic University Malaysia (IIUM), P.O. Box 10, 50728 Kuala Lumpur, Malaysia

Keywords:

Evaluation study, Evaluation dimension, Importance of ‘Fit’ between user,Technology and organization,

Examples of good ‘Fit’ and poor ‘Fit’.

Abstract:

In this paper, we discuss the importance of addressing the ‘ﬁt’ between user, technology and organization

in evaluating user acceptance of healthcare technology. We give an overview of evaluation dimensions and

explore two models that are related to ‘ﬁt’. We demonstrate how users’ acceptance factors in previous studies

could be better explained through the perspective of ‘ﬁt’ between user, technology and organization. We

believe that the importance of ‘ﬁt’ needs to be understood in greater detail among the evaluation research

community. The ‘ﬁt’ between user, technology, and organization needs to be addressed together with the

factors that inﬂuence user acceptance. This paper attempts to gain empirical support for the inclusion of ‘ﬁt’

between user, technology and organization when evaluating user acceptance of the healthcare technology.

1 INTRODUCTION

Evaluation of the impact, effect and acceptance of

healthcare technology has greatly developed over

recent years and has led to a huge number of

methodological and practical publications (Randell

and Dowding, 2010; Schaper and Pervan, 2007; May

et al., 2000). Given the important role that health-

care technology has on the delivery of quality ser-

vices, it is important that the acceptance of technol-

ogy by healthcare professionals is evaluated, to en-

sure it fulﬁls the needs and purpose of the implemen-

tation (Bowns et al., 1999; Bleich and Slack, 2010;

Bossen, 2007). Decision makers often believe tech-

nology will bring beneﬁts to the organization as a

whole and to the patients, in particular, and that it

should be fully embraced. However, in some cases the

implementations does fail (Southon et al., 1999; Vish-

wanath and Scamurra, 2007). In some other cases,

the same systems implemented in two different set-

tings resulted in two different outcomes, where in one

setting it was widely accepted and in another setting

it was rejected by the users (Travers and M.Downs,

2000; Gremy et al., 1999). This is an interesting sce-

nario to be investigated, particularly the reasons for

such differences in outcomes. To understand user ac-

ceptance of healthcare technology, we need to under-

stand not only what are the factors inﬂuence accep-

tance but also how well these factors ‘ﬁt’ together. Al-

though, a number of publications have discussed the

issue of ‘ﬁt’ within their evaluation studies, this is in-

sufﬁcient because importance of ‘ﬁt’ with the organi-

zation needs to be explored in greater detail, together

with user and technology, in order to better under-

stand issues surrounding healthcare technology im-

plementation. Thus, there is a strong current need to

understand, address and gain empirical support for the

‘ﬁt’ factor when evaluating user acceptance of health-

care technology.

2 EVALUATION DIMENSION:

USER, ORGANIZATION,

TECHNOLOGY

Information systems are embedded within social sys-

tems in which different people and environments in-

teract with each other. In order to evaluate user

acceptance issues, we need to evaluate three ‘play-

ers’ which could inﬂuence users’ acceptance factors.

These are the user, the organization and the tech-

119

Azizah K. S-Mohamadali N. and M. Garibaldi J..

UNDERSTANDING AND ADDRESSING THE ‘FIT’ BETWEEN USER, TECHNOLOGY AND ORGANIZATION IN EVALUATING USER ACCEPTANCE

OF HEALTHCARE TECHNOLOGY.

DOI: 10.5220/0003696901190124

In Proceedings of the International Conference on Health Informatics (HEALTHINF-2012), pages 119-124

ISBN: 978-989-8425-88-1

 2012 SCITEPRESS (Science and Technology Publications, Lda.)

nology itself. According to (Despont-Gros et al.,

2005), evaluation frameworksneed to incorporate ﬁve

common features, which are (a) user characteristics,

(b) Clinical Information Systems (CIS), (c) process

characteristics, (d) environment characteristics, and

(e) impact. In our opinion, process characteristics

are the result of interactions between user, technol-

ogy and the environment in which the technology

is used. Impact is also the result of interaction be-

tween these three players. All these ﬁve features

could be explained from the perspective of the user,

technology and organization ‘ﬁt’. Furthermore, as

stated by (Chau and Hu, 2002), technology accep-

tance has three dimensions; characteristics of the in-

dividual, characteristics of the technology and charac-

teristics of organizational context. Several other eval-

uation frameworks also categorises factors that inﬂu-

ence user acceptance of the technology under these

three broad dimensions which are user, organization

and technology (Schaper and Pervan, 2007; Yusof

et al., 2008; Lorenzi, 1999). Therefore, when evaluat-

ing user acceptance issues these three players all need

to be evaluated together to understand how well they

‘ﬁt’ together. It is important to understand that to-

gether with factors which inﬂuence user acceptance,

the present or absence of ‘ﬁt’ between user, technol-

ogy and organization also will have an impact on user

acceptance.

3 ‘FIT’ RELATED MODEL

In this section, we are going to illustrate brieﬂy two

models that discuss the ‘ﬁt’ or equivalents to a ‘ﬁt’

factor. The ﬁrst is the task-technology model by

(Goodhue, 1995) and the second is the ‘design-reality

gap model’ by (Heeks, 2006).

3.1 Task-Technology Model

One area constantly received attention among IS re-

searchers when considering technology acceptance is-

sues is ‘ﬁt’ which is based on the Task-technology Fit

model (TTF). TTF holds that information technology

is more likely to have a positive impact on its indi-

vidual performance and be used if the capabilities of

the technology match the tasks that the user must per-

form. As (Goodhue et al., 2000) writes, “performance

impacts are dependent upon the ‘ﬁt’ between three

constructs: technology characteristics, task require-

ments and individuals’ abilities”. This model focuses

on the degree to which systems’ technology char-

acteristics match users’ task needs, hence the name

‘task-technology’ model. According to this model,

the higher the ﬁt between tasks and technology, the

better is the performance. (Bleich and Slack, 2010)

demonstrates the importance of ‘ﬁt’ between user and

technology in their article. As stated, “the key en-

thusiastic acceptance of electronic medical records

is computing that is easy to use and helpful to doc-

tors and other clinicians in the care of their patients”.

Management needs to understand that introduction of

any new systems have to match with the skills of the

users. In our opinion, the TTF model has a limita-

tion. TTF model focuses and discusses only the ‘ﬁt’

between user and task, and between task and technol-

ogy. It does not explicitly consider the importance

of the ﬁt between user and organization, nor between

technology and organization. TTF needs to incorpo-

rate the organization factor into its dimension to better

understand user acceptance issues.

3.2 Design-reality Gap Model

Another model which introduces almost similar con-

cepts as TTF Model is called the ‘design-reality

gap’ model, commonly known as ITPOSMO (Heeks,

2006). The ITPOSMO model suggests that success

or failure of new health information systems depends

on the existence of the gap between reality and de-

sign conception of health information systems. The

larger is the gap between the design of the system and

the reality of the system when it is operational, the

higher is the chance of system implementation fail-

ure. This concept is very similar to the concept pro-

posed by TTF model. The distinction would be, how-

ever, that TTF discusses the issue of acceptance from

a ‘ﬁt’ perspective, while ITPOSMO discuss it from a

‘gap’ perspective. Furthermore, the ITPOSMO model

presents more dimensions of evaluation than the TTF

model itself. The model introduces seven evaluation

dimensions which include information (data stores,

data ﬂow), technology (both hardware and software),

process (the activities of user and others), objectives

and values, stafﬁng and skills, management systems

and structures and other resources (particularly time

and money). We believe this model could be im-

proved with the inclusion of an organization factor

into its evaluation dimensions.

4 THE FIT BETWEEN USER,

TECHNOLOGY AND

ORGANIZATION

As described earlier, to evaluate user acceptance is-

sues, all three (user, technology and organization)

HEALTHINF 2012 - International Conference on Health Informatics

120

need to be evaluated together to examine how well

they ‘ﬁt’ together. The ‘ﬁt’ will have an inﬂuence on

the users’ acceptance factor. The higher is the ‘ﬁt’ be-

tween user, technology and organization, the higher

will be its inﬂuence on those factors related to user

acceptance.

The success or failure of information systems de-

pends largely on the ‘ﬁt’ between these three players.

A concept of ‘ﬁt’ is essential to understandimplemen-

tation issues within the organization’s current setting.

A user with certain IT skills is not a sufﬁcient require-

ment for the use or acceptance of a new system but

rather their skills must match with the requirement of

the system itself. This demonstrate the needs of ‘ﬁt’

between user and technology. And if the user does not

have the necessary skills to use the system, manage-

ment is responsible to provide necessary training to

ensure technology is accepted and used accordingly.

If the ‘ﬁt’ between user and technology is low, it will

eventually result in the rejection of the system (Tsik-

nakis and Kouroubali, 2008).

Selection of new information systems needs to

support both objectives and strategies of the organi-

zation. Any new system needs to be aligned with the

current settings and social organization it was meant

to support. This indicates the need of ‘ﬁt’ between

technology and organization. Kaplan and Shaw’s

recommendations for IT evaluation highlight the fol-

lowing, “Evaluation needs to address more than how

well a system works. Evaluation also needs to ad-

dress how well a system works with particular users

in a particular setting and further why it works that

way there, and what works itself means” (Kaplan and

Shaw, 2004) (pg. 220). This clearly shows the need

to evaluate technology along with the organization, as

well as the people using it, i.e. the ‘ﬁt’ along with

factors that inﬂuence acceptance.

Another example which demonstrates the ‘ﬁt’ be-

tween user, technology and organization is in work

by (Bossen, 2007). The author conducted a three

month case study on the daily use of a computerized

problem-oriented medical records (CPOMR) at a uni-

versity hospital in a county in Denmark. The ﬁnd-

ings show that the use of systems led to more time

spent in documenting clinical work. This was due

to the fragmentation of a patient situation into sep-

arate problems, and that the system also could not

provide an overview of patient records when needed.

Although the system is useful for patients with few

and simple problems, it is not useful for patients who

were admitted for longer periods of time. The pro-

totype system was concluded as not supporting daily

clinical practice. This is an example of absence or

poor ‘ﬁt’ between user and technology. This example

clearly shows the presence of poor ‘ﬁt’ between user

and technology.

As the above examples suggest, many of the ex-

isting studies on user acceptance could be better ex-

plained from a ‘ﬁt’ perspective. Previous studies have

mainly identiﬁed those factors which inﬂuence user

acceptance (Martens et al., 2008; Meade et al., 2009;

Chau and Hu, 2002). We believe it is insufﬁcient to

understand the reasons for different acceptances of

the same system. In evaluating user acceptance issue,

researchers need to evaluate not only factor which in-

ﬂuence user acceptance but also to evaluate the ‘ﬁt’

between user, technology and organization. For ex-

ample, a number of studies have identiﬁed for ex-

ample ‘ease of use’ as one user acceptance factor

(Tsiknakis and Kouroubali, 2008; Schaper and Per-

van, 2007). However, when we evaluate acceptance

of this ‘ease of use’ factor on its own, we cannot pro-

vide answers as to why the same system is accepted

in one setting and rejected in another setting. This

factor, ‘ease of use’, is basically dependent on the

‘ﬁt’ factor . Users who accept the system may have

the necessary skills and knowledge to use the system

which means there is a good ‘ﬁt’ between user and

technology. And user who rejects the system may not

have the skills and knowledge needed to use the sys-

tem, which is an absence of ‘ﬁt’. This clearly illus-

trates that identifying ‘ease of use’ as the sole factor

to inﬂuence user acceptance is inadequate. It has to

be incorporated with a ‘ﬁt’ factor.

From literature, we have identiﬁed various user

acceptance factors. These factors, we believe, could

be better explained from a ‘ﬁt’ perspective to bet-

ter understand user acceptance issues. The factors

are also divided between good ‘ﬁt’ or poor ‘ﬁt’. Ta-

ble 1 provides some examples of user acceptances’

factor which could be categorized as good ‘ﬁt’. Ta-

ble 2 demonstrate examples of user acceptance factor

which could be categorized as poor ‘ﬁt’.

5 CONCLUSIONS AND FUTURE

WORK

This paper aims at providing an understanding of ad-

dressing the ‘ﬁt’ between user, technology and orga-

nization factors when evaluating user acceptance is-

sue. To better understand issues on user acceptance of

healthcare technology, evaluation frameworks need to

incorporate ‘ﬁt’ factor together with user acceptance

factors. ‘Fit’ between user, technology and organi-

zation could serve as a determinant of those factors

that inﬂuence user acceptance. By understanding ‘ﬁt’

between these three players, we may understand why

UNDERSTANDING AND ADDRESSING THE 'FIT' BETWEEN USER, TECHNOLOGY AND ORGANIZATION IN

EVALUATING USER ACCEPTANCE OF HEALTHCARE TECHNOLOGY

121

Table 1: Categorizing user acceptances’ factor as examples of Good ‘Fit’.

Factor(s) Reference(s)

System beneﬁted user and/or patient (Travers and M.Downs, 2000; Bleich and

Slack, 2010; Randell and Dowding, 2010)

Time spend is less on clinical related work (Lee et al., 2008)

User have computer experience/ knowledge/ skills (Folz-Murphy et al., 1998; Ammenwerth

et al., 2006; Lee et al., 2008)

Organization provides training and accommodate team requirement (Lorenzi and Riley, 2003; Bowns et al.,

1999; Aggelidis and Chatzoglou, 2009;

Meade et al., 2009)

System provides sufﬁcient speed to accomplish jobs (Folz-Murphy et al., 1998; Martens et al.,

2008; Ash et al., 2000)

Systems is ease to use and useful (Dishaw and Strong, 1999; Carayon et al.,

2010; Yen et al., 2010; Chang, 2010)

User gets support from top management/managerial commitment (Travers and M.Downs, 2000; Yusof et al.,

2008; Tsiknakis and Kouroubali, 2008)

Organization promotes team spirit/ team-work (Travers and M.Downs, 2000; George

R. Harper and Dawn R. Utley, 2001; Bowns

et al., 1999)

Management provides supportive working environment and in-house tech-

nical support

(Randell and Dowding, 2010)

Management provides right technology which meets the requirements of the

job

(Folz-Murphy et al., 1998)

Technology is designed for all level of users (Carayon et al., 2010)

Good help desk support by vendor/technical support/administrative support (Martens et al., 2008; Aggelidis and Chat-

zoglou, 2009)

Table 2: Categorizing user acceptances’ factor as examples of Poor ‘Fit’.

Factor(s) Reference(s)

System negatively impacted staffs’ work ﬂow (Travers and M.Downs, 2000; Bleich and

Slack, 2010; Randell and Dowding, 2010)

System’s problem such as content, computer generated forms, hardware and

interface

(Lee et al., 2008)

System did not meet user’s practice requirement (Folz-Murphy et al., 1998)

Poorly designed system which increases workload/paperwork (Bossen, 2007; Meade et al., 2009; Lam-

mintakanen et al., 2010)

Information systems which is not ready to be used and does not support

management.

(Ellis and May, 1999; Lammintakanen et al.,

2010)

Lack of standardized terminologies which clinicians used to work with (Tsiknakis and Kouroubali, 2008)

User who has less/insufﬁcient experience with technology, limited skills to

use the systems

(Bossen, 2007; Short et al., 2004)

Technology that does not meet clinical needs or match with work ﬂow (George R. Harper and Dawn R. Utley, 2001)

Lack of internal IT support (Tsiknakis and Kouroubali, 2008; Vish-

wanath and Scamurra, 2007)

Lack of coordination at operational level (Lammintakanen et al., 2010)

Insufﬁcient training (Lee et al., 2008)

Organization does not provides training or educational program to the user (Vishwanath and Scamurra, 2007)

Insufﬁcient number of computer, printer problems, system downtime, sys-

tem breakdown

(Lee et al., 2008)

Mismatch or misalignment between facilities and social organization it

meant to support

(Southon et al., 1999)

Interaction problem between new system and existing system - complex,

time consuming, susceptible for error

(Heeks, 2006; Jr. et al., 2010)

Prototype lacking in functionality or usability (Bossen, 2007)

Technical problems/multiple updates to the information systems/operating

system

(Martens et al., 2008; Lorenzi and Riley,

2003; Carayon et al., 2010)

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the same system implemented in two different setting

results in two different outcome. Most of the pre-

vious studies only identify those acceptance factors,

but these factors could not stand on their own. The

present or absence of user acceptance factors depend

on the ‘ﬁt’ function. In this paper, we have argued

for the importance of understanding and addressing

the ‘ﬁt’ between user, technology and organization

in evaluation studies. The ‘ﬁt’ between user, tech-

nology and organization could serve as a function of

those factors that may inﬂuence user acceptance of

the technology. We believe ‘ﬁt’ is an essential ele-

ment to understand user acceptance issues. This pa-

per provides some fundamental basics of ‘ﬁt’, sufﬁ-

cient for researchers to consider the inclusion of ‘ﬁt’

factor within user acceptance factors. We believe ‘ﬁt’

should be addressed in all future evaluation studies.

In future, we are going to validate our proposed

model of user acceptance of healthcare technology.

The model has incorporated a ‘ﬁt’ function which

serves as a core determinant of the factors that inﬂu-

ence users’ intention to use technology. A case study

of the intention of medical students to use medically

related software in their work practice will be con-

ducted to test the applicability of our proposed model.

All the items measured in the questionnaire will be

based on the proposed model.

ACKNOWLEDGMENTS

Noor Azizah KS Mohamadali would like to gratefully

acknowledge the funding received from both the Pub-

lic Service Department of Malaysia and the Interna-

tional Islamic University of Malaysia (IIUM) that is

helping to sponsor this research.

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