perceived quality of e-health services: a conceptual scale...
TRANSCRIPT
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Perceived quality of e-health services: A conceptual scale development of e-health
service quality based on the C-OAR-SE approach
Karsten Hadwich
University of Hohenheim, Stuttgart, Germany
Dominik Georgi
Frankfurt School of Finance and Management, Frankfurt am Main, Germany
Sven Tuzovic
Pacific Lutheran University, Tacoma, WA, USA
Julia Buettner
Roche Diagnostics AG, Rotkreuz, Switzerland
Manfred Bruhn
University of Basel, Basel, Switzerland
Published in:
International Journal of Pharmaceutical and Healthcare Marketing
Vol. 4, No. 2, 2010, pp. 112-136
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Purpose – Health service quality is an important determinant for health service satisfaction
and behavioral intentions. The purpose of this study is to investigate requirements of e-health
services and to develop a measurement model to analyze the construct of “perceived e-health
service quality”.
Design/methodology/approach – The present study adapts the C-OAR-SE procedure for
scale development by Rossiter (2002). The focal aspect is the “physician-patient relationship”
which forms the core dyad in the healthcare service provision. Several in-depth interviews
were conducted in Switzerland; first with six patients (as raters), followed by two experts of
the healthcare system (as judges). Based on the results and an extensive literature research,
the classification of object and attributes is developed for this model.
Findings – The construct e-health service quality can be described as an abstract formative
object and is operationalized with 13 items: accessibility, competence, information,
usability/user friendliness, security, system integration, trust, individualization, empathy,
ethical conduct, degree of performance, reliability, and ability to respond.
Research limitations/implications – Limitations include the number of interviews with
patients and experts as well as critical issues associated with C-OAR-SE. More empirical
research is needed to confirm the quality indicators of e-health services.
Practical implications – Health care providers can utilize the results for the evaluation of
their service quality. Practitioners can use the hierarchical structure to measure service quality
at different levels. The model provides a diagnostic tool to identify poor and/or excellent
performance with regard to the e-service delivery.
Originality/value – This study contributes to knowledge with regard to the measurement of
e-health quality and improves the understanding of how customers evaluate the quality of e-
health services.
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Introduction
The importance of the Internet in the public health sector has increased continuously over the
last years. Reasons for the rising demand of healthcare e-services (also referred to as e-health)
can be attributed to a number of factors. Bliemel and Hassanein (2007, p. 53) point out that
the “Internet has enabled consumers to become more proactive in managing their health.”
Searching for health or medical information is one of the most popular online activities for
healthcare consumers (Akerkar and Bichile 2004; Gallant et al. 2007). Surveys by the Pew
Internet & American Life Project find that between 75% and 80% of American Internet users
have used the Internet to obtain health information, particularly those in the 55% of
households with broadband connections (Fox 2006; 2008). Besides convenience and better
accessibility of obtaining information online, some studies find that health consumers prefer
the anonymity of the Internet compared to answering personal questions to a physician
(Anderson et al. 2003; Borowitz and Wyatt 1998). Other motivations of patients to seek
information online relate to the fact that medical care is inherently characterized as a
“credence quality” (Lovelock and Wirtz 2007) with associated uncertainties about diagnosis,
care, etc. Consumers may thus have a lack of trust, e.g., in their doctor’s competency, or feel
discomfort of discussing the issue with the physician or experience frustration with failed or
ineffective treatment (Eysenbach and Diepgen 1999). For instance, a 2002 Harris Interactive
poll indicates that 75% of adults prefer e-mail communication with their healthcare providers
(Conhaim and Page 2003), however, only a small portion of patients (6% or fewer) actually
have e-mailed them (Baker et al. 2003; Sittig et al. 2001). Finally, fewer costs are involved for
the patient. For instance, patients that engage in online transactions or electronic
communication such as e-mail or chat do not have to travel to their physician or pharmacy.
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However, despite these benefits, certain stakeholders have great concerns regarding the
provision of e-health services. First, physicians and academics are concerned with the quality
of health information that is posted online (Bliemel and Hassanein 2007). A meta-study by
Eysenbach et al. (2002) who review 79 studies suggests that a majority (70%) of these
research studies reported a problem with quality of health information on the Internet. For
instance, the reliability and integrity of health information online may vary from useful to
dangerous information (Cullen 2006). Second, physicians are concerned with the effects on
the traditional physician-patient-relationship. Even though traditional consultation and
treatment will never become redundant (Ball and Lillis 2001) many physicians consider e-
health services a direct attack on their service competence. Third, e-health services such as
electronic patient-physician communication gives rise to new challenges for physicians. For
example, some authors point out the provider’s inability to manage large electronic message
volumes (Kassirer 2000; Neinstein 2000). The consequence is seen in greater administrative
burden for physicians, e.g. additional time needed to answer e-mails from patients, which
would affect the time for treating patients negatively (Lerer and Rowell 2000). Moreover, the
absence of the physical presence of the patient can present problems for accurate diagnosis
and treatment alternatives (Mandl et al. 1998). Finally, some scholars point out safety issues
of e-health services (Hodge et al. 1999) as well as privacy concerns since health-related
information is considered highly sensitive data (Eng 2001).
The missing piece in the discussion about healthcare e-services, however, is the consumer.
Bliemel and Hassanein (2007, p. 54) criticize that “prior research has focused on the
information and its authors to determine the quality from experts’ perspectives.” The e-health
consumer (or e-patient) is generally disregarded in this debate, even though patients as online
users influence widely the success or failure of e-health services. For example, Bliemel and
Hassanein (2007) suggest that both the content of health web pages and the information
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retrieval system influence the consumers’ experience with the information found online. They
further argue that the knowledge about patients’ perception of online information in the health
context “(…) has great implications, because of the seriousness of the consequences when
consumers act upon this information” (Bliemel and Hassanein 2007, p. 54). Furthermore,
“consumers’ expectations of the service level they receive from the healthcare system have
also risen as they educate themselves on new medical treatment” (Bliemel and Hassanein
2007, p. 54). Since it is most likely that consumers and experts evaluate quality of healthcare
e-services differently, it is important to determine the relevant drivers of e-health quality from
a patient perspective. Furthermore, e-health service quality may have a positive influence on
patients satisfaction and loyalty. For instance, Li and Suomi (2009) who investigate e-service
quality in the electronic marketplace argue that the improvement of e-service quality to satisfy
and retain customers is becoming a challenging issue. Dagger, Sweeney and Johnson (2007)
demonstrate that health service quality is an important determinant for health service
satisfaction and behavioral intentions which underscores the significance of service quality as
a decision-making variable. Based on this background, the objective of this study is to
identify requirements of e-health services and to develop a measurement model to analyze the
construct of “perceived e-health service quality”. The focal aspect in this research will be on
the “physician-patient relationship” which forms the core dyad in the healthcare service
provision.
e-Health Services in the Physician-Patient Relationship
Classification of healthcare e-services
According to Car et al. (2008, p. 7), “eHealth is a relatively new and rapidly evolving field
and so many of the concepts, terms and applications are still in a state of flux.” Furthermore,
there is no agreed definition of e-health so far. In some cases the term refers to telemedicine
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or health informatics only. Others see telemedicine as one of many applications of e-health
services (Berger-Kurzen 2004). Meyers et al. (2002) state that e-health is the health-related
industry made possible by the Internet. Eng (2001, p. 20) defines e-health as “the use of
emerging information and communication technology, especially the Internet, to improve or
enable health and healthcare.” Car et al. (2008, p. 7) develop an inclusive definition based on
Eysenbach (2001) describing e-health as “an emerging field of medical informatics, referring
to the organization and delivery of health services and information using the Internet and
related technologies (…).” Some scholars point out that this includes in particular
interpersonal computer-mediated communications between service providers and their
patients, such as e-mail, chat and discussion forums (Klein 2007; Wilson 2003).
To better understand the complexity of e-health services it is useful to distinguish four
different areas of e-health, the four Cs: commerce, content, care, and connectivity (Meyers et
al. 2002):
e-health commerce: This refers to products and services that are researched and paid for
online. One example would be e-Pharmacies offering medications online. Other services
could include links to health publications, or, more progressively, health insurance
products (Meyers et al. 2002).
e-health content: This refers to offerings of health information via an electronic exchange.
Patients can able to inform themselves on health portals, including online patient
educational documents and video presentations. The information is mostly standardized as
it addresses the need of the general population. Other examples may include
administrative linkages to appointment systems, lab results, and claims management.
e-health care: Health care is evolving through the development of “virtual services and
information-rich bedside services” (Meyers et al. 2002). Internet capabilities will be useful
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for providers to extend existing clinical treatment capabilities. For example, providers can
make virtual house calls using medical devices that report information through in-home
monitors linked to the Internet (Meyers et al. 2002). Other options include interactive
home monitoring systems that monitor continuously patients’ vital functions at home,
transmitting real-time information, and retrospective patient data, via wireless point-of-
service communication to health professionals located outside the home (Meyers et al.
2002).
e-health connectivity: This refers to Internet-based services that link the various
participants in the healthcare marketplace (Meyers et al. 2002). Examples include virtual
customer service, online access of claim history and payment, transmission of electronic
patient data among members of the health care system, e.g. among physicians and
insurance companies.
Kirchgeorg and Lorbeer (2002) also address these four Cs but add a fifth C: communities. For
example, consumers can join discussion forums and online chats to exchange information
about medical problems, e.g. diabetes, depression, etc. Overall, the 5 Cs differ with regard to
the degree of individualization as well as the degree of provider-patient interaction (Figure 1).
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Figure 1: Classification of e-health services (based on Kirchgeorg and Lorbeer 2002, p. 590)
It is reasonable to assume that the implementation of e-health services becomes more difficult
as the degree of individualization and interaction of service delivery increases. Furthermore,
legal regulations and privacy concerns regarding online health-related patient data may
restrain the implementation of services in the areas of care and connectivity (Lerer and
Rowell 2000).
The Physician-Patient Relationship as Core Dyad in Healthcare
The present study focuses on physician-patient relationships. According to a document by
American Healthways (2004, p. iv), the “patient-physician relationship is fundamental to
providing and receiving excellent care, to the healing process and to improved outcomes.” In
other words, the physician-patient relationship forms the core dyad in the healthcare service
provision. Traditionally, the physician-patient relationship has been based on a paternalistic
model that assumes physician authority (Dolgin 2005). However, in recent years the
Content
Community
Care
Connectivity
Degree of interaction
Interactive
Independent
Commerce
De
gre
eo
f in
div
idu
aliz
atio
n
sta
nd
ad
ize
d
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traditional paternalistic relationship is being replaced. Patients are seen increasingly as
consumers of healthcare, similar to commercial market environments (American Healthways
2004; Dolgin 2005; Ouschan et al. 2006). As the landscape of healthcare is changing, it is
important to analyze how information and communication technology, in particular the
Internet, can be utilized to contribute to both medical professionalism and quality of care.
While the number of e-health applications is potentially endless, three main domains can be
distinguished (Car et al. 2008, p. 8):
storing, managing and sharing data;
informing and supporting medical decision-making; and
delivering expert professional and or consumer care remotely.
In the following sections we will discuss the literature relevant to the development of health
service quality and its application to the field of e-health.
Literature Review and Theoretical Background
Healthcare industry and service quality
Healthcare has been one of the fastest growing sectors in the service economy (Andaleeb
2001; Dagger, Sweeney and Johnson 2007). Total U.S. healthcare expenditures are expected
to increase to $2.72 trillion in 2010 from $2.39 trillion in the previous year, while annual
increases are forecasted to average about 7% for the next 10-years (Rickman 2009). With
respect to achieve competitive advantage, increased patronage and long-term profitability,
service quality has become increasingly important as a corporate strategy for many healthcare
organizations (Dagger, Sweeney and Johnson 2007). While traditionally the healthcare sector
has used objective criteria (e.g. mortality or morbidity rates) to assess quality of medical care,
over the last two decades researchers have drawn the attention to the role of patients in
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defining the meaning of quality in healthcare (e.g. Dagger, Sweeney and Johnson 2007,
Donabedian 1992; Jun, Peterson, and Zsidisin 1998; O’Connor, Trinh, and Shewchuk 2000).
Although a large amount of research has been published in the area of service quality and its
measurement (e.g. Brady and Cronin 2001; Carrillat, Jaramillo and Mulki 2007; Grönroos
1984; Le Blanc and Nguyen 1988; Parasuraman, Zeithaml and Berry 1985, 1988; Saleh and
Ryan 1992), some scholars argue that “much of this research has focused on the development
of generic service quality models” (e.g. the SERVQUAL scale developed by Parasuraman,
Zeithaml and Berry 1985, 1988) whereas only “few studies, in comparison, have focused on
the development of context-specific service quality models” (Dagger, Sweeney and Johnson
(2007, p. 124). The authors further point out that studies that have applied the widely used
SERVQUAL scale (Parasuraman, Zeithaml and Berry 1985, 1988) in the context of
healthcare services have led to mixed results, ranging from the original 5-factor structure
(Rohini and Mahadevappa 2006), to 6 and 7 dimensions (Headley and Miller 1993; Lytle and
Mokwa 1992) to even 12 dimensions (Licata, Mowen and Chakraborty 1995).
Examining the healthcare literature, several frameworks can be found for assessing the quality
of care (e.g. Brook and Williams 1975; Donabedian 1966, 1980; Wiggers et al. 1990; Zineldin
2006). Dagger, Sweeney and Johnson (2007) conclude that a comparison of dimensions
identified in the healthcare literature shows considerable overlap with findings in the
marketing literature. The authors develop a new scale to measure health service quality. Their
findings suggest that “customers base their perceptions of health service quality on four
primary dimensions: interpersonal quality, technical quality, environment quality and
administrative quality.” (Dagger, Sweeney and Johnson 2007, p. 135).
Development of e-service quality measures
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With the adoption of e-services in business, the importance of measuring e-service quality has
become increasingly more important, and “e-service quality posits to be a hot topic in
research field” (Li, Liu and Suomi 2009, p. 3). Most researchers that develop e-service quality
scales have taken a combination of traditional service quality dimensions, often based on the
SERVQUAL instrument, and web interface quality dimensions as a starting point (Li, Liu and
Suomi 2009; Li and Suomi 2009). Judging from the existing literature, studies on e-service
quality have been conducted in different domains; primarily in the context of online retailing,
online shopping, online financial service and e-services (for a literature overview see Li and
Suomi 2009). Yet, Wolfinbarger and Gilly (2003) describe the existing research as
fragmented. Furthermore, some researchers argue that recent studies show more different
dimensions on s-service quality (Li, Liu and Suomi 2009; Li and Suomi 2009). In order to
develop a scale for e-health service quality, it is necessary to combine and synthesize the
existing dimensions. Table 1 summarizes the literature review with regard to the development
of e-service quality measures, illustrating the main quality dimensions that have been
identified. While the number of dimensions and their description differ, a close look shows
that most of the descriptions are consistent.
Table 1: A review of dimensions of e-service quality
Bar
nes
and
Vid
gen
2001
Cox
and
Dal
e 20
01
Jun
and
Cai
200
1
Zei
tham
l et a
l. 20
02
Loi
acon
o et
al.
2002
Yan
g an
d Ju
n 20
02
Wol
finb
arge
r an
d G
illy
200
3
Yan
g et
al.
2003
Van
Rie
l et a
l. 20
03
Kuo
et a
l. 20
05
Par
asur
aman
et a
l. 20
05
Kim
et a
l. 20
06
Lin
200
7
Li a
nd S
uom
i 200
9
Li e
t al.
2009
Reliability X X X X X X X X X XAccessibility (availability, access, contact)
X X X X X X X X X
Responsiveness (speed of delivery, queue
X X X X X X X X X X X X
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management, response time)
Ease of use (ease of understanding, convenience, intuitive operations)
X X X X X X
Fulfillment (performance, accuracy, functional benefit, compensation)
X X X
Assurance (credibility, competence, reputation)
X X X
Tangibles (design, features, usability, structure, layout, aesthetics, appearance, user interface, website design, linkage)
X X X X X X X X X X X X
Personalization (customization, differentiation, relative advantage, attractiveness of selection, product portfolio)
X X X X X
Trust X X X X
Empathy (emotional benefit, courtesy)
X X X X X
Information Quality (consistency, completeness, content, understanding, information)
X X X X X X X
Communication (support, contact, customer service, collaboration, feedback / complaint management)
X X X X X X
Innovativeness (continuous improvement)
X X
Security / Privacy X X X X X X X X X X X
Efficiency X X
In addition to the previous studies, a number of scholars have investigated healthcare-specific
concerns regarding the provision of e-health quality. Eysenbach et al. (2002) in their meta-
analysis conclude that quality of consumer health information on the Internet has been
expressed in terms of accuracy, completeness, readability, design, disclosures, and references.
They argue that the term quality requires a better operational definition. Within the physician-
patient relationship, a survey shows that user friendliness and the timeliness of the provider
response correlated positively with patients’ satisfaction (Liederman and Morefield 2003).
Bliemel and Hassanein (2007) find that consumers’ satisfaction with health information
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online is best determined by the content quality (that is, the information on a website) and
technical adequacy of the website. Several authors also discuss the role of trust in the context
of online health services, e.g. user trust of hospital websites (Gallant et al. 2007; Kind et al.
2004; Rosenvinge et al. 2003). Among various sources on the Internet, the most trusted source
for online information is the personal doctor (Kind et al. 2004). Another important factor for
the success of e-health services is trust in the security of patient data and the assurance of
privacy (Hodge et al. 1999). Bernhardt et al. (2002) argue that privacy and confidentiality are
key concerns of patients with regard to electronic communication with their provider.
Conceptual scale development
As outlined in the previous sections, numerous studies have investigated the constructs of
service quality and e-service quality. While service quality has been seen commonly as a
second-order factor (Grönroos 1984; Parasuraman, Zeithaml and Berry 1988), several
scholars have recently described it as a third-order factor (Brady and Cronin 2001; Dabholkar,
Thorpe and Rentz 1996; Dagger, Sweeney and Johnson 2007). Within the German marketing
literature the position has been established to differentiate service quality in three primary
dimensions: potential quality, process quality and outcome quality (Bruhn and Stauss 2002;
Corsten 1985, 2001; Maleri 1994; Steffen 2006). The origin of this perspective is based on
work by Donabedian (1966, 1980) who conceptualizes quality of care in hospitals. He
distinguishes three elements: structure, process and outcome. Gleason and Stiff (1985) argue
similarly in the context of legal services. The term ‘potential quality’ has not been prominent
in the extant Anglo-American literature; however, certain aspects of it are inherent in
commonly used terms, such as ‘store atmospherics’ (Donovan and Rossiter 1982) and
‘servicescape’ (Bitner 1992, 2000). Tuzovic (2008) adapts this view to describe service
quality of real estate services as a sequence of potential quality, process quality and outcome
quality, in which potential quality combines the quality of the virtual and physical service
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environment. In the context of healthcare services potential quality refers to cues that serve as
‘surrogate’ quality indicators. Process quality reflects the interaction between actors in a
physician-patient relationship. Outcome quality describes the outcome of the service process.
Following the opinion in literature that service quality in health care is perceived at multiple
levels of abstraction (Dagger, Sweeney and Johnson 2007), we expect that e-health service
quality in the physician-patient relationship consists of primary and secondary dimensions as
well. Based on the literature review we propose that eleven quality indicators that can be
grouped in three quality dimensions:
Potential quality: accessibility and competence;
Process quality: usability/user friendliness, information, security, trust,
individualization, system integration;
Outcome quality: degree of performance, reliability, ability to respond
Methodology
Research design
The authors of this study have chosen to use the C-OAR-SE scale development procedure.
Until today, empirical marketing research has been influenced strongly by the work of
Churchill (1979), especially with regard to measuring marketing constructs (Bergkvist and
Rossiter 2007; West 2006). For example, Bergkvist and Rossiter (2007, p. 175) state that “In
the 28 years since Churchill’s article, academics have increasingly used multiple items to
measure every marketing construct.” They further criticize that “it is virtually impossible to
get a journal article accepted in marketing unless it includes multiple-item measures of the
main constructs” (Bergkvist and Rossiter 2007, p. 175). More recently, Rossiter proposed a
different approach. Published 2002 in the International Journal of Research in Marketing
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(IJRM) he presents a six-step procedure for scale development, labeled with the acronym C-
OAR-SE. In this article Rossiter argues in favor of a single-item measurement approach
instead of the commonly used multi items approach by Churchill. He suggests that single
items are sufficient if object and attribute can be conceptualized as concrete and singular
(Bergkvist and Rossiter 2007; Rossiter 2002). Other scholars however, such as
Diamantopoulos, argue contrary pointing out that “use of single-item measures and
construction of formed attribute scales” is a weakness of Rossiter’s approach
(Diamantopoulos 2005, p. 8). Yet, Diamantopoulos acknowledges that the C-OAR-SE
procedure offers a “breath of fresh air in the marketing literature on measure development”
(Diamantopoulos 2005, p. 1) and “encourages a much more flexible and open-minded
approach towards scale development and releases researchers from the shackles of
conventional test theory” (Diamantopoulos 2005, p. 8).
The sequence of C-OAR-SE involves six steps: (1) construct definition, (2) object
classification, (3) attribute classification, (4) rater identification, (5) scale formation, and (6)
enumeration.
(1) Construct definition: The first step in the process of scale development involves the
conceptual definition of the construct. This definition should specify the object, the
attribute, and the rater entity (Diamantopoulos 2005; Rossiter 2002).
(2) Object classification: This refers to the classification of the focal object in one of three
categories: concrete singular, abstract collective and abstract formed (Diamantopoulos
2005; Rossiter 2002). This step is critical since the measurement of constructs would
not require multiple items if object and attribute can be conceptualized as concrete and
singular.
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(3) Attribute classification: This is to classify the attribute of the construct, that is, the
“dimension on which the object is being judged” (Diamantopoulos 2005, p. 4; Rossiter
2002, p. 313). Three distinct types of attributes can be identified: concrete, formed,
and eliciting. This step clarifies if constructs can be measured by a single item. Thus,
it tells which measurement model is to be used.
(4) Rater identification: According to Rossiter “constructs differ depending on whose
perspective they represent” and he concludes that “the rater entity is part of the
construct” (Rossiter 2002, p. 318, emphasis in original). Three types of rater entity can
be distinguished (individual raters, expert raters, group raters) which require different
approaches for reliability assessment (Diamantopoulos 2005).
(5) Scale formation: This refers to the combination of object and attributes to a common
scale.
(6) Enumeration: Due to different combinations of object and attribute classifications,
Rossiter proposes six distinct ways for deriving a total score from the scale items. The
type of scales varies “from a single-item score equaling the total score, to two types of
index, a double index, an average, and averages which are then indexed” (Rossiter
2002, p. 324).
Rossiter (2002, pp. 326 and 332) emphasizes that the C-OAR-SE procedure to scale
development relies strongly on content validity. This is “partly grounded on C-OAR-SE’s
designation as a rationalist procedure […] and partly on a dismissal of alternative forms of
validity” (Diamantopoulos 2005, p. 6). To achieve content validity, the C-OAR-SE procedure
stresses to conduct pre-interviews with raters and the involvement of expert judges throughout
the process.
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The present study adapts the C-OAR-SE procedure for scale development by Rossiter (2002).
An extensive literature review is also conducted; a step that is not mentioned explicitly in
Rossiter’s C-OAR-SE procedure. The primary focus of e-health service conceptualization is
on the classification of the object as well as the attribute. According to Rossiter, the
classification requires the inclusion of a sample of the final rater entity. Following C-OAR-
SEs procedure, this study utilizes in-depth interviews with patients (as raters) as well as
experts of the healthcare system (as judges). The construct definition is as follows: Quality of
e-health services within the physician-patient-relationship, perceived by the service recipient
(the patient). Raters are thus patients. E-health services are the object of the research and the
attribute is identified as service quality.
Data collection
In-depth interviews were conducted with six patients in Switzerland who were contacted in
person. Based on the assumption that every human is a potential recipient of healthcare
services, the selection of interviewees did not follow any specific guidelines. A key criterion
was that none of the participants was both service recipient and service provider. Other than
that, the objective was to have a diverse sample with regard to age and socio-economic
factors. Further, both experienced and inexperienced users of e-health services were selected.
Table 2 summarizes the basic data of the sample.
Table 2: Sociodemographic data of the sample Interview 1 2 3 4 5 6 Gender Male Female Male Male Female Male Age 27 52 55 25 30 26 Education University Apprentice-
ship University of Applied Science
Bachelor University Master
Occupation Employee Tax accountant
Executive Student Employee Intern
User of e-health-services
No Limited Limited Yes Yes No
Chronic disease No No No Yes Yes No
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All interviews were conducted by the same researcher. In order to develop a broad perspective
of e-health service quality dimensions, a semi-structured questionnaire with open-ended
questions was employed which allowed respondents significant freedom in their narration of
responses. The first step in all interviews was to achieve a common understanding regarding
the term e-health, followed by questions directed at the individual understanding of quality e-
health services. Interviewees were asked to tell which attributes and factors had lead to a
positive or negative experience of their e-service encounter. Non-users of such services were
asked about reasons why they have not chosen any e-services. From a normative perspective
these interviewees also were questioned about factors that would make e-services more
attractive for them.
Table 3: Exemplary interview questions Exemplary questions directed to users of e‐health services:
What is your understanding of e‐health services? Can you describe positive and negative experiences with e‐health services? What expectations do you have regarding e‐health services?
Exemplary questions directed to non‐users of e‐health services:
Can you imagine to use e‐health services? Please describe why or why not. Which aspects of e‐health services would be important for you to consider using them?
Interviews lasted between 60 and 90 minutes. Following the interviews with patients (as
raters) the resulting classification is subject to an evaluation by experts. The authors chose to
conduct in-depth interviews with experts instead of using a structured evaluation form – thus
diverting from Rossiter’s C-OAR-SE procedure. The underlying reason was to gain more
comprehensive information that would help to extract conclusions about the quality
dimensions of e-health services. Two experts, both with more than five years of experiences
as an approbated physician, were selected for the interviews. Expert 1 has been a chief
physician of several hospitals in Switzerland with an experience of 20 years in healthcare.
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Expert 2 is a general practitioner in Germany with ten years of experience as a practice-based
doctor. These two interviews also lasted between 60 and 90 minutes.
All of the interviews were recorded and transcribed. The analysis of the qualitative data
proceeded by coding and qualitative content analysis in order to classify quality dimensions.
No software package has been used with regard to the coding process. The coding structure
was developed in a first step by the interviewer herself, followed by critical discussion and
reflection with two other researchers involved in this project. The reliability of the results was
enhanced by documenting the empirical research process thoroughly. External validity was
enhanced by drawing analytical conclusions based on the literature review. To enhance
construct validity, the same general structure was used for all interviews.
Findings of Patient and Expert Interviews
Results regarding the meaning of e-health (object classification)
The results of the patient interviews (IP) provide insights for the object classification. Patients
had different perceptions regarding the meaning of e-health and e-health services. First,
comments of interviewees illustrate that the term e-health is not easy to define. For example,
raters mentioned the following: “everything electronic in healthcare” (IP 5), “Internet in
healthcare” (IP 6) or “to exchange and process data” (IP 6). With regard to the meaning of e-
health services interviewees referred to aspects such as online pharmacies, electronic
communication among healthcare constituents (e.g. pharmaceutical companies, medical
associations), electronic services between physicians/hospitals and insurance companies (e.g.
electronic patient files), call center of insurance companies, electronic billing and
telemedicine. One respondent who was affected personally with a chronic disease mentioned
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electronic devices that read and monitor data as well as additional services such as keeping a
medical diary.
A more specific question dealt with the understanding of e-health services within the
physician-patient-relationship. The interviewees primarily referred to the electronic
communication with their physician. In addition, tools such as medical data management
software were mentioned that can be used to improve the efficiency of the consultation
process with the physician. For instance, one respondent said he would transfer his medical
results that were taken by a mobile device to a PC in order to email them to his physician
before his next appointment. Thus, in this study it seems that e-mail communication is the
centerpiece of e-health services.
According to Rossiter’s C-OAR-SE procedure an abstract formative object has to answer the
question “What does it mean” (Rossiter 2002, p. 312). In summary, all respondents were able
to describe the different features of e-health services within the physician-patient-relationship,
even though all of them did show a somewhat different understanding of e-health.
Consequently, the qualitative interviews were able to answer Rossiter’s core question.
Furthermore, following the classification of objects under C-OAR-SE, concrete objects are
differentiated from abstract objects as follows: for the former “nearly everyone (of a sample)
of raters describes the object identically”; for the latter “the object suggests different things to
the sample of raters” (Diamantopoulos 2005, p. 3; Rossiter 2002, p. 310). We thus conclude
that e-health services within the physician-patient-relationship can be described as an abstract
formative object.
Results regarding indicators of e-health service quality (attribute classification)
21
Patient interviews also provided information regarding the classification of the attribute as
concrete, formed, or eliciting. The transcripts indicate that quality indicators previously
identified in the literature review were supported. One candidate mentioned how easy it is to
go online and search for information after a doctor’s consultation in case questions have been
unanswered (IP 5). By the same token, the person stressed the importance to have access
anytime to his own personal data. These two comments seem to indicate that accessibility is a
key quality indicator.
All interviewees pointed out the competence of the service provider as an important quality
indicator. For example, patients do not know if the service online is delivered actually by a
physician or by someone else. Since they cannot see the doctor’s “lab coat” (translated from
“weisse Arztkittel”) it is difficult to evaluate the doctor’s experience or specialization (IP 1, IP
2, IP 5, IP 6). Closely related is the issue of credibility of the information provided online (see
table 1). One interviewee said that he would only search for information on trustworthy
websites such as research institutions or associations since he would associate a higher level
of competence to these sites (IP 2). Some patients (IP 1, IP 6) seem to be afraid of misleading
information published by certain lobbyist or interest groups (e.g. pharmaceutical companies).
Both quality dimensions, accessibility and competence, fall in the category of the primary
dimension of potential quality. They describe search qualities; that is, cues that serve as
‘surrogate’ quality indicators of e-health. These two aspects can be evaluated by the patient
more easily than other intangible e-health services.
Patients also indicate that information is considered to be an important quality criterion. Li
and Suomi (2009) point out that information is vital for customers to make their decision in an
online marketplace since they cannot physically examine what they want to purchase. In the
22
healthcare context patients expect to receive recent and comprehensive information that is
easy to understand (IP 1, IP 2). More specifically, the information has to be case-specific,
which means it has to apply to the individual’s needs. This is mostly likely the case with
discussion forums or online communities where patients can exchange stories with other
humans who feel the same way (IP 4).
Usability (or user friendliness) is also seen as an important topic among all interviewees. The
service providers’ website should be designed for customers’ ease of use, including searching,
navigating and use (Li, Liu and Suomi 2009). Patients mentioned the tedious process of
searching and finding information online. Apparently, it is necessary to gather information
from different websites in order to combine the content. This is seen as very time consuming.
One person (IP 1) called this process “time killer” (translated from “Zeitfresser”), while
another person (IP 5) said that it takes forever to collect and read information, to evaluate its
content, to make considerations (e.g. if one agrees or disagrees), until one can actually start
the process of treatment. This highlights a trade-off that users have to face between usability
and security. The aspect of usability also came up in the context of home monitoring devices.
That is, those devices are supposed to be small, easy to handle and not to feel burdensome
during every-day’s life (IP 2, IP 3). One person mentioned that it would be nice if such
medical devices could be integrated in other common technological devices such as cell
phones. Since people usually always carry their cell phone with them, the perceived usability
is seen as very high (IP 4).
Security of e-health services and problems with privacy are also deemed highly relevant.
Interviewees said that they would prefer anonymity when using e-health services, in
particular, with regard to online discussion forums (IP 2, IP 4). They expect that their personal
and medical data is stored and handled securely (IP 1, IP 2, IP 6). That means only authorized
23
people would have access to the data. Security in a general context refers hereby to the
technical security and the functionality of the information system (e.g. “the backbone
mechanics has to be reliable,” IP 5). That means, the system has work properly to transmit
data correctly and in a timely manner. The following comment illustrates this view:
“Maybe the data is not transmitted properly. We know that this happens with cell phones. For example,
SMS that are sent will be received much later” (IP 2).
System integration refers to the compatibility of several electronic devices. For instance, one
person said that home monitoring devices should be integrated and be able to exchange data
(IP 4). This reduces complexity and increases user friendliness. With regard to electronic
patient files some patients referred to network issues. Two interviewees expect that the
interaction among different stakeholder in healthcare will become easier with the introduction
of a standard electronic patient file (IP 3, IP 5).
Patients also elaborated on the topic of trust in the context of e-health services. One person
who was rather critical of e-health services made the following comment:
“With health I would put the highest emphasis on treatment, trust and non-verbal communication such
as gestures” (IP 1)
The criticism of patients relates to the difficulty of establishing a trusting relationship. Two
interviewees mentioned the example of “web visits” to an unknown physician (IP 5, IP 6).
Even more explicit is that some patients do not like the idea of getting monitored by an
electronic device. Instead, they preferred the personal contact to their doctor (IP 1, IP 2, IP 6).
In other words, it is the holistic impression that patients perceive based on the doctor’s verbal
24
and nonverbal interaction. That is, a diagnosis may be perceived differently, or more
seriously, based on interpersonal relations between doctor and patient, including gestures
given by the doctor.
As assumed earlier, patients also pointed out the degree of individualization as a quality
indicator. The following comment illustrates this perspective:
“Such an online portal only represents experiences either of other patients or medical personnel offering
information for the public, but it is never specific for my own case” (IP 1).
In other words, e-health users do not like to receive a standard answer to their question, but
expect a customized solution (IP 2, IP 3).
With regard to outcome quality, two interviewees questioned if the outcome of e-health
services would provide the same value as traditional medical treatment. In other words, e-
health users are concerned with the degree of performance. This holds true in particular for
health information obtained online. For example, one person said:
“So, nobody tells me what I should do now [with this information]. Basically, I have to decide whether I
want to try it or not. That is nothing else than gambling.” (IP 1)
Similar reactions were found with regard to e-services such as “web visits” or an e-mail
consultation.
“The final outcome [of online consultation] just has to be as good as if I go visit my doctor in person”
(IP 6)
25
Other outcome quality dimensions mentioned by patients refer to reliability and
responsiveness. Interviewees stressed the importance that the provision of e-health services
has to be reliable. Further, they expect the service provider to respond in a timely manner to
questions (IP 2, IP 3, IP 5). One person criticized the ability to respond in the case of “ad hoc”
questions. Since the service provider would not be able to respond to ad hoc questions, the
person was reluctant to use e-health services in the first place (IP 1). This comment
emphasizes the need to respond quickly to patients’ questions.
Modification of construct definition
All of the quality indicators identified in the literature review seem to be relevant for the
patients who participated in the interviews. Reflecting on the results, however, it seems that
the personal contact and the physician-patient interaction are highly important in the context
of healthcare services in general, but also specifically in the context of the delivery of e-health
services. We thus propose to extend the model with a new factor: empathy. That means how
empathetic service providers are, when dealing with patients via the Internet. Li, Liu and
Suomi (2009) point out that even though there is no direct interaction, some human contacts
are involved in the delivery of e-services. And providing customers with individual attention
does show empathy to customers. Do they provide the same personal attention compared to
someone in a face-to-face interaction? The overall model is the basis for the discussion with
experts.
Results of the qualitative interviews with experts
The purpose of the expert interviews was to evaluate the classification of object and attribute
and to discuss the measurement model that resulted from the qualitative analysis of the patient
responses. Additional information was expected to be gained due to the long, practical
experience of the experts in the field of healthcare and as a provider of health services. Their
26
experience was the final factor to modify the measurement model. Overall, the object
classification as abstract formative could be supported by this research. Both experts agreed
that the term “e-health services” comprises various components ranging from information
technology in patient care (Exp. 1) and electronic communication between physician and
patient (Exp. 2) to monitoring systems, e.g. via webcams, in hospitals (Exp. 2).
Furthermore, the attribute classification as abstract formative could be supported. Both
experts identified the same quality indicators that first were identified in the literature review
and then modified based on the results of the patient interviews. Keys topics that were
mentioned by the experts are security/privacy as well as usability.
“Even though patients probably do not completely understand that their data is secure, it is reasonable to
see that there are concerns. However, I believe a patient who is well informed will see the advantages.”
(Exp. 1)
The experts also supported the quality indicators trust and empathy. Comments show that it is
important for the physician to perceive the patient in a comprehensive manner. Building a
relationship with the patient is important to evaluate the patient’s description of his/her
medical conditions, e.g. if the person is exaggerating or not.
“Basically, you have to find out if the whining and moaning is serious or not” (Exp. 1)
The interviews with the experts also generated new insights. Based on the discussion and
feedback about e-mail consultation and “web visits” it becomes apparent that physicians
consider their ethical conduct as an important quality indicator. For example, the experts were
critical about e-mail consultation or “web visits” if the patient is unknown to the provider.
27
Furthermore, in the case of more complicated medical questions, the consultation via the
Internet would be contradictory to the doctor’s Hippocratic Oath.
“Medical consultation and treatment means to see and touch the patient” (Exp. 1)
The ethical obligation of the physician includes his/her responsibility not to answer certain
medical questions without meeting the person face-to-face. Thus, doctors would have to stop
any kind of e-mail consultation once they diagnose a severe illness that requires further “real-
world” consultation. In summary, the expert interviews largely confirmed the twelve quality
indicators that were identified in the patient interviews. Ethical conduct is a new quality
indicator that extends the process dimension in the measurement model. As a result, the
construct e-health service quality is operationalized with 13 items (see Figure 2).
Figure 2: Formative measurement model of e-health service quality
Potential quality
Process quality
Outcome quality
e‐healthservice quality
Accessibility
Competence
Information
System integration
Security of data/system
Usability/User Friendliness
Trust
Individualization
Degree of performance
Ability to respond
Reliability
Ethical conduct
Empathy
28
Conclusion
The study presents important contributions to theory and practice. With regard to research,
this paper builds upon a new approach labeled with the acronym C-OAR-SE that is discussed
as a procedure for scale development. Following Rossiter’s C-OAR-SE approach we
conceptualize systematically the construct e-health service quality. Thus, we contribute to a
research field that does not follow the traditional path of empirical marketing research
influenced by the work of Churchill (1979). Our study also contributes to knowledge with
regard to the measurement of e-health quality and improves our understanding of how
customers evaluate the quality of e-health services. Our findings suggest that quality of e-
health services is perceived at multiple levels of abstraction which is consistent with previous
research in healthcare quality (Dagger, Sweeney and Johnson 2007). We have identified three
primary dimensions: potential quality, process quality and outcome quality. These primary
dimensions are driven by 13 sub-dimensions: accessibility, competence, information,
usability/user friendliness, security, system integration, trust, individualization, empathy,
ethical conduct, degree of performance, reliability, and ability to respond.
The resulting quality indicators of this study provide contributions for several entities in the
public health sector. In particular, health care providers can utilize the results for the
evaluation of their service quality. Dagger, Sweeney and Johnson (2007) suggest that
practitioners can use the hierarchical structure to measure service quality at different levels.
For instance, they can measure at the overall level, at the primary dimension level (with
measures for potential, process and outcome quality) or at the sub-dimension level. The scale
thus offers physicians several choices regarding the level of detail measured (Dagger,
Sweeney and Johnson 2007). To improve the perceptions of process quality, service providers
29
could start, for instance, by improving usability, individualization, etc. Practitioners can use
the structure also as a diagnostic tool to identify poor and/or excellent performance with
regard to the s-service delivery. This information is particularly important for the purpose of
continuous improvement of the e-health service quality.
The paper also provides insights for other actors in the healthcare industry. For example,
insurance companies can benefit from this study. The underlying assumption is that the
successful provision of e-health services between physicians and patients may lead to costs
savings. Thus, the provision of premium, yet cost-efficient, medical e-services contributes to
the general public health sector.
As with any research study there are limitations that need to be addressed. While Rossiter’s
C-OAR-SE procedure “encourages a much more flexible and open-minded approach towards
scale development and releases researchers from the shackles of conventional test theory”
(Diamantopoulos 2005, p. 8), there are several critical issues associated with C-OAR-SE. For
example, Diamantopoulos (2005, p. 8) mentions the “use of single-item measures and
construction of formed attribute scales” as well as “sole reliance on content validity”. Second,
the number of interviews with patients and experts are limited. Future research may extend
the qualitative analysis with different methods, e.g. focus groups or exploratory case-study
methodology. Third, the present study focuses on the healthcare sector in a particular country.
Since healthcare regulations vary across countries, it seems reasonable to conduct cross-
country studies to compare the results. Finally, one has to acknowledge differences in the
availability of e-health services due to different technological standards across the world –
referred to as the “digital divide”. For instance, e-health services will be less relevant in
countries with a lower penetration rate of the Internet (e.g. Africa). Consequently, the results
30
may only apply to countries with a high penetration rate of the Internet as well as broadband
connections.
This study offers several important perspectives for future research. While the qualitative
results at hand constitute a necessary first step, the existing formative measurement model
would need further specification by quantitative studies. Jarvis et al. (2003, 213) point out
problems regarding indeterminacies associated with the construct level error term. One of
their solutions is to add a path to unrelated latent constructs with reflective indicators. In the
context of the present study, one suggestion for future research thus may be the integration of
the construct “satisfaction with the e-health service provider” which can be operationalized
with reflective indicators. Dagger, Sweeney and Johnson (2007) suggest that health service
quality is a key determinant for satisfaction of health services and customers’ behavioral
intentions. It is reasonable to assume that this position holds true also for the delivery of e-
services. Future research thus needs to address the relationships and mediating role of e-
service quality in more detail. In addition, more research is needed as e-health “is a huge
rapidly changing area” (Simmons 2000, p. 3). With changing technology and an increasing
focus on mobile devices, the provision of e-services will most likely evolve and change. More
empirical research is needed to confirm the quality indicators of e-health services.
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