Public Organization Review (2021) 21:471–489
https://doi.org/10.1007/s11115-020-00498-x
Examining Quality, Value, Satisfaction and Trust
Dimensions: An Empirical Lens to Understand Health
Insurance Systems Actual Usage
Vincent Ekow Arkorful1 & Benjamin Kweku Lugu2 & Anastasia Hammond3 &
Ibrahim Basiru2 & Frederick Appiah Afriyie4 & Bobita Mohajan5
Accepted: 25 December 2020/ Published online: 1 February 2021
# The Author(s), under exclusive licence to Springer Science+Business Media, LLC part of Springer Nature 2021
Abstract
Health insurance policies have become key social policy interventions incepted to
extend healthcare to vulnerable populations. In this vein, Ghana devised a health
insurance scheme in the year 2003. However, there have been concerns about quality,
value, satisfaction and trust regarding healthcare and insurance usage. Using data
drawn from 345 participants, our study investigates these dimensions to empirically
test their predictive effects on the actual usage of health insurance. Data analysis results
using the Structural Equation Modelling technique confirmed these dimensions as
predictors of intention and actual usage. Our study delineates the practical, theoretical
and policy implications of the study findings.
Keywords Health insurance . Healthcare quality . Value . Trust and satisfaction . Health
insurance use intention . Actual usage
Introduction
The growing efforts exerted towards the pursuit of universal health coverage goals has
imposed huge responsibilities on state and non-state actors to device sustainable
* Vincent Ekow Arkorful
saintvincentino@gmail.com
1 Department of Government and International Studies, Hong Kong Baptist University, Kowloon
Tong, Kowloon, Hong Kong, China
2 School of Management, University of Science and Technology of China, Hefei, Anhui, China
3 Department of Psychology, University of Ghana, Legon, Accra, Ghana
4 School of Law, Zhongnan University of Economics and Law, Wuhan, Hubei, China
5 School of Public Affairs, University of Science and Technology of China, Hefei, Anhui, China
472 Arkorful V.E. et al.
mechanism targeted at dispensing comprehensive healthcare to populations. Essential-
ly, among other things, the institution of these mechanisms aimed at advancing life
devoid of treatable ailments and premature morbidity, whiles ensuring freedom and
reducing deprivation. The realization of these goals, primarily calls for an elevation in
healthcare by stakeholders. And as much as issues of healthcare remain a fundamental
human right, developing governments in developing countries are challenges in ad-
ministering essential health services (Sulemana and Dinye 2014), thereby entrenching
inequity in healthcare (Arkorful et al. 2018). Given the centrality of Primary Health
Care (PHC) services as a sustainable pathway to reducing healthcare inequities, part of
the resolve to devise proactive polices to advance healthcare in an efficient and
effective environment has guided the implementation of various forms of health
policies in various countries. Advanced countries like Canada and Australia have made
phenomenal inroads in healthcare by implementing a hybrid public-private insurance
scheme (Dalinjong and Laar 2012).
The passage of the National Social Security System for health, under the universal
health insurance scheme (Law 100) approved in 1993 has helped extend health
coverage to a population of approximately 95% (Escobar et al. 2010). And whereas
the 2011 implementation of Thailand’s universal coverage scheme enhanced a 95%
population coverage in 2012, (Health Insurance System Research Office 2012), the
passage of the National Health Insurance in Taiwan in 1995 ensured a population
coverage of 97% by 2001 (Hsiao and Cheng 2013). Though the history of these
schemes has been a success, same cannot be said for similar schemes in other countries.
The National Health Insurance Scheme in Nigeria for instance has enhanced a
population-wide coverage of less than 5% (Kumi-Kyereme et al. 2017). In Kenya,
the National Health Insurance Fund (NHIF) of 1966 and the National Social Security
Fund (NSSF) of 1965 has enhanced a 10% population coverage (Abuya et al. 2015).
Furthermore, schemes like the NHIF, Social Health Insurance benefit, Community
Health Fund (CHF), Tiba Kwa Kadi (TIKA) and other private ones like the National
Insurance Corporation, MEDEX (T), AAR4 Health Insurance and Strategies Insurance
in Tanzania have enhanced 16% population-wide coverage (Dutta 2015).
Over the years in Ghana, one of the most utilized conduits to reducing poverty has
been the reduction in healthcare inequality levels. Precisely, health insurance has
actually been a fulcrum around which health governance has revolved. The tone for
the state’s commitment to healthcare and access policy reforms was set through the
promulgation of the National Health Insurance Law, Act 650 of parliament of Ghana,
in the year 2003. The mandatory insurance policy had a legal backing in the year 2004
when the national health insurance regulation (legislative instrument-1809) was enacted
(Government of Ghana. National health insurance regulations 2004). Ghana’s insur-
ance policy seeks to extend healthcare to all people living in Ghana. The scheme which
covers about 95% of disease burdens (Amu and Dickson 2016) is financed from 2.5%
Value Added Tax (VAT) on goods and services, 2.5 deductions from social security
pension contributions of formal sector workers and annual premium payments by
persons aged 18 years and above. Other sources include; grants, donations, invest-
ments, gifts, voluntary contributions and other fund allocations from the health insur-
ance fund by the parliament of Ghana.
The national health insurance authority is the regulatory body in charge of the health
insurance scheme. As much as the history of the scheme has been chequered, reforms,
Examining Quality, Value, Satisfaction and Trust Dimensions: An... 473
including; the inception of a clinical audit, free maternal health care, claims processing
outfits, biometric identification cards, call centers, consolidated premium account in
2011 (Amu and Dickson 2016; National Health Insurance Authority 2012) and self-
renewal options have been introduced to promote efficiency and effectiveness of
service delivery. These reforms have resulted into significant improvement in
healthcare accessibility. For instance, the policy has influenced ante natal service and
supervised delivery (Dzakpasu et al. 2012). In view of this, insured pregnant enrollees
stand 85.7% chance of accessing prenatal care, whiles the uninsured stand a chance of
72% (Mensah et al. 2010). Generally, the introduction of the policy in 2005 increased
health service utilization by over forty-fold from 0.6 million in 2005–25.5 million in
2011, making up 33% coverage of Ghana’s population (National Health Insurance
Scheme in Ghana 2011).
Although easing financial burden generated by the cost recovery policy (especially
on the poor), was one of the proximate reasons for the introduction of the health
insurance policy (Blanchet et al. 2012), whiles there exist a substantial evidence of the
inability of the poor to utilize the policy, there are also pervasive reports of subscriber
discontentment with the policy and services rendered by service providers including,
but not limited to; health institutions and health personnel, health insurance registration
outfits and personnel, health insurance accredited pharmacies, amongst others. These
challenges have the potential to erode the gains made over the years. They could also
impair the effectiveness and sustainability of the policy (Arkorful et al. 2018).
Prior studies have revealed poor quality services to health service seekers. And the
fear of receiving inferior services has generated dissatisfaction, further making both the
enrolled and prospective enrollees reluctant to utilize the scheme. In the year 2008 for
instance, a stakeholder assessment underscored poor service quality of the scheme, and
its affiliate service providers. Specific issues at the heart of the study findings centred
on perceptions of poor-quality medications, unprofessional attitude of service pro-
viders. With regard to medications, another study by the National Development
Planning Commission recounts the challenges of subscribers and revealed that 80%
of enrollees complained of non-availability of medications (National Development
Planning Commission 2009).
Moreover, another report by the Ghana Heath Service recounts of the negligible
quality healthcare (Ghana Health Service 2011). And as much as the implementation
of the health insurance scheme has placed enormous pressure on health systems, it
has also created a germane space for the festering of malpractices like bribery and
corruption among service providers. To this end, service providers extort sums from
service seekers before delivering service. This has taken a toll on not only service
seekers overall perception, but also, their usage of health insurance (Arkorful et al.
2018). In view of the confluence of factors disparately identified by prior studies, vis
avis the global pursuit of universal health coverage goals, our study sets to empiri-
cally investigate the amalgam of quality, value, satisfaction and trust dimensions
relative to individual’s intention to use, and actual usage of health insurance. A
comprehensive investigation of these dimensions would be of immense significance
to a broad spectrum of global health stakeholders, as well the pursuit of universal
health coverage goals. The remaining part of the paper is segmented as follows: the
theoretical development and hypothesis discourses on theory and study hypothesis;
study methods are presented under methodology; results of the study, present
474 Arkorful V.E. et al.
outcomes. The final segment presents the discussion, conclusion, practical and
theoretical implications of the study.
Theoretical Development and Hypothesis Formulation
The pertinent nature of health and have over the years gained enormous attention (Lee
2017). For this reason, concerns of quality and general reforms have subsequently
increased. The service quality model has been extensively used to measure quality in
various service areas because of its suitability and usability. Actually, healthcare quality
discourse has evolved over the years. Myers (1969) conceptualised quality to include
access, effectiveness, care improvement and continuity. Donabedian (1980) also de-
fined quality to include efficacy, effectiveness, efficiency, legitimacy, optimality,
acceptability and equity. Whereas Myers (1969) and Donabedian (1980) commonly
agreed on efficiency and effectiveness. Donabedian (1980) introduced the dimension of
efficacy to patient care. Parasuraman et al. (1988) delineated dimensions which among
other things include; responsiveness (i.e. the attitude of service providers who nurse,
care, and provide immediate service, and assurance (i.e. patients trust and faith
regarding service providers attitude). Doran and Smith (2004) classified healthcare
service quality measurement items to include reliability, responsiveness, assurance and
elevation in care. Lee (2017) suggested health quality based on service providers and
seekers perspective regarding efficiency, safety, quality. The foregoing discussion
indicates the evolving nature of the discourse of health quality. Healthcare quality
should be evaluated based on service seekers perceptions (Jun and Arendt 2016).
Integrating these disparate perspectives, our study puts forward an empirical study to
investigate service quality, value, trust and satisfaction dimensions. The integration of
trust is based on the observation that, Ghanaians have strong bond of trust with social
protection policies initiated by government. For that matter, it could be considered that,
health insurance sustainability, in terms of enrolment, renewal, and retention could be
augmented by trust. The integration of use intention and actual usage as widely used
constructs within behavioral and psychological science-related studies hinged on the
Theory of Planned Behavior (Ajzen 1991) and the theory of Reasoned Action (Fishbein
and Ajzen 1980) will further help deepen understanding. Therefore, our study inte-
grates quality, value, satisfaction and trust dimension within the theoretical framework
of TRA to enhance an understanding and further prediction of intention to use, and
actual usage of health insurance.
Hypotheses
Service Quality
Service quality is conceptualised as the standard degree of health system to provide
the needed care support for service seekers (Lee 2017). Essentially, service quality
has been an important driver of policy patronage, including social protection policy
(i.e. health insurance policy). In this regard, the study posits that, intention to use, and
actual usage of health insurance could be driven by service seekers perception of the
support that the policy provides. In a situation whereby the enrolled perceive of
Examining Quality, Value, Satisfaction and Trust Dimensions: An... 475
inferior service quality, they are likely not to renew. In the case of prospective
enrollees, they are also not likely to enroll. These perceptions may constrain health
insurance use, thereby posing policy sustainability threats. Therefore, service quality
could be overarching to health insurance use. Precisely, perceptions of assurance to
services like medication, timely access to health service providers, amongst others,
will enhance intention to use. Thus, it is projected that, service quality regarding
health insurance related services can inform intention to use. From the foregoing, we
hypothesize that:
H1: Service quality has a significant positive relationship with intention to use
health insurance
Value
Value constitutes an essential underpinning element of consumers intention to
transact (Holbrook 1994). Consumers satisfaction with a service or a product informs
the formation of a better value expectation. Essentially, whiles value considerations
inform loyalty to a service or product, it also drives a positive reaction (Anderson and
Srinivasan 2003). Value considerations are largely utility based, stemming from a
positive evaluation of the service or product in question. Relating this logic to health
insurance, it could be said that, enrollees’ perception regarding the likelihood to
maximize utility benefits, is likely to inform intention to use and actual usage.
Moreover, when individuals consider health insurance to offer superior benefits than
other alternatives (e.g. out-of- pocket payment health-based services), and as such
guarantee’s satisfaction, benefits and overall excellence (i.e. medications, access to
healthcare etc), they are likely to be motivated to use. Greater values are likely to
result in greater intention to use health insurance. From the foregoing discussions,
this study proposes the following hypotheses:
H2: Value has a significant positive relationship with intention to use health
insurance
Satisfaction
Satisfaction with an object, in this case health insurance is informed by the degree of
interaction between users/service seekers and service providers (Zineldin 2006). In this
respect, satisfaction borders on a positive user experience with health insurance, and
healthcare service in general. Within the context of this study, we predict satisfaction as
a determinant and/or predictor of intention to use health insurance. On this premise, it
could be said that, as much as the satisfaction of enrollees could inform enrollment,
renewal, retention and usage, through service seekers experience, it could also inform
the decision of prospective enrollees to get themselves enrolled. The non-satisfaction of
enrollees may affect intention to use. Satisfied enrollees are likely to exert efforts
towards use. Most importantly, health insurance user’s satisfaction will be enhanced
476 Arkorful V.E. et al.
by their general experience with service providers and health systems. As such we
propose that:
H3: Satisfaction has a significant positive relationship with intention to use health
insurance
Trust
Issues of trust has in recent times dominated social science discourses. Trust is a psycho-
logical construct bordering on the judgements of individuals or group of individuals
regarding the fact that, systems or individuals within a systemwould be effective and results
oriented towards their needs (Rousseau et al. 1998). Trust in this study is premised on
service seekers reliance and confidence on the health insurance scheme to provide them the
expected health protection. Actually, health insurance in one way or the other constitutes a
shock absorber that saves individuals from health-related uncertainties. Moreover, given the
pro-poor nature of the policy intervention, and the general poverty situation in Ghana, this
policy has provided some form of safety net, as it protects vulnerable households with
unsustainable income streams from outrageous health expenditure. Given the situation of the
vulnerable in the society, it becomes more obvious that, the potency of the health insurance
scheme to render efficient and effective services (e.g. providing the requisite drugs and
services, not been exploited), has the tendency to increase individual trust in the scheme.
Enhanced trust will further increase intention to use. As such trust stands as an important
construct to boost intention to use among health insurance enrollees and prospective
enrollees. In view of this, we hypothesize that:
H4: Trust has a significant positive relationship with intention to use health
insurance
Intention to Use and Actual Usage
In view of the fact that enrolment, renewal and retention contribute to ensuring health
insurance sustainability, it is instructive to state that, as much as it is imperative to
attract potential enrollees, it is equally important to retain already enrolled. Retaining
the already enrolled, whiles attracting the non-enrolled is premised on their belief in
health insurance, as it encapsulates their cycle of experience with the health care system
and the service providers as well. Behavioral studies corroborate the positive relation-
ship between intention to use and actual usage (Fishbein and Ajzen 1980). By
extending same logic in our study of health insurance, we posit that, intention to use,
could have a contagious effect on actual usage. The intention to use, within th context
of the study model will be influenced by quality, value and trust dimensions, which
would further, finally determine actual usage. In the regard, we hypothesize that:
H6: Intention to use has a significant positive relationship with actual usage of
health insurance
Examining Quality, Value, Satisfaction and Trust Dimensions: An... 477
Research Methodology
Research Participants and Data Collection
A questionnaire survey was utilized to draw data (from 1 st November 2019 to 20 th
February, 2020) to test the study hypotheses. To ensure timely, useful and scientific
data collection, questionnaires were self-distributed to participants (composed of users
and prior users of health insurance) seeking health care at selected health facilities.
Given the general difficulty of conducting facility-based data collection in Ghana, the
research team established contacts with a health regulatory institution to help sample
health facilities, and also introduce the research team to the targeted population. This
led to the selection of two hospitals each from three regions (i.e. Northern, Upper-West
and Upper East Regions) selected on the basis of poverty prevalence (Ghana Statistical
Service 2015). Prior to data collection, to enhance the protection of the rights and
privacy of study participants, an ethical approval was obtained from the institutions.
Thereafter, data collection commenced. Participants were briefed on the study
purpose and their right to drop out at any stage. Completing a questionnaire took a
maximum of 30 min. During data collection, all participants who had reading chal-
lenges were ably assisted by the research team which was adequately composed to meet
the communication needs of the targeted population. In total, 370 questionnaires were
distributed. At the end of data collection, 350 questionnaires were returned. After
sorting uncompleted questionnaires with missing data, 345 useful questionnaires
remained. Overall, the study recorded a 95% response rate. The details of study
participants are presented in Table 1.
Measures
The questionnaires used presented questions seeking to capture participants’
sociodemographic details such as gender, age and education. The questions were
structured to capture constructs (with 18 items) adapted from past studies which had
confirmed their validity and reliability. Items for service quality were adapted from
Urbach et al. (2010). Value items were adapted from Sweeney and Soutar (2001). Trust
items were adapted from (Boateng et al. 2016). System quality items were adapted from
Urbach et al. (2010). Furthermore, items for “Intention” were adapted from Bagozzi
et al. (2003). Items for measuring satisfaction were adapted from (Wu and Wang 2006).
And finally, “actual usage” items were adapted from Moon and Kim (2001). These
items were refined the suit the context of our study. A 5-point Likert scale starting from
Strongly Disagree to Strongly Agree were used to measure items. Sentence structures
of adapted items were significantly refined to suit the study context (Tables 2, 3 and 4).
Data Analysis and Results
In view of the theoretical framework, and the study hypothesis, the Structural Equation
Modeling (SME) technique, complemented with Analysis of Moments of Structures
(AMOS) software version 24 was employed for data analysis and establishing the
proposed model. SEM helps to; (a) examine series of dependent variables at the same
time, especially in a situation where there exist direct and indirect effects among
478 Arkorful V.E. et al.
Table 1 Descriptive Characteristics of the Sample
Measures Frequency (n) Percentage (%)
Gender
Male 157 46
Female 188 54
Age
<25 111 32
26–30 105 30
>30 129 38
Education
Junior high school 97 28
Senior High school 79 23
Tertiary and above 93 27
No formal education 76 22
Income
>$50 222 64
$50–$100 95 28
$101–$150 15 4
$151–200 8 3
>$200 5 1
Current status
Active 299 87
Inactive 46 13
Prior status
Subscribed 255 74
Not subscribed 90 26
constructs (Hair et al. 2010); (b) analyse latent and observed variables inter-
relationships; (c) model errors within observed variables and provide exact measure-
ments; and (d) measure latent variables using multiple indicators and testing hypotheses
at construct, rather than item level (Hoyle 2011). In analyzing data, a three-step
approach was employed. Measurement model was confirmed to establish the validity
and reliability of constructs at the first step. The structural model was evaluated in the
second step employing hypothesis testing. Mediation effect analysis was conducted to
test the mediating roles of “intention to use”.
Measurement Model Analysis
Exploratory factor analysis was conducted with Statistical Package for Social Scientist
(SPSS) to evaluate factor loadings, reliability, convergent and discriminant validity of
the proposed model. In Table 3, factor loadings for items ranged from .794 to .948,
which is greater than the recommended benchmark of .70. Test of reliability indicated
Cronbach alpha values to be greater than 0.7 signifying acceptable reliability of scale
Examining Quality, Value, Satisfaction and Trust Dimensions: An... 479
Table 2 Measurement and Cross Loadings
Construct Item INT SAT SQ AU VAL TR
Intention to Use (INT) INT1 .919 .000 −.059 .017 −.019 −.004
INT2 .923 .051 −.002 .000 .025 −.019
INT3 .948 −.023 .071 −.019 .002 .014
Satisfaction (SAT) SAT1 −.024 .886 .030 .058 .012 −.051
SAT2 .027 .918 −.034 −.008 .014 .028
SAT3 .022 .925 −.021 −.014 −.028 .040
Service Quality (SQ) SQ1 .041 −.014 .884 −.031 −.042 −.026
SQ2 −.016 .000 .900 .059 .002 .036
SQ3 −.014 −.012 .893 −.011 .045 −.001
Actual Usage (AU) AU1 −.046 .070 .021 .863 .083 −.021
AU2 .030 −.041 −.015 .911 −.039 .024
AU3 .012 .010 .012 .870 −.046 −.010
Value (VAL) HV1 −.015 .076 .044 −.098 .868 .002
HV2 .078 −.138 −.053 .090 .834 .028
HV3 −.052 .053 .014 .005 .878 −.027
Trust (TR) TR1 −.018 .053 −.007 −.027 .023 .794
TR2 .021 −.086 −.079 .050 .038 .878
TR3 −.013 .050 .097 −.029 −.059 .825
Table 3 Results of Factor Analysis
Construct Item Factor Cronbach Composite Average Variance
loadings Alpha Reliability Extracted (AVE)
(CR)
Intention to Use (INT) INT1 .919 .925 0.951 0.865
INT2 .923
INT3 .948
Satisfaction (SAT) SAT1 .886 .905 0.935 0.828
SAT2 .918
SAT3 .925
Service Quality (SQ) SQ1 .884 .873 0.921 0.796
SQ2 .900
SQ3 .893
Actual Usage (AU) AU1 .863 .864 0.913 0.777
AU2 .911
AU3 .870
Value (VAL) VAL1 .868 .826 0.895 0.740
VAL2 .834
VAL3 .878
Trust (TR) TR1 .794 .778 0.872 0.694
TR2 .878
TR3 .825
480 Arkorful V.E. et al.
Table 4 Average Variance Extracted and Correlation
Construct Mean STD SQ VAL TR INT SAT AU
SQ 13.258 2.393 .892
VAL 10.441 3.119 −.083 .860
TR 10.759 3.167 .017 −.003 .833
INT 9.667 3.836 .131* .139** .141** .930
SAT 11.603 2.717 −.033 .109* .030 .346** .910
AU 11.197 3.004 .080 −.004 .062 .393** .389** .881
Note: ** p < 0.01, STD=standard deviation, SQ=service quality HV=health value, TR=trust INT=intention to
use, SAT=satisfaction, AU=actual usage
(Fornell and Larcker 1981). Average variance extracted (AVE) values and composite
reliability measures were used to imply convergent validity. Composite reliability
scores of variables were greater than 0.7 signifying the sufficiency and representative-
ness of items of proposed constructs reliability (Hair et al. 1998). AVE values greater
than 0.5 signifies a good convergent validity (Fornell and Larcker 1981). Discriminant
validity was assessed using both cross-loadings (Table 2) and correlations among
constructs (Table 4). The cross-loadings among constructs are smaller compared to
their corresponding factor loadings (Table 2), and the square root value of AVE for
each construct is shown to be greater than correlations among constructs (Table 4). This
is a clear indication that items measuring constructs are distinct from others. This
signifies the validity and reliability of the measurement model (Fig. 1).
Measurement and Structural Model Evaluation
Analysis of Moments of Structures (AMOS) version 24 was used to assess the
goodness-of-fit of the structural and measurement model, and also to test the signifi-
cance of the respective hypothesis paths. Indices examined to test the overall fitness
included Normed Fit Index (NFI), Comparative Fit Index (CFI), Incremental Fit Index
(IFI), Root Mean Square of Error of Approximation (RMSEA) and Normed Fit Index
Fig. 1 Conceptual Framework
Examining Quality, Value, Satisfaction and Trust Dimensions: An... 481
Table 5 Fit Indices for the Measurement and Structural Model
Measurements Indices Criterion Results
Structural model Measurement
Absolute fit measures AGFI > .80 .918 .925
GFI > .90 .938 .947
RMSEA < .08 .044 .038
Incremental fit measures NFI > .90 .939 .950
CFI > .90 .974 .983
IFI > .90 .975 .983
CMIN/DF < 3.00 1.674 1.497
Note: AGFI=adjusted goodness-of-fit index, GFI=goodness-of-fit index, RMSEA= root mean square of
approximation of error, NFI=normed fit index, CFI=comparative fit index, IFI=incremental fit index
(NFI). These indices constitute the benchmarks for signifying the diverse categories of
model fit measures as presented in Table 5. From Table 5, there is sufficient evidence
that all measurements have good fit consistent with Wu (2010). Altogether, the study
model finds good fitness in view of the recommendations of (Elkaseh et al. 2016).
Hence, the measurement and structural models are acceptable (Table 6).
Hypotheses Testing and Effects
Next, the study tested the proposed hypothesis of the model. Figure 2 captures the path
analysis of the structural model. The output of analysis indicates that, service quality
(β=.321***, t=3.377, p<.001), Value (β=.139*, t=2.063, p<.05), trust (β=.215**,
t=2.793,p<.01) and satisfaction (β=470***, t=6.893, p<.001) were all revealed to have
a significant relationship with intention to use health insurance. These results are in
support of H1, H2, H3 and H4.
Table 6 Path Analysis of Structural Model
Path β t-statistics Hypothesis Interpretation
SQ →INT .321*** 3.377 H1 Supported
VAL → INT .139* 2.063 H2 Supported
TR→ INT .215** 2.793 H3 Supported
SAT → INT .470*** 6.893 H4 Supported
INT → AU .323*** 7.454 H5 Supported
R2
INT .212
AU .191
*p < 0.05 **p < 0.01 ***p < 0.001
482 Arkorful V.E. et al.
Fig. 2 Results of research model test with significance. Note: *p<0.05, **p<0.01, ***p,0.001
Furthermore, the study revealed intention to use health insurance to have a signif-
icant positive relationship with actual usage (β=.323***, t=7.454, p<.001). This is also
in support of H5. The results indicated the support of all proposed hypotheses.
Test of the Mediating Effect
As part of the data analysis for this research, we conducted the mediating effect analysis
to find out how intention could mediate between the Independent variables (IV) and the
dependent variable (DV). Test of mediating effects adopted the criteria by Zhao et al.
(2010) and Preacher and Hayes (2008).
As captured in Table 7, intention to use health insurance fully mediated the
relationship between service quality and actual usage. Also, intention to use health
insurance also fully mediated the relationship between health value and actual usage.
Similarly, the relationship between trust and actual usage was also fully mediated by
intention. And finally, the relationship between satisfaction and actual usage was also
partially mediated by intention to use health insurance.
Table 7 Mediating effect Analysis Results
Paths Indirect Effect Direct Effect Results
Size LLCI ULCI Size LLCI ULCI
SQ →INT→ AU .055 .019 .098 .057 −.063 .176 Full
VAL → INT→ AU .033 .005 .064 −.071 −.162 .021 Full
TR→ INT→ AU .036 .008 .071 .010 −.079 .100 Full
SAT → INT→ AU .108 .060 .164 .329 .218 .439 Partial
Note: Level of confidence=90%. LLCI/ULCI= lower/upper limit of confidence interval. SQ= service quality,
HV= health value TR= trust, SAT= satisfaction, INT= intention, AU= actual usage
Examining Quality, Value, Satisfaction and Trust Dimensions: An... 483
Discussion
The study seeks to investigate quality, value, satisfaction and trust dimensions regard-
ing individual’s intention and actual usage of health insurance. Health insurance usage
has been a medium for protecting poor individuals and households in both developed
and developing countries. Actually, it is touted as one of the ways to champion the
course of universal health coverage, targeted at extending healthcare to all populations
without anyone being left behind. Therefore, investigating predictors and possible
influencers of intention and actual usage would be key to promoting healthcare for
all people including the underprivileged, whiles informing structural mechanisms for
policy and decision making. As such our study adopts a predictive modeling technique
through SEM to predict intention and actual usage of health insurance.
Our study findings revealed service quality to have a significant positive relationship
with intention to use health insurance. This finding suggests that, a greater degree of
service quality administered by service providers, and enjoyed by service recipients or
patients, has the tendency to increase their intention to use health insurance. The
plausible reason for this finding could be that, populations in resource-deficient settings
have the propensity to have gravid expectations of health service delivery, more than
those in typical resource-rich urban areas. Given the situation that a majority of
Ghana’s poor population caught in the entangling web of extreme poverty situations
live in the three Northern Regions (Ghana Statistical Service 2014), the relationship
between quality concerns, and intention to use is understandable especially when
situated within the context of the stark deprivity that characterise these areas in terms
of lack of access to qualified health personnel (Nketiah-Amponsah et al. 2019).
Moreover, this result could be interpreted in the light of the dearth of health facilities in
the study areas. Health service delivery in the three northern regions is complemented by
health-related non-governmental organisations and other missionaries. Our study finding is
consistent with prior studies in Ghana (Andoh-Adjei et al. 2018; Nketiah-Amponsah et al.
2019) and Iraq (Burnham et al. 2011). On this basis, individuals who perceive high quality
of care are more likely to use than those with low quality perceptions (Dong et al. 2009). To
this end, it could be said that, whenever people are assured of meeting their expectations
from a particular health system, they are likely to use as well. Quality factors could be
intersectional to include, but not limited to medication (Oriakhi and Onemolease 2012),
service providers attitude (Adebayo et al. 2015), geographic location and proximity to
service providers, as well as service provider-recipient communication (Andoh-Adjei et al.
2018), and long waiting times and efficiency of treatment regimes (Adebayo et al. 2015). In
the views of Adebayo et al. (2015) and Arkorful et al. (2018), the attraction and retention of
health insurance users requires for a constant intermittent neck turn look at quality factors.
Furthermore, statistical results of data analysis provide evidence to support the
significant positive relationship between value and intention to use health insurance
scheme. This finding implies that, value as a derivative of a general utility function,
constitutes one of the primary factors that spur health insurance use among both
enrollees and prospective enrollees. The plausible reason for the significance and
centrality of value to health insurance use intention could be attributed to the largely
unstable financial situation of under-resourced settings denizens who tend to place
much value on social protection and pro-poor schemes meant to provide safety nets for
them. In accounting for quality and value premium placed on health insurance, Dixon
484 Arkorful V.E. et al.
et al. (2013) ascribes the variance in dimensions between the resource-rich and poor to
resource availability. The relevance of value to insurance use is confirmed by (Andoh-
Adjei et al. 2018 & Adebayo et al. 2015).
As hypothesized, statistical output of data analysis revealed satisfaction to be
positively related to adoption intention. This is an empirical testimony to the fact that,
as much as the policy sustainability of health insurance is largely based on subscribers,
it is equally based on intention to use. The relevance of service seekers/recipient’s
satisfaction to intention to use health insurance in developing countries predominated
by poor populations is confirmed in a study of community-based insurance study in
Ethiopia (Badacho et al. 2016). The study confirms high satisfaction as likely to
translate into high usage and increased healthcare utilization. Another study in Turkey
(Jadoo et al. 2012) and Nigeria (Mohammed et al. 2011) also confirm the significance
of satisfaction to health insurance use. Based on the study finding, it could be
concluded that, greater satisfaction is likely to translate into expansion and increased
coverage in healthcare access, which is cardinal to advancing universal health coverage
(WHO 2005). For policy efficiency and effectiveness purposes, it becomes important
for a constant investigation of factors associated with service seekers satisfaction to
understand what actually underpins this dimension, to further inform service change
and improvements (Zineldin 2006).
In relations to the study hypothesis, further interrogation revealed trust to have a
positive significant relationship with intention to use health insurance. This result
reveals trust as a predictor of intention to use insurance. The relevance of trust does
not only act as a motivator, but also, helps in forming a positive intention towards
health insurance use. Trust has been confirmed in prior health insurance studies as a
determinant of individual and population use, and enrolment (Ozawa and Walker
2009). This could be construed to imply that, individuals, and even household heads
with greater trust in the health insurance will be willing to pay and use (Ozawa and
Walker 2009). To enhance trust in health insurance, (Arkorful et al. 2018) among other
things recommend transparency and clarity regarding understanding of benefits, and
eschewing negative behaviours (Adebayo et al. 2015). Trust is very cardinal to
insurance. This is because, health insurance all over the world subsist on voluntary
contributions from people. As such, given the financial contribution of people through
premium payments, a reasonable degree of trust needs to be maintained to ensure
patronage and sustainability (Adebayo et al. 2015).
And finally, the study results confirmed that, intention to use had a significant
positive relationship with actual usage. It is however important to emphasize that, the
combined effects of quality, value, satisfaction, and trust additively contribute to predict
intention to use. Together, these further incrementally contribute to determine actual
usage. As much as our study confirms the appropriateness of the study model, it also
proves that, intention to use, and actual usage of the health insurance, is determined by
a confluence of factors composed of quality, value, satisfaction and trust dimensions.
Conclusions
Our study presents a novel model to predict actual usage of the health insurance policy
scheme in Ghana. The study’s research model was segmented into three (3)
Examining Quality, Value, Satisfaction and Trust Dimensions: An... 485
components to include independent variables: service quality, value, trust and satisfac-
tion; Mediator (Intention to use health insurance), and dependent variable; actual usage.
In the study model, analysis of data revealed that, quality, value, trust and satisfaction
dimensions were critical to influencing intention to use, which in turn predicts actual
usage of health insurance in Ghana. The study results suggest that, a higher degree of
perception regarding service quality, value, trust and satisfaction are very central to
intention to use (i.e. enrollment, renewal, retention and usage). The amalgam of these
dimensions collectively and incrementally contributes to predicting intention to use and
actual usage. Most importantly, the utilization of a structural equation model (SEM)
provides additional originality of our study. The use of SEM, among other things help
test and verify the research model. Furthermore, the use of SEM in this study helped in
unraveling the complexities surrounding pro-poor social policy use, precisely within
health policy domains. Our study employs SEM approach to test research hypotheses
and identify statistically significant predictors, and empirically establish the model for
not only policy purposes, but also, for guiding and providing insights for better
decision-making regarding health insurance policy. Our study illuminates on relevant
theoretical, as well as practical consequences for researchers, academicians, health
policy makers and health sector stakeholders as well.
Implications for Theory and Practice
Our study has a plethora of theoretical implications. In view of the quality, value,
satisfaction and trust dimensions employed for the study, it is confirmed that, they are
sufficient predictors of intention and actual usage of health insurance in Ghana. Given
that the health insurance is a health sector social policy intervention meant to provide
protection for vulnerable and poor populations from health expenditures, it is obvious
that, as much as individual, group or individuals or households are likely to repose a
huge trust in health insurance, they will be expecting quality service in return. More-
over, it is also apparent that, in much the same way, they will be expecting a high value
and satisfaction in return. In this study, as captured in the sociodemographic charac-
teristic of study participants in Table 1, it is obvious that, majority of participants have
low income levels. This is a confirmation that such populations will be expecting much
from health insurance. The study results indicate that, users’ intention to use would be
predicated on quality, value, satisfaction and trust. As such, an integrated approach is
employed to understand antecedents of actual usage of health insurance.
Furthermore, the study also has practical implications for health policy. The pro-
posed study model, and a comprehension of the correlations between various decision
variables sheds substantial light on possible considerations for making effective health
policies. In Ghana, health insurance has enhanced an appreciation in the health seeking
behavior of populations whiles extending protection to an appreciable segment of the
population. That notwithstanding, perceptions of quality, value, satisfaction and trust
have in recent times been of much concern. This simply implies that, a decline or
depreciation in consumer perceptions regarding any of these dimensions could poten-
tially discourage the enrolled and potential enrollees from enrolling, renewing,
retaining and using health insurance, thereby posing policy sustainability threats. It is
against this backdrop that our study proffer mechanisms for reforms. On this score,
health policy makers from around the work, and more particularly in Ghana should
486 Arkorful V.E. et al.
therefore tap into this study findings to formulate and further implement appropriate
strategies to enhance actual usage of health insurance.
Limitations and Scope for Future Research
This is the first empirical study measuring quality, value, satisfaction and trust dimen-
sions regarding intention and actual usage of health insurance. As much as the study
has several theoretical and practical strengths which have been highlighted in the
preceding discussions, it also has limitations which needs to be delineated to guide
the conduct of future research and policy. Firstly, the data for the research was collected
from respondents in Ghana. Also, the study used a questionnaire survey to elicit data
from study participants composed of subscribers and non-subscribers. As such the
generalization of the study findings mut be done cautiously. On this basis, the study
strongly recommends future studies to consider concentrating on either subscribers or
non-subscribers separately. And finally, given that the effects of sociodemographic
variables were not considered, we suggest future studies to explore these factors. These
however do not invalidate the study findings. This study could be a starting point for
the conduct of further future empirical studies.
Funding None.
Compliance with Ethical Standards
Conflict of Interest None.
Informed Consent Informed consent was obtained from all individual participants included in the study.
Ethical Approval All procedures performed in this study were in conformity with the ethical standards of
the institutional and/or national research committee and with the 1964 Helsinki declaration and its later
amendments or comparable ethical standards.
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Vincent Ekow Arkorful is currently a PhD candidate at the Hong Kong Baptist University, Department of
Government and International Studies. His main research interests include public administration, public policy
analysis, social policy, health and technology policy, health and politics, decentralization and participatory
governance, voting and voters behavior, parliamentary studies, development studies, entrepreneurship and
sustainable development.
Benjamin Kweku Lugu is currently a postgraduate masters research student at the University of Science and
Technology of China (USTC), School of Management. His research interests include big data, consumer
behavior, statistics, economic policy and management and entrepreneurship.
Anastasia Hammond is affiliated to the University of Ghana (UG), Department of Psychology and Home
Science. Her research interests include peace studies, mental health, human behavior and politics.
Ibrahim Basiru is a PhD candidate at the University of Science and Technology of China (USTC), School of
Management. His areas of interest include Climate Change, Environmental Sustainability, Health Policy, and
Local Government Administration.
Frederick Appiah Afriyie is affiliated to the Zhongnan University of Economics and Law (ZUEL). His
research interest focuses on International Relations and Security, Public Administration, Law and Social
Policies.
Bobita Mohajan is postgraduate student in the School of Public Affairs, University of Science and
Technology of China. Her reserach interest covers Public Administration and public Policy