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https://doi.org/10.1177/22799036231170843
Journal of Public Health Research
2023, Vol. 12(2), 1 –6
© The Author(s) 2023
DOI: 10.1177/22799036231170843
journals.sagepub.com/home/phj
Journal o
f
Public Health Research
Original Article
Introduction
Non-insulin-dependent-diabetes-mellitus (NIDDM) is a
chronic disease with high treatment costs because it will
last a lifetime for a person diagnosed with type 2 diabetes.
Patients with NIDDM require continuing medical care
with direct and indirect costs. Diabetes also has the poten-
tial to pose a risk of early complications if not treated prop-
erly. Diabetes and its associated complications impose a
significant economic burden on the health care system and
society, given the large expenditures spent on managing
these complications. Preventative measures are needed to
improve patients’ glycemic control, thereby preventing
diabetes complications, which could potentially reduce the
1170843PHJXXX10.1177/22799036231170843Journal of Public Health ResearchKarimah et al.
research-article20232023
1Doctoral Program of Medicine and Health, Faculty of Medicine, Public
Health and Nursing, Universitas Gadjah Mada, Yogyakarta, Indonesia
2Department of Health Science, Politeknik Negeri Jember, East Java,
Indonesia
3Department of Family and Community Medicine, Faculty of Medicine,
Public Health and Nursing, Universitas Gadjah Mada, Yogyakarta,
Indonesia
4Department of Health Policy and Management, Faculty of Medicine,
Public Health and Nursing, Universitas Gadjah Mada, Yogyakarta,
Indonesia
Corresponding author:
Lutfan Lazuardi, Department of Health Policy and Management, Faculty
of medicine, Public Health and Nursing, Universitas Gadjah Mada,
Yogyakarta 55281, Indonesia.
Email: lutfan.lazuardi@ugm.ac.id
Development of the information quality
scale for health information supply chain
type 2 diabetes mellitus management using
exploratory factor analysis
Rinda Nurul Karimah1,2 , Hari Kusnanto3
and Lutfan Lazuardi4
Abstract
Background: Research on the quality scale of the healthcare supply chain is still limited. This study aimed to assess the
information quality of the supply chain model with a focus on construct validity. Studies related to information quality
measurement generally focus on measuring the dimensions of the completeness of medical records and consumer
perspectives. We intended to assess the scale based on doctors needed as care coordinators on type 2 diabetes mellitus
or the Non-Insulin-Dependent-Diabetes-Mellitus (NIDDM) program in primary healthcare.
Methods: Sixty-four primary healthcare doctors with an age range of 24–51 years were involved in this research. The
scale obtained was formed from the assessment of the point of view of a panel of experts through the content validity
index (CVI). The exploratory factor analysis (EFA) method was used to explore the scale of information quality in the
information supply chain model for the NIDDM chronic disease management program.
Result: The data analysis results indicated three main factors that affected the quality of the information supply chain
model of NIDDM, namely accessibility, safety, and efficiency of information related to NIDDM. The results of the
validity and reliability of the data showed that the scale used in this research was valid and reliable with a Cronbach alpha
coefficient of 0.861.
Conclusion: The scale developed in this research could be used to explore the quality of the information supply chain
of NIDDM management in primary healthcare. Each item on the scale could explain the variables according to their
respective groups.
Keywords
Diabetes mellitus, primary healthcare, health information, supply chain, information quality
Date received: 5 August 2022; accepted: 1 April 2023
2 Journal of Public Health Research
health and economic burden on the public health care sys-
tem.1–3 Based on International Diabetes Federation (IDF)
data for 2021, Indonesia is globally ranked fifth with
19.5 million adults aged 20–79 years living with diabetes.
Referring to the IDF data, the number of people with
Diabetes Mellitus in Indonesia is projected to increase to
28.6 million in 2045.4
The increasing prevalence of NIDDM in various coun-
tries in the world should be anticipated with preventive
and promotive actions by policy makers.5 NIDDM is a
non-communicable disease that has become a priority for
primary health care policies. Primary health services are
considered as basic health services in the community with
preventive, promotive and limited curative efforts.6–8
Doctors in primary health care facilities have an important
role as care coordinators.6 A clinical information system is
highly required to support the performance of doctors in
the NIDDM chronic disease management program.9 In the
management of chronic diseases such as NIDDM, patients
will require health services related to diabetes manage-
ment throughout their life, so that a good supply of infor-
mation is highly needed. The information supporting
clinical decision making by doctors must be presented in a
sequential and continuous manner.5,10,11 The NIDDM man-
agement program strategy of primary healthcare in
Indonesia is supported by the national health insurance,
specifically the Social Security Administrator for Health
(known as BPJS Kesehatan in Indonesia) through chronic
disease management programs to anticipate the economic
burden and risk of complications that can arise from
patients with NIDDM.12,13
There has been policy research on implementing NIDDM
chronic disease management program strategies in primary
healthcare and improving service quality with the support of
information systems for good data presentation. The study
on the application of digitization in the existing health ser-
vice supply chain has mostly focused on the supply of medi-
cal devices, blood, and medicine.14–17 Study on the supply of
medical data has not been widely conducted, and there has
been no research that has developed a standard scale for
measuring the success of strategies to improve the quality of
information through the data supply chain in supporting the
performance of doctors as care coordinators for the NIDDM
management program. This study was conducted to develop
a scale for measuring the quality of information supply
chain of NIDDM management programs in government-
owned primary services.
Methods
This research utilized an exploratory mixed-methods
(qualitative-quantitative) study design to develop an infor-
mation quality measurement tool for the supply chain
management of health information on the management of
the chronic disease NIDDM. In the first stage, a question-
naire with a qualitative approach had been produced,
namely through the stages of construct definition, domain
content, and assessment items. In the next stage, an evalu-
ation of the reliability and validity of the scale was con-
ducted with a quantitative approach. Scale development
requires additional time and research, since many proce-
dures have to be used to refine the scale with various prob-
lems related to finally acquiring the final form of the
scale.18,19 This manuscript is focused in detail on the dis-
cussion of the reliability evaluation stage by testing the
initial factor structure that had been formed with its items
through exploratory factor analysis (EFA). The EFA
method in this research was used to reduce the dimensions
of the observed factor variables, and were represented in
an easy-to-understand form. The processed data had been
analyzed by an expert panel consisting of eight experts:
Three lay experts and five content experts covering three
main factors that can explain the quality of information in
the supply chain management of health information on the
management of the chronic disease NIDDM. The ideal
number of expert panels is a minimum of 5 people and a
maximum of 10 people to obtain sufficient control of the
deal opportunities.20–22 The results from the expert panel’s
viewpoint judgment were assessed through the content
validity index (CVI), from three latent factors (construct),
where each factor has 5 items, which was reduced to 3
items each. Based on the CVI score criteria, the item
≤0.80 should be eliminated.22
The results of the CVI, including factors and items,
were then tested for construct validity using the EFA
method19,23 which was conducted by recruiting 64 subjects
in this research who work as doctors in the management of
the NIDDM chronic disease from 50 government-owned
primary healthcare facilities in a regency area in Indonesia
with an age range of 24–51 years. The number of subjects
in this research was in accordance with the standard num-
ber recommended by several literatures, where the mini-
mum sample size in a validation research should be 5–10
times the number of instrument variables or the ratio of
participants per variable or item (n:p) is 5:1.24,25 This
research consisted of nine items, and the minimum number
according to this statement must amount to 45 subjects.
This research involved 64 subjects, so it had met the stan-
dard number of subjects in the validation research. EFA
statistical analysis was conducted with SPSS 22 software
(IBM Corp., Armonk NY). This research had obtained an
ethical clearance from the Medical and health research eth-
ics Committee (MHREC) of Universitas Gadjah Mada
(number: KE/FK/0042/EC/202).
Results
All 64 subjects who participated in this research had an
average age of 36.5 years, and were doctors in charge of
managing NIDDM chronic disease in government-owned
primary healthcare facilities. Table 1 shows the details of
the basic characteristics of the participants.
Karimah et al. 3
The Kaiser-Meyer-Olkin Measure of Sampling
Adequacy (KMO-MSA) test and Bartlett’s Test are tests to
assess the feasibility of the question item variables for fac-
tor analysis. The results of the feasibility test of the ques-
tion item variables in this research are presented in Table 2.
The KMO-MSA results showed a value of 0.779 > 0.5,
which means that the sample in this test was adequate for
factor analysis. The significance of the value of Bartlett’s
test must be ≤0.05 for the factor analysis to be acceptable.
The results above showed a value of <0.000, which means
that factor analysis could be conducted in this research.
Table 3 shows how much the formed factors can explain
the variation of the data, and it can be concluded that the
three factors could explain 68.69% of the total variance.
The results of the extraction value should be >0.5, so
that the question items could explain the factors. Based on
the output in Table 4, it can be concluded that the nine
items were able to explain the factors. The best correlation
was found in the following factors:
1. The first factor contains question items number 1,
2, and 3;
2. The second factor contains question items number
4, 5, and 6; and
3. The third factor contains question items number 7,
8, and 9.
These were grouped based on the correlation value of the
largest variable contained to a certain factor. These three
factors indicated a value above 0.5, which means that they
were feasible to summarize the nine question items. Based
on the screen plot graph in Figure 1, the nine question
items were observed to form three factors or dimensions
(eigenvalue >1).
Reliability
Internal consistency was applied to assess the reliability of
the questionnaire. Table 5 shows the cronbach’s alpha
coefficient of 0.861 above the threshold >0.6 is an accept-
able level of reliability, so it can be concluded that the
questionnaire formed was reliable.
Discussion
Exploratory factor analysis (EFA) was used to assess the
construct validity of the scale. The scale tested for con-
struct validity was a scale that had been declared valid
based on the results of the CVI test. The scale in the form
of a questionnaire consisted of three main factors, namely
accessibility, safety, and efficiency, and was composed of
nine question items. This scale was intended to measure
Table 1. Characteristics of participants.
Variable No (N = 64) Percent
Gender
Female 40 62.5
Male 24 37.5
Status
Civil Servants (PNS) 53 82.8
Non-Civil Servants (Non-PNS) 11 17.3
Working period as
primary care doctor
<1 year 9 14.1
1–3 years 15 23.4
3–5 years 4 6.3
>5 years 14 21.9
>10 years 22 34.4
Table 2. Results of the KMO and Bartlett’s test.
Kaiser-Meyer-Olkin measure of sampling adequacy 0.779
Bartlett’s test of Sphericity Approx. chi-square 309.318
Df 36
Sig. 0.000
Table 3. Total variance explained.
Factor Initial Eigenvalues Extraction sums of squared loadings Rotation sums of squared loadings
Total % of Variance Cumulative % Total % of Variance Cumulative % Total % of Variance Cumulative %
1 4.307 47.855 47.855 4.007 44.518 44.518 2.158 23.981 23.981
2 1.481 16.461 64.316 1.171 13.015 57.533 2.014 22.382 46.363
3 1.329 14.771 79.087 1.004 11.152 68.685 2.009 22.322 68.685
4 0.493 5.474 84.561
5 0.412 4.578 89.139
6 0.313 3.478 92.617
7 0.293 3.260 95.877
8 0.208 2.310 98.187
9 0.163 1.813 100.000
4 Journal of Public Health Research
the quality of information from the health information sup-
ply chain role model on the management of the NIDDM
chronic disease in primary healthcare in supporting the
performance of doctors. Details of the measuring scale are
presented in Table 6.
Factor 1 in the form of an accessibility construct con-
sisted of three question items that were developed accord-
ing to the needs of doctors in supporting performance,
namely ease of access, continuity of access, and fast
access. According to Wixom and Todd in 2005, the per-
ceived use value of information is strongly influenced by
information satisfaction. Accessibility is one of the most
Table 4. Rotated factor matrix.
Item Rotated factor matrixa
123
1 0.789
2 0.790
3 0.785
4 0.801
5 0.721
6 0.805
7 0.727
8 0.760
9 0.404 0.863
Figure 1. The scree plot graph shows the formation of the
three constructs/factors in the instrument.
Table 5. Cronbach’s alpha.
Cronbach’s alpha No of items
0.861 9
Table 6. Scale for measuring the quality of information from the Information Supply Chain of NIDDM.
No Construct Item themes Item definition
1. Accessibility Ease of access 1. Doctors are able to easily obtain the information needed for the care of NIDDM
patients with current medical record documents.
Continuity of access 2. The current medical documentation process supports doctors to continuously
write data on the progress of NIDDM patients.
Fast access 3. Doctors can quickly understand the information presented in medical record
documents, which are further needed to provide more reliable information during
patient care.
2. Safety Confidentiality of
medical data and
legality
1. Doctors feel protected by using the medical record documents presented in
the management of NIDDM patients, because they have met the legality and
confidentiality aspects.
Reliability 2. Doctors can rely on continuous information on existing medical record documents
to prevent medical errors or medication errors for joint management of NIDDM
patients.
Early warning 3. Existing medical record documents have functioned as an early warning for doctors
in the management of NIDDM patients, regarding the opportunities for hypo/
hyperglycemia, allergies, risk of falls, infectious diseases, the impact of a pandemic,
etc.
7 Efficiency Costs of drugs 1. The current medical record document has met the quality and cost control aspects,
especially the integrated program related to the number and types of drugs in the
management of NIDDM patients at primary healthcare.
Costs of
complications and
emergencies
2. Costs due to complications, emergency events, and referrals to NIDDM patients
can be controlled/reduced with the support of current medical documentation.
Costs of care 3. The current medical documentation process supports efforts to save time and
doctors as the coordinator of care related to the management of NIDDM patients.
NIDDM: Non-Insulin Dependent Diabetes Mellitus.
Karimah et al. 5
important items of a quality system. Accessibility is
described as the ease of accessing or extracting informa-
tion from the system.26,27 As stated by Eppler in 2006,
accessibility is defined as a continuous and unobstructed
way to obtain information.26,28 Referring to the combined
definition of Eppler in 2006 and Wixom and Todd in 2005,
accessibility can be perceived as information that must be
accessed continuously without many obstacles, which
means that it can be related to fast access criteria. Supply
chain management provides a significant impact on better
access to health services.29,30 This is certainly very useful
in supporting the performance of doctors in NIDDM
chronic disease services, where patients with NIDDM
need access to health services for the management of their
disease throughout their life.
Factor 2 is a safety construct consisting of three theme
items, namely confidentiality of medical data and legality,
reliability and early warning. The safety factor was chosen
in this research, because it was found to be correlated with
the quality of information from information systems on
health services, specifically on the management of chronic
diseases that require continuous data.31,32 Management of
chronic diseases with high costs and prone to emergency
complications, such as NIDDM, requires continuous med-
ical data support to assist doctors in performing quality
services. Previous research had suggested that supply
chain management provided significant benefits for
improving patient safety.17,30,33 Confidentiality of medical
data and legality play an important role in ensuring the
safety of doctors in carrying out their performance as coor-
dinators of health services.34,35 Researchers see this oppor-
tunity, especially in the chronic disease prevention program
at the primary healthcare. The program runs in collabora-
tion between health workers from the main health center to
a network in the form of Integrated Health Post for Non-
Communicable Diseases (POSBINDU-PTM) with a fam-
ily approach to increase the reach of community targets.
Documentation is a method of communication with mem-
bers of the care team, using medical records as an effective
method to support communication, collaboration, and
coordination of care.35,36
Factor 3 is an efficiency construct consisting of three
theme items, namely costs of drug, care, and complications
and emergencies. Research conducted by Joep Top in 2015
found a correlation between cost and increased informa-
tion.26 In this research, authors intended to identify the effi-
ciency construct based on health services, especially in the
management of NIDDM chronic disease, namely drug
costs, and complications and emergencies costs, as well as
costs of care, which include the time and energy that must
be spent by doctors in providing health services. Supply
chain management had an important impact on reducing
costs and improving performance in healthcare organiza-
tions.15,17,30 The authors found that the chronic disease man-
agement program at the primary healthcare does not only
involve doctors as care coordinators, but also other health
workers both at the primary healthcare and their network
service units. The supply chain management is realizing its
goals and collaborating among supply chain suppliers to
achieve system efficiency. Supply chain coordination and
cooperation are operating with connections throughout the
chain with materials and information flowing smoothly
throughout supply chain operations in achieving
efficiency.37,38
The results of the study indicate that the compiled scale
has acceptable validity and reliability. Each item on the
scale can be explained according to its respective group of
variables. The results of the research showed that the com-
piled scale had acceptable validity and reliability. Each
item on the scale could explain the variables according to
their respective groups.
This study has practical implications for providing
guidelines for stakeholders to evaluate the quality of infor-
mation from the supply chain model in the NIDDM chronic
disease. The information supply chain model can help to
improve the performance of doctors as a care coordinator
in primary healthcare. This study has several limitations
since it is only focused on primary healthcare, and the
results may not be suitable for implementation in larger
hospitals with complex business processes.
Acknowledgements
The authors are grateful to Lembaga Pengelola Dana Pendidikan
(LPDP) Indonesia for the provision of assistance to conduct this
study.
Declaration of conflicting interests
The author(s) declared no potential conflicts of interest with
respect to the research, authorship, and/or publication of this
article.
Funding
The author(s) disclosed receipt of the following financial support
for the research, authorship, and/or publication of this article:
This work was supported by Lembaga Pengelola Dana Pendidikan
(LPDP) Indonesia.
ORCID iD
Rinda Nurul Karimah https://orcid.org/0000-0003-
0644-9071
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