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RESEARCH ARTICLE
Readiness of Ghanaian health facilities to
deploy a health insurance claims
management software (CLAIM-it)
Gordon Abekah-NkrumahID
1
*, Maxwell Antwi
2
, Alex Yao AttacheyID
3
, Wendy Janssens
4
,
Tobias F. Rinke de WitID
5
1Department of Public Administration and Health Services Management, University of Ghana Business
School, University of Ghana, Legon, Accra, Ghana, 2Management Department, Pharm Access Foundation,
East Legon, Accra, Ghana, 3Research and Innovartions Department, Pharm Access Foundation, East
Legon, Accra, Ghana, 4Amsterdam Institute for Global Health and Development, School of Business and
Economics, Vrije Universiteit, Amsterdam, The Netherlands, 5PharmAccess Foundation and Department of
Global Health, Amsterdam University Medical Centre, University of Amsterdam, Amsterdam, The
Netherlands
*gabekah-Nkrumah@ug.edu.gh
Abstract
Introduction
Inadequate, inefficient and slow processing of claims are major contributors to the cost of
health insurance schemes, and therefore undermining their sustainability. This study uses
the Technology, Organisation and Environment (TOE) framework to examine the prepared-
ness of health facilities of the Christian Health Association of Ghana (CHAG) to implement a
digital mobile health insurance claims processing software (CLAIM-it), which aims to
increase efficiency.
Methods
The study used a cross-sectional mixed method design to collect data (technology and
human capital capacity and baseline operational performance of claims management) from
a sample of 20 CHAG health facilities across Ghana. While quantitative data was analysed
using simple descriptive statistics statistics (frequencies, mean, minimum and maximum
values), qualitative interviews were recorded, transcribed and abstracted into two major
themes that were reported to re-enforce the quantitative findings.
Results
The quantitative results revealed challenges including inadequate computers and accesso-
ries, adequate numbers and skills for claims processing, poor intranets and internet access,
absence of a robust post-implementation support system and inadequate standard operat-
ing procedures (SOPs) for seamless automation of claims processing. In addition to the
above, the qualitative results emphasised the need to make CLAIM-it more flexible and
capable of being integrated into third-party softwares. Notwithstanding the challenges, deci-
sion-makers in CHAG health facilities see the CLAIM-it software as having better functional-
ity and superior capabilities compared to existing claims processing systems in Ghana.
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OPEN ACCESS
Citation: Abekah-Nkrumah G, Antwi M, Attachey
AY, Janssens W, Rinke de Wit TF (2022)
Readiness of Ghanaian health facilities to deploy a
health insurance claims management software
(CLAIM-it). PLoS ONE 17(10): e0275493. https://
doi.org/10.1371/journal.pone.0275493
Editor: Syed Ahmad Chan Bukhari, Yale University,
UNITED STATES
Received: March 19, 2021
Accepted: September 19, 2022
Published: October 5, 2022
Copyright: ©2022 Abekah-Nkrumah et al. This is
an open access article distributed under the terms
of the Creative Commons Attribution License,
which permits unrestricted use, distribution, and
reproduction in any medium, provided the original
author and source are credited.
Data Availability Statement: All relevant data are
within the manuscript and its Supporting
Information files.
Funding: The article is based on a report funded by
the Pharm Access Foundation, Ghana. Pharm
Access provided support in the form of salaries for
the corresponding author (GAN), who was mainly
responsible for study design, data collection and
analysis, report writing, decision to publish and
preparation of the manuscript. Staff members of
the funder who are co-authors of this manuscript
Conclusion
Notwithstanding the challenges, the CLAIM-it software is more likely to be adopted by deci-
sion-makers, given the positive perception in terms of superior functionality. It is important
that key actors in claims management at the National Health Insurance collaborate with rele-
vant stakeholders to adopt the CLAIM-it software for claims processing and management in
Ghana.
Introduction
Achieving universal health coverage (UHC) constitutes a key objective of health policy in both
developed and developing countries [1]. Efforts to improve UHC are paramount especially in
developing countries where disease burden and mortality are high. In response to this, Ghana
introduced a National Health Insurance Scheme (NHIS) in 2003 to reduce financial barriers to
health service utilization [2]. NHIS reached 38% coverage in 2013, 39% in 2016, and 40% in
2020 [3]. The scheme covers a wide range of diseases (about 95%) in Ghana and exempts sev-
eral groups (children under 18, those above 70 years of age, pregnant women, contributors to
the Social Security and National Insurance Trust (SSNIT) and those who are extremely poor)
from paying premium. The sources of funds for the NHIS are 2.5% Value Added Tax on vata-
ble transactions, 2.5% of contributions of the SSNIT Fund, premium paid by members of the
scheme, registration fees as well as interest on funds invested by the National Health Insurance
Authority (NHIA) [4].
Since the establishment of the NHIS, the scheme has adopted different methods for pur-
chasing services from providers in an attempt to improve on efficiency and reduce costs. The
NHIS started with a fee-for service (FFS) arrangement in 2005. In 2008, the diagnostic-related
group system of payment, known as the Ghana Diagnostic-Related Grouping–G-DRG system
was introduced [3,4]. Besides the G-DRGs, NHIS also piloted a capitated payment scheme in
the Ashanti region in 2012. Although the G-DRGs and the capitation system (currently aban-
doned) were supposed to increase efficiencies under the FFS, costs rather escalated [4].
Although this increase is partly attributed to growth in membership of the scheme and there-
fore utilization, supply and demand side moral hazards have also been identified as major
causes of the increased costs [5–7].
A key contributor to high health insurance costs is the processing of claims. This ranges
from overbilling of medicines, inappropriate application of tariffs, duplication of claims, lack
of evidence on diagnosis to back claims, absence of a link between treatment and diagnosis,
treatment outside the defined benefits package, irrational prescription of medicines, inflation
of the quantities of medicine supplied to subscribers, provision of services above accreditation
level and overbilling of medicines [4,8]. This has contributed to financial losses to the NHIS
and thus is threatening the scheme’s sustainability. Also, these issues contribute to delays in
claims processing and payment, leading to decreased trust and participation by both patients
and providers, as well as provider adaptive mechanisms that have adverse implications for
availability and quality of care [7].
To address these challenges, the NHIA in collaboration with PharmAccess Group devel-
oped a software (CLAIM-it) to manage claims processing. CLAIM-it is a four-module applica-
tion, comprising a claims entry module, a receiving (aggregation) system, a claims
adjudication module and a Regional and District Health Director’s reporting module. The
claims entry module implements and enforces all the necessary claims generation rules and
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provided inputs and review comments which are
clearly articulated in the ‘author contributions’
section.
Competing interests: The authors have declared
that no competing interests exist.
protocols of the NHIA. Hence claims submitted for adjudication are validated by the software
and this ensures due diligence prior to claims submission. The claims entry module runs fully
offline and thus allows users to work independent of the internet. It can be installed and oper-
ated on a single user computer or implemented on a network, with as many user nodes as
needed. It can also be integrated into any existing Hospital Management Systems (HMS).
Claims submission takes into account the lack of internet in some parts of Ghana and the
distance travelled by some facilities to submit their claims to Central Processing Centres
(CPCs). Claims generated via CLAIM-it can be submitted either directly to NHIA over the
internet or with data downloaded and saved on a flash drive for submission at a local district
NHIA office or CPC. Submitted claims are aggregated in the receiving system, and using a
newly developed provider coding system, are grouped according to the region, district, type of
facility and facility ownership, before distribution to the various CPCs for adjudication and
reporting. Reports generated by the receiving system before and after adjudication are avail-
able to both the NHIA and respective Regional and District Directors through an online por-
tal. The reports provide an overview of the types of claims submitted by providers, the total
volume of claims submitted, cost associated with claims submitted and submission date of the
claims. Regional and District Directors of Health can use the information provided through
the reporting system to plan. It is anticipated that providers in the future will be able to track
progress of their claims from submission through adjudication to payment. Thus, CLAIM-it is
expected to tackle inefficiencies in claims generation, claims collation, claims storage and
claims submission and vetting. With the NHIA claims vetting protocols built into the CLAIM-
it software, it is expected that providers will experience reduced delays in claims processing
and the NHIA will also be able to reduce time to vet claims. The CLAIM-it software was
piloted in a few CHAG health facilities and is currently being scaled up to the full CHAG net-
work of morev than 300 health facilities. This study examined the readiness of CHAG health
facilities to implement CLAIM-it. Particular attention was paid to human resources capacity
(numbers and skill sets), technological preparedness (hardware and relevant infrastructure
readiness status of selected health facilities), claims generation and submission, benefits of the
CLAIM-it application and potential implementation challenges. Results are put in the context
of the operational performance of existing claims management systems, with emphasis on
claims output (the value of monthly claims and deductions as well as the average number of
days it takes to submit claims).
Relevant literature
It is widely acknowledged that the use of Information Technology (IT) has noteworthy effects
on the productivity of businesses [9]. Organizational readiness is a major factor in implement-
ing a new technology such as the CLAIM-it application. The Technology Organisation Envi-
ronment (TOE) framework [10] was used as a conceptual model to examine the readiness of
health facilities to implement the CLAIM-it application, based on it wide applicability across
geography and industries including; manufacturing [11], healthcare [12], retail and financial
services [13]. The TOE framework [14] suggest that three contexts (technological, organiza-
tional and environmental) influence processes adopted by a firm to implement a technological
innovation [14]. The technological context describes current practices and equipment internal
to the firm as well as the set of available technologies external to the firm [15,16]. Organiza-
tional context refers to the scope, size, resources and managerial structure of the organization
that constrain or facilitate use of technology [17,18]. The environmental context is the arena
in which a firm conducts its business,—its industry, competitors, and dealings with the gov-
ernment [19,20].
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The technological context has been represented by several variables such as relative advan-
tage, complexity, IT infrastructure, IT expertise [16]. Relative advantage can be defined as the
extent to which an innovation or a technology is perceived as offering an advantage over previ-
ous ways of performing the same task [21]. Relative advantage can be measured in terms of
performance and convenience. Literature suggests that organizations are more likely to imple-
ment a new technology if the technology can bring about better organizational performance
and higher economic gains [22]. Complexity is defined as the degree to which an innovation
or technology is regarded as relatively difficult to understand and use [23]. If technology is
seen to be complex by employees, it negatively influences adoption or implementation of that
technology [18]. IT infrastructure is defined as collection of physical technology resources
which provide the basis for IT-related purposes [24]. Readiness to implement technology
depends on availability of IT infrastructure [25]. Additionally, IT expertise, which refers to
employees’ knowledge of using technologies [26] positively influences an organisation’s likeli-
hood of implementing new technology-related applications [27].
Also, firm size constitutes an important factor that influences organizational performance
and also flexibility to implement technology [28]. Large firms, unlike small firms have more
resources and hence are likely to adopt and implement a new technology faster [29]. However,
in some instances, small firms were swift and flexible in implementing technology, especially
when financial and technological resources are controlled for [30]. A firm’s scope (the geo-
graphical extent of an organization’s operations) is also associated with a higher likelihood of
technology adoption and implementation [20,30,31]. Finally, the need to out-perform com-
petitors [32], support from an organization’s top management [33] and regulators [26] as well
as financial and human resources [34] have all been shown to positively influence the adoption
of a new technology.
Although the TOE framework is applicable to technology adoption in diverse contexts
(electronic data interchange [35]; open systems [36]; web site [10]; enterprise resource plan-
ning [37] and business to business e-commerce [38]), specific contexts are associated with
unique sets of factors that influence adoption [39]. Factors that have been identified as deter-
minants of adoption are technology competence, firm size, global scope, enterprise integra-
tion, competition intensity and regulatory environment [40], IT infrastructure and
management, government regulation and promotion [41].
On the basis of the above literature, we argue that human resource capacity, available tech-
nological infrastructure, existing processes for generating and submitting claims, knowledge
of potential benefits and possible implementation challenges of the CLAIM-it application as
well as output from the existing claims management system constitute key factors that will
enable or constrain adoption and implementation of the CLAIM-it application by health
facilities.
Methods
Study design
A cross-sectional multi method design was used to address the objectives of the study through
the use of survey that was subsequently augmented by inerviews with staff.
Sampling
The study focused on CHAG health facilities in Ghana that had not yet implemented the
CLAIM-it software. Health facilities fulfilling this criteria were 115 out of a total of 333. These
comprised hospitals (37), Health Centres/Primary Health Centres/Community Health Plan-
ning and Services- CHPS (HCPHC-CHPS) (11), and Clinics (67). A four-criterion process was
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used to select a representative sample from the 115 health facilities. First, the sample size was
set at 20 health facilities, deemed sufficient to reach information saturation as per previous
studies [42]. Second, to achieve geographic representativeness, Ghana’s three geographic zones
were used to allocate the 20 health facilities proportional to the number of health facilities in
each zone. This meant 10, 4 and 6 health facilities for the Middle, Northern and Coastal zones
respectively. Third, types of health facilities were selected proportional to the number of each
type of health facility found in each geographic zone. Thus, 5 hospitals, 4 clinics and 1
HCPHC-CHPS were selected in the Middle zone; 2 hospitals and 2 clinics were selected in the
Northern zone, and 3 hospitals, 1 clinic and 1 HCPHC-CHPS were selected in the Coastal
zone. Physical accessibility of providers was considered as a requirement for selection into the
sample. Finally, selection of specific providers was done to capture the widest possible range of
variation in responses.
Data collection
Following from the literature review, readiness of health facilities to deploy the CLAIM-it soft-
ware is argued to be contigent on available human resource capacity, technological infrastruc-
ture, sound existing processes for generating and submitting claims, knowledge of potential
benefits (including coparative strengths of existing claim management software and the
CLAIM-it software) and possible implementation challenges of the CLAIM-it software. Thus,
data collected through a survey using closed and open ended questions as well as semi-struc-
tured interviews focused on the above. Whiles the survey focused on on facility preparedness
for the deployment of CLAIM-it (technological capcity and human capital capcity); claims
generation and submission and baseline operational performance of the claims-management
unit of each health facility (value of claims and deductions), the interviews focused on claims
generation and submission and knowledge of CLAIM-it and potential challenges. Each health
facility answered one questionnaire which contained two sections; survey and interview guide.
Before data collection, a draft of the questionnaire was pre-tested using two CHAG health
facilities in Accra that did not participate in the data collection process. The pre-tested ques-
tionnaire was amended to reflect comments from the pre-testing. The questionnaire (both sur-
vey and interviews sections) were administered by two trained enumerators (a female and
male PhD candidates at the time of data collection, who did not have any relationship with the
facilities or officers interviewed) to three staff members of each health facility whose roles are
related to the claims processing functions of the health facility (the accountant, an officer of
the hospital in-charge of claims processing and the administrator). Although the three officers
were restricted to different sections of the survey (sections mainly relevant to their work), they
were interviewed together to enable triangulation of earlier answers and/or to ask follow-up
questions. The interviews were audio-recorded to enable discussions arising from follow-up
questions to be captured. Beside triangulation, the interview re-enforced findings from the
survey.
Analysis of data
To examine implementation readiness, the human resources and technological capability of
the Claims Unit of the health facilities studied were examined. In addition, the claims genera-
tion and submission process, knowledge on the CLAIM-it software as well as potential imple-
mentation challenges were also examined. Operational performance of the claims
management system, with emphasis on claims output (the value of monthly claims and deduc-
tions as well as the average number of days it takes to submit claims) was studied, both as a
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basis to establish whether the CLAIM-it application has an advantage over existing systems
and also as a basline for follow-up evaluations.
Simple descriptive statistics (frequencies, mean, minimum and maximum values) were
used to analyse the survey (human resource and technology preparedness, claims generation
and submission and claims output). To better understand the quantitative findings, a qualita-
tive analytical approach was used to re-enforce findings from the survey. Specifically, recorded
data were transcribed into an MS-Word document. The transcripts were compared to the
audio tape to ensure that data on the tape was captured accurately. Information from the tran-
scripts were abstracted into seven themes but captured under two broad themes in the results
(claims generation and submission and knowledge of CLAIM-it and potential implementation
challenges) and constituted the basis for presenting the results.
Ethical consideration
Ethical approval was received from the Ethical Review Committee of CHAG with serial num-
ber 190001. Management of each participating health facility gave a written administrative
approval for the study to be conducted in their health facility. In addition to the administrative
approval, participating officers gave verbal consent and were informed that they could with-
draw from the study at any time without any consequence whatsoever.
Results
Profile of health facilities
The profiles of health facilities assessed for the study are shown in Table 1.
The average health facility bed size was 68 (maximum 250; minimum 10), less for rural
areas than urban centers (results not shown). The workforce averaged 154 workers (minimum
21; maximum 483), with health facilities in urban areas having a relatively higher average (192)
compared to the average in rural areas (84). Patient turnover averaged 3,534 patients a year
(minimum 300; maximum 11,382). The turnover in rural areas was 2,074 patients, which was
twice as low as the average patient turnover in urban areas. Out of the 20 facilities examined,
17 gave information related to their annual revenue. The average annual revenue is GH
₵2,840,000 (about USD 50,000) with minimum and maximum revenue figures of GH₵24,000
and GH₵11,000,000 respectively (Table 1). Average revenue in rural facilities was much lower
than their counterparts in urban areas. Also, 10 out of 20 of the health facilities reported the
current value of their assets, which averaged GH₵4,160,000, with rural areas having a much
lower value (GHC 1,290,000) compared to urban areas (GHC 6,080,000). Health facilities on
the average had operated for 30 years, with a maximum of 88 years, minimum 5 years. Consis-
tent with the current trend, urban hospitals have on the average been in operation for a much
Table 1. Profile of health facilities studied.
Variable NHF Mean Min Max
Facility size in terms of bed capacity 20 68 10 250
Total facility workforce 20 154 21 483
Average patient turnover in facility 20 3,534 300 11,382
Size of annual revenue (GH₵) 17 2,840,000 24,000 11,000,000
Value of facility assets (GH₵) 10 4,160,000 153,000 15,500,000
Number of years in operation 20 30 5 88
NB: The value of the dollar to the Ghana Cedi (GHC) is USD 1 to GHC 5.7; patient turnover is annual and NHF is number of health facilities
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longer period (32 years) compared to rural health facilities (26 years). Finally, 11 of the health
facilities examined do not use a health management information system, with 5 of them
located in an urban area and 6 in rural areas (results not shown).
Human resource capacity for claims management
In this sub-section we present results on human resource (HR) capacity (see Table 2) as rele-
vant for claims processing, to assess whether HR would provide sufficient manpower for
implementing the CLAIM-it software.
The data collected indicate that an average of 4 staff work in the Claims Management Unit,
with the least number of staff being 1 and a maximum of 8. Additionally, 3 out of the 4 staff in
the Claim’s Unit are permanent staff with 1 being casual. In terms of Claim’s Unit staff respon-
sible for vetting, an average of 2 are responsible for this, with maximum of 6 and a minimum
of 0 (i.e. no person solely assigned to claims), with about 2 workers on the average involved in
data entry (maximum 6) and trained in MS-Office applications (maximum 7). In terms of
usage, 79%, 53% and 21% of the staff using MS-Office applications indicated that they use
Word and Excel, PowerPoint and Outlook and MS Project respectively.
Technological preparedness for CLAIM-it
Table 3 presents information on technological resources of health facilities that may be rele-
vant for the adoption of an electronic claims processing system such as CLAIM-it.
Health facilities owned an average of 23 computers (minimum of 1 and maximum of 85).
On the average, 3 functional computers were dedicated to claims processing, with some health
facilities recording a maximum of 6 whiles others did not have any dedicated computers for
data processing at all. Also, there was an average of 1 functional electrical surge protector in
the health facilities studied, although some had as many as 6, with others having none. In addi-
tion, 50% (10) of health facilities in the study had local area networks (LAN), 55% (11) had
arrangements to support their hardware and LAN, with 60% (12) having backup power sys-
tems in place.
Claims generation and submission
Table 4 presents information on claims processing procedures to assess potential CLAIM-it
implementation readiness.
Thus, 5 out of 20 health facilities had written guidelines or manuals (Standard Operating
Procedures, SOP) for capturing or entering data and processing claims. From the 5 with guide-
lines or SOPs, 1 gave a copy of the SOPs out, 3 showed a copy of the SOPs, with 1 unable to
show a copy of their SOPs. Furthermore, all the health facilities studied were credentialed
NHIS service providers. However, only 12 of them were able to present documentation to this
Table 2. Human resource capacity for claims management.
Variable Obs Mean Min Max
Total number of staff working in the claims unit 20 4 1 8
Total staff who work in the claims unit as permanent employees 20 3 0 6
Total staff who work in the claims unit as casual employees 20 1 0 3
Number of claims staff responsible for claims vetting 20 2 0 6
Number of claims staff involved in JUST data entry 20 2 0 6
Number of claims staff trained in MS-Office 20 2 0 7
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effect. Additionally, 3 of the health facilities submit their claims to the district office for pro-
cessing, while the rest (17) submit their claims to the Central Processing Center.
With respect to the submission process, 10 used electronic only submission process, fol-
lowed by both electronic and paper (8) and paper only (2). In terms of the storage media used
by the health facilities, all the health facilities kept their claims electronically, mainly using stor-
age media such as a dedicated server, computer hard disk, external hard drive, CD or pen
drive. Overall, 5 of the health facilities surveyed used a dedicated server, 1 health facility used
dedicated server and external hard drive, 8 used computer hard disk, 1 used computer hard
disk, CD and pen drives, 1 used computer hard disk, CD, pen drives and external hard drives,
2 used CD or pen drives and 1 used external hard drives. In addition to storing data
Table 3. Technological resources for claims management.
Variable Obs Mean Std.Dev. Min Max
Panel A: Number of Computers
Number of functional computers /laptops/tablets in the facility 19 23 27.64 1 85
Number of functional computers in this facility solely dedicated to claims data entering and processing 20 3.05 1.79 0 6
Number of functional surge protectors in this facility solely dedicated to claims data entering and processing 20 1.05 1.63 0 6
Panel B: Availability of LAN and Accessories
Variable Response Freq. Percent
Do you have a local area network in place (LAN) Yes 10 50
No 10 50
Do you have in place an arrangement to support your hardware and LAN Yes 11 55
No 9 45
Do you have in place backup power systems in time of power failure Yes 12 60
No 8 40
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Table 4. Frequency distribution of claims generation and submission.
Variable Response Freq. Percent
Does this facility have a written guideline or manual SOP for capturing/
entering data and processing claims
Yes 5 25
No 15 75
If YES request to obtain or see a copy Copy obtained 1 20
Copy requested and
seen
3 60
Copy requested but not
available
1 20
Is this facility a credentialed NHIS service provider Yes 20 100
No 0 0.00
If YES request to obtain or see a copy of credentialed certificate Copy requested and
seen
12 60
Copy requested but not
available
8 40
If YES, please state where your claims are submitted to for processing. District Office 3 15
CPC 17 85
In what form do you usually submit your claims Paper only 2 10
Electronic only 10 50
Both paper and
electronic
8 40
Does this facility keep claims data electronically Yes 19 100
No 0 0
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electronically, 13 health facilities used off-the-shelve software and MS-Excel to generate and
process claims, with the remaining using other software.
The results of the qualitative data suggest that claims management is made up of three
stages: generation of the base data, processing and validation of the data and finally submission
of the data to the NHIA. Two systems (manual and electronic) are used for the generation of
base claims data. However, irrespective of the system used, the qualitative results indicate that
the validation and processing of claims is done electronically, either using MS-excel, an off-
the-shelve or a bespoke software, with most of the vetting and processing protocols automated.
The submission is mostly done electronically as already demonstrated in the quantitative
results, with only a few health facilities submitting manually as per the quote below.
“For claims we normnally have data from our transactions which has already been captured
into our HIS.That data is entered into another software which helps us to validate the claims
for inclusion in the claims to be submitted for the month.We then submit the claims report ot
NHIA for reimbursement”.. . .. . .. . .. . .. . .. . ..R4
More importantly, inherent challenges were identified with the existing system(s) for gener-
ating and submitting claims. For example, those who use a manual system experienced chal-
lenges such as (1) the length of time it takes to process claims, (2) the fact that the process is
error ridden (due to diagnosis mismatch, lack of access to pricing information) and (3) equally
expensive due to the cost of inputs (personnel and other inputs) used. For those who use an
electronic system to generate the base data and then use a bespoke software to validate and
process claims, the main complaint was inadequate computers and accessories like power
back-ups and lack of appropriate technical support from vendors as per the quote below.
“Validating claims for submission can be a tedious job,especially if you have to enter the data
into your health insurance software manually”. . .. . .. . .You will have too many mistakes,
leading sometimes to the rejection of claims and it takes all your time and delays the submis-
sion of the calims to NHIA”. . .. . .. . .. . .. . .. . .. . .. . .Respondent 5
“Using an automated claims management system has been helpful interms of reducing errors
and the time it takes to compile and validate claims. . .. . .. . ...Our main challenge is comput-
ers,power buckups and and maintenance support”. . .. . .. . .. . .. . .. . .. . ...Respondent 2
The qualitative results further suggest that internet access is a major challenge, especially given
that it is needed to access the NHIA system to generate a unique code for patients. For those who
had just started using the CLAIM-it software (testing), a major source of frustration was the inflex-
ibility of the software and the lack of thorough training to help users to navigate the software.
“The CLIAM-it software is very good,but the problem is that it is not flexible.This is a hospital
and sometimes you have an emergency where you will not be able to do things as expected.So
it should be possible for the software to allow you to do want you have to do and later make the
corrections if needed.Else we will loose our clients. . .. . .they are mostly unhappy when yu say
the software is nnot making it possible”.. . .. . .. . .. . .. . .. . .. . .. . .. . .. . .Respondent 13
Knowledge of CLAIM-it and potential implementation challenges
The qualitative interviews revealed that almost all of the respondents knew of CLAIM-it’s exis-
tence, with some respondents participating in specific training programmes. Respondents
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were unanimous that CLAIM-it is potentially superior to current systems being used. The
main areas of expected benefits mentioned were: reduction in errors due to the inbuilt NHIA
validation protocols, speed in claims processing, cheaper alternative for processing claims due
to the fact that there is no need to print the claims, thus reducing cost of paper. Health facilities
also indicated that the possibility of online claims submission means one may not need to
physically go to the Central Processing Center, a potential cost saver. Some respondents also
suggested that CLAIM-it can reduce the level of stress of staff in the claims unit. Additionally,
the respondents indicated that with CLAIM-it, one is able to have access to detailed informa-
tion on the claims submitted, which can be used for management decision-making. The above
findings is captured in the quotes below.
“I will prefer using the CLAIM-it software because it has the NHIA protocols as part of the
software.In addition,you can submit the claims online to the CPC and this saves time and
can save paper from printing”. . .. . .. . .. . .. . . Respondent 16
“The fact that the CLAIM-it software can be used with our current software,for me is a game
changer.This means that we can just import from our software and CALIM-it can help is to
process and validate claims in a short time”. . .. . .. . .. . .. . ..Respondent 3
Notwithstanding the benefits articulated above, majority of the respondents indicated that
there could be challenges with the roll-out and implementation of CLAIM-it, with the follow-
ing constituting major areas of concern:
• The need for adequate computers and accessories, reliable local area networks and internet.
• The need to for adequate personnel who have the skill to use computers for claims process-
ing. In this regard, adequate training was emphasised.
•Given that CLAIM-it adheres to the NHIA vetting protocols, the software will in most cases not
allow users to proceed unless the transactions being processed adhere strictly to the respective
NHIA vetting protocols. Hence potential users suggested the need to ensure that CLAIM-it is
flexible enough to allow for the processing of certain transactions even though they may not
meet the vetting protocols at the time of processing. To them what is most important is that
they can later correct whatever anomalies before finally submitting such claims.
• The need to ensure that there will be adequate technical support to the users of CLAIM-it so
that their technical challenges can easily be addressed.
• The need to find a way to integrate CLAIM-it into existing software that generates the base
data for claims processing. The challenge raised was that manually entering information that
is available in electronic formats from third-party software into CLAIM-it is tedious and
time consuming.
Claims output
In this sub-section, we present results on the performance of the current claims management
system in terms of the output it delivers and this includes the value of monthly claims and
deductions as well as the average number of days it takes to submit claims.
Value of monthly claims and deductions
Table 5 presents descriptive statistics of the number and value of total monthly claims from
July 2018 to June 2019.
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May and June 2019 recorded the highest average monthly claims of GH₵123,000. Addition-
ally, Fig 1 indicates that the average value of monthly claims has been increasing since Febru-
ary 2019, with the rate of increase being much sharper in urban areas compared to rural areas.
Whereas the highest urban average monthly claim was GHC 158,935 in May 2019, that for
rural health facilities was GHC 60,563 in June 2019.
Fig 2 shows data on average monthly deductions by the NHIA on incorrect claims submit-
ted from July 2018 to June 2019. The number of health facilities that provided information
from July 2018 to December 2018 were 10 while less than 10 facilities provided information
from January 2019 to May 2019. In terms of average deductions, November 2018 recorded the
Table 5. Average value of total monthly claims (July 2018 to June 2019).
Variable Obs Mean Min Max
July 2018 20 100,000 3,018 431,000
August 2018 20 103,000 1,856 428,000
September 2018 20 94,064 2,006 351,000
October 2018 20 104,000 2,801 383,000
November 2018 20 106,000 2,685 389,000
December 2018 20 93,212 1,835 317,000
January 2019 20 98,480 1,767 371,000
February 2019 20 94,106 1,686 330,000
March 2019 20 104,000 1,842 363,000
April 2019 20 110,000 1,871 388,000
May 2019 20 123,000 2,188 414,000
June 2019 18 123,000 2,503 404,000
https://doi.org/10.1371/journal.pone.0275493.t005
Fig 1. Comparison of average value of total monthly claims in Ghana Cedis. (Please, see figure file for Fig 1).
https://doi.org/10.1371/journal.pone.0275493.g001
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highest average of GHC16,187. The next highest average deduction of GHC8,608 was in Octo-
ber 2018. In terms of absolute numbers, the highest and lowest deduction of GHC 146,000 and
GHC 6 respectively, occurred in November 2018. Beside claims revenue and deductions, the
data collected indicate that 18 of the health facilities surveyed have at one point in time had
errors in claims submitted and 17 of them had their claims ever rejected by the NHIA. The
results (not shown) indicate that it took an average of 4.6 days to submit claims to the NHIA
office between July 2018 to December 2018, fluctuating between 1–20 days. However, this
changed to 2.7 days, with a minimum and maximum of 1 and 10 days respectively for January
2019 to June 2019.
Discussion
This study using multi method approach and a sample of CHAG health facilities, sought to
examine the readiness of the health facilities to implement the CLAIM-it software. Core find-
ings of the study cover five key domains (HR capacity, claims generation and processing, tech-
nological preparedness, claims output and potential benefits and implementation challenges of
CLAIM-it).
The quantitative results suggest that on the average there were sufficient staff at the Claims
Unit for the purpose of processing claims even though for some health facilities this was not
the case. It is important to reiterate that the size of health facilities interviewed (the highest of
which are district hospitals, which normally will not be up to 100 beds in size) are such that an
average of 4 staff for the Claims Unit should be enough for the work they do. The majority of
staff in the Claims Unit are computer literate, suggesting that it will be relatively easy to use
existing software or adapt to a new software [27]. These observations imply that the CLAIM-it
software is unlikely to have difficulties in the area of human resources when adopted by
CHAG health facilities.
On the contrary, technological preparedness, a key input into technology adoption readi-
ness [15,16,25] seems to be low. There will be the need for increased investments in comput-
ers and accessories, reliable local area networks (LAN) and access to the internet which per the
qualitative interviews seem to be crucial both for accessing the NHIA system and also sending
Fig 2. Average monthly deduction from submitted claims in Ghana Cedis. (Please, see figure file for Fig 2).
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data to the NHIA. These investments will be crucial for the success of CLAIM-it implementa-
tion, given that efficient functioning of the CLAIM-it software will depend on the availability
of adequate number of appropriate computers and accessories, LAN and a properly function-
ing internet.
The TOE framework suggests that managerial structures can facilitate the adoption of new
technology [17,18]. An example of such structures that can aid the implementation of the
CLAIM-it software are SOPs for claims processing. The results indicate that only a few of the
health facilities interviewed (5) have such SOPs in place. There is the need to build capacity in
this area. Given that 18 of the health facilities interviewed use some form of electronic systems
(10 electronic only and 8 a combination of paper and electronic), we argue that any attempt to
implement the CLAIM-it software successfully will depend on the extent to which implemen-
ters will leverage on the capabilities of users of the existing electronic claims processing sys-
tems. Additionally, the fact that existing claims management processes are error ridden and
that it takes an average of 4.6 days (up to 10 days) to submit claims, indicates that healthcare
facilities are currently putting up with problematic claims management systems. It is impor-
tant to emphasise that while such challenges may constitute a catalyst for managers who want
to be competitive in the market place to abandon existing problematic systems (Oliveira et al.,
2014) and adopt CLAIM-it as an alternative, it is equally essential to point out that that such
weak structures can limit the ability of managers to implement CLAIM-it successfully when
adopted.
Given that performance and convenience (measures of relative advantage within the TOE
framework) [21,22] and flexibility [18,23] have been advocated to positively influence tech-
nology adoption and implementation, it is important to address the issue of inflexibility that
has been identified with the CLAIM-it software. Thus, introducing some flexibility in enforc-
ing the NHIS protocols as well as the integration of the CLAIM-it software into third-party
applications used to collect the base claims data will be essential. Although users appreciate
that enforcing the NHIS protocols will reduce errors in claims processing, and therefore
reduce the likelihood of claims being rejected by the NHIA, they are equally concerned that
enforcing the NHIS protocols in the context of their business processes may inconvenience a
lot of their patients. Thus, finding a balance between accuracy and flexibility will be key in
adopting and implementing the CLAIM-it software. Additionally, while perceived superior
capabilities and positive view of the CLAIM-it software compared to existing substitutes will
increase the likelihood of adoption [21,22], its integration into third party applications will
reduce the amount of required data entry and make the use of CLAIM-it attractive compared
to existing alternatives.
For claims output, the results indicate that monthly claims revenue are on the increase
while the level of monthly deduction as well as the time it takes to submit claims to the NHIA
office is has reduced over the last year. Although it is not directly apparent from the current
data what may be causing the trend of positive claims outcomes in recent months, it is possible
that our observed increased use of electronic systems by some of the health facilities may be
partly responsible. Thus, it is possible that the full implementation of the CLAIM-it, viewed as
a more superior software compared to existing available softwares will lead to further improve-
ment in claims processing and consequently claims output.
We emphasize that although attempts were made to attain a representative sample of health
facilities (20 out of 115 CHAG facilities that have not yet implemented CLAIM-it), the possi-
bility of sampling bias cannot be ruled out entirely. Thus, results may not necessarily reflect
full generality of the situation of all CHAG health facilities. However, the qualitative informa-
tion gathered from the 20 facilities confirms our quantitative information, strengthening the
validity of our results. Additionally, the focus of the current study was on preparedness and so
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did not cover user experiences of the very few who have tested the CALIM-it software. A large
portion of the technology adoption literature has focused understanding factors that facilitate
or constraint adoption with issues of readiness not explicitly emphaised. Thus, the findings of
the current study adds to the adoption literature by additionally emphaising the importance of
readiness (required HR capacity, required structures and processes to aid adoption, technolog-
ical preparedness in terms of appropriate infrastructure and assesories, perception of benefitds
and challengesassociated with adoption) to technology adoption.
Conclusion
This study examines readiness of health facilities to implement the CLAIM-it software. The
study used the TOE framework, that emphasises technological, organisational and environ-
mental factors as key to the adoption and implementation of new technologies. The results
suggest that the adoption and implementation of the CLAIM-it software can be a challenge to
several of the health facilities studied, due mainly to low technological preparedness (inade-
quate computers and accessories, poor intranets and internet access). Additionally, the absence
of a robust post-implementation support system, challenges with the claims processing capa-
bilities of existing claims processing systems, inadequate SOPs for a seamless automation of
claims processing and the required integrations between existing claims processing software
and the CLAIM-it software may pose challenges. The above challenges notwithstanding, health
facilities studied tend to have a positive view of the CLAIM-it software, and perceive it to have
superior functionality and capability compared to existing systems used to process claims.
Such a positive view of the CLAIM-it software can facilitate and encourage of adoption of
CLAIM-it.
Thus, to ensure that implementation is successful, it will be important for stakeholders
(CHAG secretariate, NHIA, PharmAccess and most importantly the health facilities) to work
together. Key in this regard will be providing health facilities the right computers and accesso-
ries, especially backup power systems, LAN and appropriate internet access. Although our
findings indicate that human capital does not constitute a major challenge for implementing
CLAIM-it, it will remain important for health facilities to continue training their existing staff
not only for operating the software but also providing relevant technical support to users. Also
important will be to continue addressing operational deficiencies identified in the CLAIM-it
software (e.g. integration into other third party applications already in use and post-imple-
mentation support), making available requisite structures and procedures for automating the
claims processing function. Finally, there will be the need to recalibrate the CLAIM-it software
and make it more responsive to the needs of health facilities. The ability to balance accuracy
with flexibility will be crucial to adoption and therefore implementation. It is anticipated that
readiness for the implementation of CLAIM-it will be enhanced substantially if the issues
above are addressed.
Supporting information
S1 File. Survey questionnaire and qualitative interview guide. Data collection instrument
has information on profile of health facilities, HR capacity for claims management, claims gen-
eration and submission, claims output and qualitative interview guide.
(DOCX)
S2 File. Data. Anonymized data as per the content of attached quantitative instrument.
(XLSX)
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S3 File. Data. Anonymized data as per the content of attached interview guide.
(XLSX)
Acknowledgments
The authors acknowledge the contributions of health personnel in all the facilities where data
for the paper was collected. We equally express our gratitudes to Doris Oti-Boakye and Rich-
mond Owusu who assisted in data collection.
Author Contributions
Conceptualization: Gordon Abekah-Nkrumah, Maxwell Antwi, Alex Yao Attachey, Wendy
Janssens, Tobias F. Rinke de Wit.
Data curation: Gordon Abekah-Nkrumah, Alex Yao Attachey, Wendy Janssens.
Formal analysis: Gordon Abekah-Nkrumah.
Methodology: Gordon Abekah-Nkrumah, Wendy Janssens, Tobias F. Rinke de Wit.
Project administration: Alex Yao Attachey.
Supervision: Maxwell Antwi, Alex Yao Attachey, Tobias F. Rinke de Wit.
Writing – original draft: Gordon Abekah-Nkrumah.
Writing – review & editing: Maxwell Antwi, Alex Yao Attachey, Wendy Janssens, Tobias F.
Rinke de Wit.
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