Electronic Health Record Portal Adoption by Health Care
Consumers
Proposal of a New Adoption Model
Jorge Tavares and Tiago Oliveira
ISEGI, Universidade Nova de Lisboa, Rua Campolide, Lisboa, Portugal
Keywords: e-Health, Technology Adoption, UTAUT2, Health Care Consumers, e-Government.
Abstract: The aim of this study is to identify a set of determinants of adoption of electronic health records (EHR)
portals by health care consumers. Based on extensive literature review we suggest a new research model
based on the unified theory of acceptance and use of technology in a consumer context (UTAUT2) by
integrating a second order construct, Concern for Information Privacy (CFIP) framework and a moderator,
chronic disability. A set of propositions is also included to test the new conceptual model. We also present a
plan to validate the proposed model through empirical testing. The EHR portals are a part of the e-
government strategy currently unfolding in Portugal. Understanding the acceptance and use of EHR portals
by health care consumers should benefit the future sustainability of the Heath Care System, which will gain
a more efficient use of resources.
1 INTRODUCTION
E-health technology for health care consumers is the
use of electronic resources, mainly web-based, on
medical topics by healthy individuals or patients
(Alpay et al., 2010; Lee et al., 2010; Millard and
Fintak 2002; Nazi, 2003). Our study focuses on a
specific type of e-health technology, the electronic
health records (EHR) portals, which give patients
access to medical records, exam results, and
services, such as appointment scheduling,
notification systems, and e-mail access to the doctor
(Angst and Agarwal, 2009, Andreassen et al., 2007).
In Portugal, where data collection for this study
will be implemented, approximately 30% of the
population already uses the internet for health
purposes (Andreassen et al., 2007), considerabl less
than Northern European countries like Denmark and
Norway, where more than 50% of the population
uses Internet for health purposes (Andreassen et al.,
2007). Understanding the acceptance and use of
EHR portals technology by health care consumers is
a very important topic with clear benefits for society
and the future sustainability of the Heath Care
System (Or and Karsh, 2009; Wilson and Lankton,
2004). In a country like Portugal, which faces a
severe austerity program, the cost and efficiency
advantages of e-health technology use by patients
brings benefits to health care consumers and relief to
the Ministry of Health budget (McKee et al., 2012;
Metaxiotis et al., 2004). The EHR portals are a
specific type of technology that can greatly help to
achieve these benefits for both patients and health
care providers (Angst and Agarwal, 2009). EHR
portals are an initiative promoted by the Portuguese
government that is a part of a broader e-government
strategy seeking to facilitate services and
communications between public services and the
citizens. The most important initiative is the “Portal
do Utente” (User’s Portal) a national EHR portal,
created by the Ministry of Health that allows all
Portuguese citizens to schedule appointments with
their general practitioner, obtain electronic medical
prescriptions, access medical records and exam
results, and share information with health care
providers (Rodrigues et al., 2013; Pereira, 2012).
With more than half a million users already
registered, the objective of the Ministry of Health is
to make this portal a primary point of contact
between the patient and the national health care
system that in Portugal provides coverage to the
entire population (Rodrigues et al., 2013; Pereira,
2012).
Understanding whether or not the current
adoption models are suitable to a particular field of
387
Tavares J. and Oliveira T..
Electronic Health Record Portal Adoption by Health Care Consumers - Proposal of a New Adoption Model.
DOI: 10.5220/0004947003870393
In Proceedings of the 10th International Conference on Web Information Systems and Technologies (WEBIST-2014), pages 387-393
ISBN: 978-989-758-023-9
Copyright
c
2014 SCITEPRESS (Science and Technology Publications, Lda.)
interest, by verifying and proposing the necessary
changes and extensions (Alvesson and Kaerreman,
2007; Martins et al., 2014; Miltgen et al., 2013) is a
vital topic in the area of information system (IS)
acceptance and use (Venkatesh et al., 2012). In our
study we will examine these assumptions in the field
of e-health technology use and acceptance by the
health care consumers and propose a new research
model based on the unified theory of acceptance and
use of technology in a consumer context (UTAUT2)
by integrating a second-order construct based on the
Concern for Information Privacy (CFIP) framework
and a new moderator, chronic disability (Angst and
Agarwal 2009; Millard and Fintak, 2002).
The paper proceeds as follows: First we review
the literature concerning information technology
(IT) adoption models regarding consumer health
care. We then present a research model to analyze
ERHs portals for the health care consumer. Finally
we discuss the issue and present conclusions.
2 THEORETICAL
BACKGROUND
There have been several theoretical models
developed from theories in psychology, sociology,
and consumer behavior employed to explain
technology acceptance and use (Venkatesh et al.,
2012). The goal of this study is to focus specifically
on the e-health adoption in the perspective of the
health care consumer, so it is of the utmost
importance to review the literature in this particular
field. Adoption of e-health technologies by the
patients is clearly a very important topic in IS. The
adoption of e-health technologies by health care
professionals still requires more attention and
research due to the limited number of studies
reported in the literature to date (Angst and Agarwal,
2009; Or and Karsh, 2009).
When studying e-health and health care adoption
by health care professionals the most common
adoption models used are the technology acceptance
model (TAM) (Dunnebeil et al., 2012; Ketikidis et
al., 2012) and UTAUT (Chang et al., 2007; Yi et al.,
2006). Evaluating the studies published in the field
of consumer health information technology adoption
and more specifically in the use and adoption of e-
health tools by the health care consumer, most
studies use TAM or extensions of TAM (Or and
Karsh, 2009; Wilson and Lankton, 2004). TAM was
designed and tailored in IS contexts to predict
information technology acceptance and usage on the
job (Venkatesh et al., 2003). Independent attempts
by several researchers to expand TAM in order to
adapt it to the constantly changing IT environments,
like e-health, has led to a state of theoretical chaos
and confusion in which it is not clear which version
of the many iterations of TAM is the commonly
accepted one (Wilson and Lankton, 2004; Benbasat
and Barki, 2007). UTAUT formulate a unified
model that integrates elements of eight models in the
field of IT acceptance. The eight models are the
theory of reasoned action (Fishbein and Ajzen,
1975); the technology acceptance model (Davis,
1989); the motivational model (Davis et al., 1992);
the theory of planned behavior (Ajzen, 1991); a
model combining the technology acceptance model
and the theory of planned behavior (Taylor and
Todd, 1995); the model of PC utilization (Thompson
et al., 1991); the innovation diffusion theory
(Rogers, 1995), and the social cognitive theory
(Compeau et al., 1999; Compeau and Higgins,
1995). The R
2
obtained with UTAUT was superior
to any of the individual models including TAM
(Venkatesh et al., 2003).
Although UTAUT provides better results than
TAM and other IS adoption models, the focus of
UTAUT is also the employee technology acceptance
at individual level (Venkatesh et al., 2003;
Venkatesh et al., 2012). Ideally, we then need a
model tailored to the consumer use context, and in
this specific field UTAUT2 was developed with this
goal, obtaining excellent results (Venkatesh et al.,
2012). When compared with UTAUT in the
consumer use context, the new UTAUT2 model
obtained higher R
2
, and is better able to explain the
reasons behind the adoption (Venkatesh et al.,
2012). If UTAUT2 outperformed UTAUT in the
consumer use context, we believe that UTAUT2
could be used as the standard starting model for
studying e-health adoption.
E-health technology adoption differentiates from
IT adoption in general due to the sensitive topics
and issues related to health status of an individual,
making the drivers of adoption in e-health different
from other IT technologies (Angst and Agarwal,
2009). In health care, confidentiality is the ethical
principle that a health professional will keep
confidential all information relating to a patient,
unless the patient consents to disclosure (Bauer,
2002). Several studies point out that awareness of
lack of confidentiality and privacy concerns may
reduce the adoption of e-health tools by the patients
and health care consumers (Angst and Agarwal,
2009; Fisher and Clayton, 2012; Fogel and Nehmad,
2009; O'Donnell et al., 2011). Studies focusing
specifically on EHR portals show that patients are
WEBIST2014-InternationalConferenceonWebInformationSystemsandTechnologies
388
highly concerned about privacy of their personal
medical records (Angst and Agarwal, 2009).
Literature review identified that patients with
chronic illness, severe illness, or disability are more
likely to use e-health technologies if they have the
resources and support available. It is paramount to
understand that it is only if patients who are
chronically or severely disabled have the conditions
and resources available, will they access the health
record portals. (Millard and Fintak, 2002; Renahy et
al., 2008).
3 RESEARCH MODEL
UTAUT2 was developed as an adoption model
providing the general factors of IT adoption in the
consumer use. However, according to Venkatesh et
al. (2012) in certain situations where the technology
may be influenced by specific factors it may be
necessary to make extend the model with new
constructs, moderators, and relationships. We
therefore identified key additional constructs and
relationships based on the literature review that are
specific to IT health care adoption to be integrated
into UTAUT2, thus tailoring it to e-health consumer
context, more specifically to study the adoption of
EHR portals. We did this by (1) identifying key
constructs from earlier research in IT health care
consumer adoption (confidentiality) and by (2)
adding a new moderator specific to IT health care
use (chronic disability). Figure 1 illustrates the new
research model.
3.1 UTAUT2 Model
Performance expectancy is defined as the degree to
which using a technology will provide benefits to
consumers in carrying out certain activities
(Venkatesh et al., 2003). Literature review indicates
that health care consumers tend more to adopt e-
health technologies that provide clear benefits, such
as obtaining an electronic medical prescription via
EHR portals (Alpay et al., 2010; Arsand and
Demiris, 2008; Keselman et al., 2008).
P1. Performance Expectancy will Positively
Influence Behavioral Intention.
Effort expectancy is the degree of ease related to
consumers’ use of technology (Venkatesh et al.,
2003). The easier that consumers can understand and
use an e-health technology, the greater is the
probability that they will adopt it (Alpay et al., 2010;
Keselman et al., 2008).
Figure 1: The Research Model.
P2. Effort Expectancy will Positively Influence
Behavioral Intention.
Social influence is the extent to which consumers
perceive that others who are important to them (e.g.,
friends and family), believe they should use a
particular technology (Venkatesh et al., 2012). In the
case of e-health this can be also an important
construct, since people that share the same diseases
(e.g., Multiple Sclerosis) or the same health
condition (e.g., obesity) tend to be influenced by
what others in the same conditionuse and do (Fisher
and Clayton, 2012; Thackeray et al., 2013).
P3. Social Influence will Positively Influence
Behavioral Intention.
Facilitating conditions refer to consumers’
perceptions of the resources and support available to
execute a behavior (Venkatesh et al., 2003). In the
specific case of e-health this construct can be very
important due to the fact that patients and disabled
people may have special needs that healthy people
do not (Arsand and Demiris, 2008; Millard and
Fintak, 2002).
P4. E-health Platforms with Greater Resources and
Support Available (Facilitating Conditions) are
more likely to Positively Influence Behavioral
Intention and Use Behavior.
Hedonic motivation is defined as intrinsic
motivation (e.g., enjoyment) and has been included
as a key predictor in much of the reported consumer
behavior research (Venkatesh et al., 2012). Dealing
and obtaining information about our health status by
using e-health technologies may be a rewarding
ElectronicHealthRecordPortalAdoptionbyHealthCareConsumers-ProposalofaNewAdoptionModel
389
process, or in some cases may not be when a patient
is dealing, for example, with cancer (Lee et al.,
2010).
P5. Hedonic Motivation will Positively or Neutrally
Influence Behavioral Intention.
Price value: in a consumer use environment, price is
also a relevant factor, as unlike workplace
technologies, consumers must bear the costs related
with the purchase of devices and services
(Venkatesh et al., 2012). If a patient can obtain his
medical prescription via an EHR portal, he can save
transportation money by avoiding a trip to a health
center or hospital. The better the perception a health
care consumer has about the “price value” of an e-
health technology (i.e., that it can help him save
money), the more likely it is that he will adopt it
(Alpay et al., 2010; Metaxiotis et al., 2004).
P6. Price Value will Positively Influence Behavioral
Intention.
Habit can be defined as the extent to which people
tend to execute behaviors automatically because of
learning (Venkatesh et al., 2012). We can expect that
habit will positively influence e-health adoption, as
it does in other IT adoption fields, since habit is a
concept that should not be specific to an IT
technology (Venkatesh et al., 2012).
P7. Habit will Influence Positively Behavioral
Intention and use Behavior.
Age, gender and experience are theorized to
moderate various UTAUT2 relationships (Venkatesh
et al., 2012). Literature review indicates that in IT
technologies in general and specifically in e-health,
younger people and women tend to have the habit to
use more e-health technologies (Millard and Fintak,
2002; Thackeray et al., 2013; Venkatesh et al.,
2012). According to the literature review, people
with less experience in using a technology tend to be
more influenced by experience (Venkatesh et al.,
2012).
P8. Age and Gender will Moderate the Effect of
Habit on Behavioral Intention, such that the Effect
will be Stronger for Younger Women.
P9. Age and Gender will Moderate the Effect of
Habit on Use Behavior, such that the Effect will be
Stronger for Younger Women.
P10. Experience will Moderate the Effect of
Behavioral Intention on Use, such that the Effect
will be Stronger for Consumers with Less
Experience.
3.2 e-Health Extension
Smith, Milberg, and Burke (1996) developed and
tested the CFIP construct to measure attitudes and
beliefs about individual information privacy related
to the use of personal information in a business
setting. They conceptualized CFIP as being
composed of four distinct, yet correlated, latent
factors: collection, errors, unauthorized or improper
access, and secondary use. Collection is the concern
that an extensive amount of personal information is
being collected and stored in databases (Smith et al.,
1996). Errors are directly linked with the concern
that protection against deliberate and accidental
error in personal data is inadequate (Smith et al.,
1996). Unauthorized access is the concern that data
about individuals is available to people not
authorized to view or work with these data (Smith et
al., 1996). Secondary use is the apprehension that
information is collected from individuals for one
purpose but is used for another secondary purpose
without authorization from the individuals (Smith et
al., 1996). Stewart and Segars (2002) expanded upon
the Smith et al. (1996) study and not only validated
the multidimensional nature of the CFIP construct,
but also found support for the hypothesis that a
second-order factor structure is empirically valid,
thus settling the complexity of an individual’s
concern for information privacy with direct
influence in the behavioral intention to use a
technology (Stewart and Segars, 2002). Angst et al.
(2009) studied the adoption of EHRs in the presence
of privacy and used in their study the CFIP
framework as a second order factor structure. To
measure CFIP Angst et al. (2009) adapted the scale
developed by Smith et al. (1996). Minor changes
were made to their instrument to reflect privacy
concerns relative to health data instead of corporate
data. Based on the earlier use of the CFIP
framework in e-health, we add CFIP as a predictor
of health consumer behavioral intention to use a
technology.
P11. CFIP will Positively Influence Behavioral
Intention.
Chronic disability is an incapacitating situation (e.g.,
chronic illness) that affects a patient permanently or
for long-term periods. Review of literature points
out that patients with chronic illness or disability are
more likely to use e-health technologies if they have
the resources and support available (facilitating
conditions) (Millard and Fintak, 2002; Thackeray et
al., 2013).
P12. We can Theorize that Chronic Disability is a
WEBIST2014-InternationalConferenceonWebInformationSystemsandTechnologies
390
Positive Moderator of Facilitating Conditions to
Explain Behavioral Intention.
4 METHODOLOGICAL
IMPLICATIONS AND
VALIDATION APPROACHES
To test the propositions suggested here, we will
develop a pilot study with a sample of 30 users of
EHR portals. The final questionnaire will be
administered in Portuguese. To ensure translation
equivalence we will translate the English
questionnaire to Portuguese and then back to
English; these tasks will be executed by professional
translators (Brislin, 1970). We will test the
hypothesized relationships among the constructs
using structural equation modeling (SEM). There are
two families of SEM techniques (Henseler et al.,
2009): covariance-based techniques and variance-
based techniques. Partial least squares (PLS) is a
variance-based technique and will be used in this
research since, (i) the research model has not been
tested in the past; (ii) the research model is
considered complex. The theoretical approach
developed in this study should be implemented first
in Portugal focusing in the EHR portals. The data
will be collected in EHR portals managed by the
Portuguese Ministry of Health, allowing a vast
coverage of the Portuguese population since
Portugal has a National Health System that covers
all of the population. The eligibilities criteria’s to
answer the questionnaire are: Portuguese nationality
and age equal to or greater than 18 years old. Our
objective is to collect a final sample with more than
300 questionnaires.
5 LIMITATIONS AND FUTURE
RESEARCH
This study is in its first theoretical concept, in which
an initial model is suggested based on the literature
review and conceptual reasoning. The next step is
the application and validation of the model to a set
of health care consumers, in order to test the
developed framework and directly assess its
explanatory and predictive power. Future studies
may evaluate other relationships that were not
foreseen in this model and that will improve the
ability to explain the dependent variables. Thus, this
study opens up other options for future research.
Refinement of the constructs and measures is one of
the possibilities. Another option is the investigation
of more complex relationships between the
independent and dependent variables of the model.
Testing this model with other e-health technologies
and in other countries that may be more or less
developed than Portugal in e-health use are options
that can also bring added value.
6 CONCLUSIONS
Understanding the acceptance and use of EHR
portals by health care consumers should bring strong
benefits for the future sustainability of the Heath
Care System, which will enjoy more efficient use of
resources. Thus, the aim of this study is to identify a
set of determinants of adoption of EHR portals by
health care consumers. To realize this goal we
suggest a research model based on UTAUT2, adding
new constructs (CFIP) and a new moderator of
chronic disability. We designate this new set of
constructs and the new moderator “e-health
extension to UTAUT2”. We also expect this study to
provide a theoretical framework that is a foundation
and a starting point for future research on the
adoption of e-health by health care consumers.
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