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International Journal of Smart Computing and Information Technology
2020, Vol. 1, No. 1, pp. 30–34
Copyright © 2021 BOHR Publishers
www.bohrpub.com
Enabling Semantic Interoperability of Regional Trends of Disease
Surveillance Data for Namibia Through a Health-Standards-Based
Approach
Nikodemus Angula1, Nomusa Dlodlo2 and Progress Qhaphi Mtshali1
1Durban University of Technology, 41/43 M. L. Sultan Road, Durban, 4001, South Africa
2Rhodes University, 94 Drodsty Road, Grahamastown, 6139, South Africa
E-mail: chcangula@gmail.com; n.dlodlo@ru.ac.za; ProgressM@dut.ac.za
Abstract. The Ministry of Health and Social Services in Namibia under the division of epidemiology uses a manual
paper-based approach to capture disease surveillance data through 5 levels of reporting which include the commu-
nity level, the health facility level, the district level, and the national level. As a result, this method of communicating
and exchanging disease surveillance information is cost and time consuming, which delay disease surveillance infor-
mation from reaching the head office on time. The current method that is being used to exchange and communicate
disease surveillance data is a manual process which very time consuming due to the fact that surveillance officers
have to organise and store the files and hunt down the information when it is needed and this can take time. There-
fore, the study developed a prototype that aggregates disease surveillance data from the 14 regions in Namibia and
can thus enable the disease service office to capture disease surveillance data through the use of mobile devices.
The functionality of the prototype would allow a disease surveillance office in one regional office to access disease
surveillance data of other regional office in real time. The method used to communicate disease surveillance data is
through the excel spreadsheet (IDSR) which is called the integrated disease surveillance and response. Furthermore,
the excel file will be sent to the relevant authority through email. However, we still do not have a web based system
to report cases of diseases, instead this is a process starting from the intermediate hospital disease surveillance data
which is captured then sent to the regional office and from the regional office the information is sent to the district
office and then sent to the national office and from the national office the information is further sent to the WHO and
other development partners as well as to the top management or to the highest authority. So it does not end at the
national level but goes to management such as the Permanent Secretary, and the data is used to inform the develop-
ment partners and the national surveillance office prepares official letters to the management as a form of reporting
disease surveillance data. The symphonic surveillance office helps to detect a particular disease. The doctors send
an investigation case form to the laboratory for testing the disease that has been identified.
Keywords: Interoperability, HL7, Semantic Interoperability.
1 Introduction
The Ministry of Health and Social Services in Namibia
under the division of epidemiology currently faces chal-
lenges of using a manual paper-based process of capturing
disease surveillance data from the regional level, national
level and eventually to the World Health Organization
(Angula, Dlodlo, & Mtshali, 2019). This is the department
in the Ministry of Health and Social Services that deals
with disease surveillance data which includes different lev-
els. Communicable diseases are the most common cause of
illness, disability and death in Namibia. While these dis-
eases present a large threat to the well-being of the Namib-
ian communities, there are well-known interventions that
are available for controlling and preventing them. Namibia
has a relatively efficient surveillance and emergency pre-
paredness and response (EPR) system in place (MoHSS,
2014). The Ministry of Health and Social Services has three
levels of exchanging disease surveillance information such
30
Enabling Semantic Interoperability of Regional Trends of Disease Surveillance Data 31
as the regional level which does not have a mandate to
declare the outbreak of a disease in the region through
monthly meetings and the CDC manager, facilities meet-
ings and sharing information with other colleagues, col-
lecting malaria statistics, and collecting data through other
staff members that attend regional meetings. However, in
these instances they don’t get real data as data is collected
through a manual process through an investigation case
form for malaria. The second one is a national surveil-
lance office which deals with 5 levels of reporting, namely
at community level, health facility level, district level,
regional level, and national level which includes different
offices such as one administrative office (IDSR) (integrated
disease surveillance and response) which is responsible to
report disease surveillance data as received every Monday
and then submitting the data to the World Health Organ-
isation and other development partners every Tuesday of
the week (MoHSS, 2014). All the 35 district hospitals have
a surveillance office that is responsible for facilitating the
process of ensuring that disease surveillance data passes
all the 5 levels of reporting disease surveillance data as
well all the 14 regions which have a surveillance office
that is responsible for reporting disease surveillance data
to the right channel and the management health infor-
mation office. If the community health worker detects an
incident of an epidemic, he/she completes an investiga-
tion case form and sends it to the health facility for further
identification. Diseases are classified into a different cate-
gory called case definition depending on the symptoms of
that particular disease and then doctors determine if it is
a known disease or an unknown disease. The community
health worker in the field can gather disease surveillance
data and send it to the intermediate hospitals such as
Rundu hospital, Oshakati hospital, Katutura hospital and
Windhoek Central hospital and at each intermediate hos-
pital there is one surveillance officer who is responsible
to complete an investigation case form and then sends
it to the next level. In each health facility there is a dis-
ease surveillance office that is responsible for receiving
and sending disease surveillance data to the district office
through completing an investigation case form. At the
district level there is a disease surveillance office that is
responsible for receiving disease surveillance data from the
health facility and they send such information to the head
office through completing an investigation case form. The
national level receives disease surveillance data through
the district level and the national level sends this informa-
tion to the laboratory for testing purposes to identify what
type of disease that is affecting a particular region and then
the disease surveillance office has to go and physically col-
lect the investigation case form from the laboratory and
eventually sends the results to top management to declare
that particular epidemic officially on media such as televi-
sion and newspapers. So the process does not end only at
national level but it further proceeds to the administrative
office that is responsible for managing the integrated dis-
ease surveillance and response system which is in excel
format, and they report all the disease surveillance data
weekly, monthly, quarterly, yearly. Moreover every Mon-
day the disease surveillance data is received from all the
four levels of reporting disease surveillance data and the
submission of disease surveillance data is submitted to
the World Health Organisation and development partners
every Tuesday on a weekly basis. The national surveillance
office is responsible for preparing official letters to report
disease surveillance data.
1.1 Problem Statement
In the Namibian health sector, different public health insti-
tutions face challenges of lack of interoperability of health
information systems (MoHSS, 2014). The Namibian health
sector has many heterogeneous health systems which are
not integrated in order to share and communicate with
each other for the purpose of exchanging disease surveil-
lance data from the 14 regional health directorates under
the Ministry of Health and Social Services. This has been a
major concern for the MoHSS because if one health profes-
sional is in one health institution, then they cannot access
information from the other health institution. The current
method used by health institutions is a manual process
that causes delays and this is time consuming when a
health professional is capturing disease surveillance data
from the regional level to the national level (Angula &
Dlodlo, 2019).
The current system being used by the Ministry of Health
and Social Services to communicate and exchange health
related information is through emails, telephone, What-
sApp groups or taking a picture of something and sending
it to whoever needs it and also through monthly meetings.
The other method that is used to share disease surveil-
lance data is through filling what is called an investigation
case form. When sharing disease surveillance data, there
is a form to be completed manually which is completed
in one facility and then sent to the district office and from
the district office, finally the form will be sent to the head
office under the division of epidemiology where disease
surveillance is done by the surveillance focal person. At the
present moment, the Ministry of Health and Social Ser-
vices does not have a health integrated system for disease
surveillance data. With the DHIS2, you cannot view data
that is entered from the regions and the regional people
will view data that is entered by another region. In other
words, there is no platform to exchange and communi-
cate disease surveillance data in real time. The department
of epidemiology in the Ministry of Health and Social Ser-
vices usually receives disease surveillance data from the
district office and regional office before the 5th of every
month and all activities are done over a month and all
32 Nikodemus Angula et al.
disease surveillance data is reported weekly and monthly,
and at the same time the reports that are presented monthly
and weekly are different and not the same reports. It takes
time to capture data from the health facilities manually,
and there is no access to other silo systems, and as such
all systems do not communicate with each other. There are
duplicate systems.
2 Literature Review
2.1 Interoperability
Interoperability is a defined as way of exchanging and use
of information in heterogeneous network made up of many
local area networks (Diallo, Herencia-Zapana, Padilla, &
Tolk, 2011).
In other words, interoperability deals with information
exchange whereby interoperable systems are characterised
by their ability to exchange information. The definition
stresses the fact that information exchange must be direct
which conforms to the view depicted in figure one below
(Diallo et al., 2011). The IEEE defines interoperability as
inherent to a system (its ability to exchange information)
which implies that systems are interoperable. Interoper-
ability is defined as “the ability of two or more systems
or components to exchange information and to use the
information that has been exchanged” (Pagano, Candela,
& Castelli, 2013, pp. 122–134). Asuncion and van Sin-
deren (2010) discuss “pragmatic interoperability” as the
interoperability dealing with mutual understanding in the
use of data between collaborating systems. Recently, com-
prehensive frameworks have been proposed to capture
the many facets of interoperability (Candela, Castelli, &
Thanos, 2010; European Commission, 2004).
2.2 HL7
HL7 International is one of several American National
Standards Institutes (ANSI) accredited Standards Devel-
oping Organizations (SDOs) operating in the healthcare
arena (Working, Meeting, & Beebe, 2018). Most of these
SDOs produce standards (sometimes called specifications
or protocols) for a particular healthcare domain such as a
pharmacy, medical devices, imaging or insurance (claims
processing) transactions. According to Working, Meeting
and Beebe (2018), HL7 international is a not-for-profit stan-
dards Development Organisations (SDO). A “message” is
considered the minimal unit of data transferred between
systems using HL7. For example, an admission transaction
would be sent as an HL7 “ADT” message. Messages are
comprised of two or more “segments” that act as building
blocks for each message (Rights, 2016).
2.3 Semantic Interoperability
Semantic interoperability pertains to the possibility that
information distributed over the net can be processed by
programmes that understand the meaning of the bits and
bytes in which the information items are encoded without
the need for constant human interpretation (and trans-
lation) (Heiler, 1995). Semantic interoperability plays a
pivotal role in healthcare organisations through enabling
ubiquitous forms of knowledge representations (Ashrafi,
Kuilboer, & Stull, 2018). By integrating heterogeneous
information, it strives to answer complex queries and pur-
sue information sharing in healthcare. In healthcare, data
exchange schema and standards allow data sharing across
clinicians, labs, hospitals, pharmacies, and patients regard-
less of the application or application vendor. However,
the absence of interoperability within and across organi-
sational boundaries impedes the ability to exchange infor-
mation in a complex network of computerised systems
developed by different manufacturers.
3 Methodology
Two hospitals in the Khomas region of Namibia, the
MoHSS, the CDC and members of the Khomas commu-
nity participated in this study. The first phase of the study
was qualitative, applying an interpretive approach and a
qualitative multi-case study research design. Face-to-face
interviews, focus group interviews, questionnaires and
document sampling were used as data collection methods
to identify the requirements for a semantic interoperability
prototype that enables the integration of disease surveil-
lance information in real time across the entire health
sector in Namibia. Through laboratory experimentation,
the second phase of the study led to the development of
a prototype. Design science research was used to guide the
development of the prototype.
4 Architecture of the System
Different health facility can access disease surveillance data
from heterogeneous health information and as a result,
hospital statistics from different health facilities can pro-
duce hospital statistics, malaria statistics, TB statistics and
patients’ records statistics as long as the data is in JSON
format.
Figure 1 below represents the architecture of the pro-
totype and its functionality which means surveillance
data from different data sources can be aggregated and
produces real time report to different health facilities in
Namibia which aid in fast and informed decision making
in the health sector in Namibia.
Enabling Semantic Interoperability of Regional Trends of Disease Surveillance Data 33
Figure 1. Aggregated disease surveillance information.
5 Technology Demonstrator
This is a login interface that can allow users who are regis-
tered into the system to login.
This shows the disease surveillance data captured in dif-
ferent towns in Namibia, which indicates title and reports
of a specific disease, possible disease name, severity and
status, whether a disease is normal or unknown, and the
name of town where disease occurred.
Figure 3 below represents reports from different town
in Namibia with possible disease cases such as Cholera in
Figure 2. Login interface.
(Own source: Prototype developed, 2018)
Figure 3. Community surveillance report.
Henties bay and Afghanistan in Windhoek. This means real
time surveillance data can be accessed at the same time
from different town in Namibia which enables health pro-
fessionals to make fast and informed decisions timely.
6 The Profile
Cross-Enterprise Document Sharing (XDS) is an integrated
health profile that enables several healthcare service deliv-
ery organisations that belong to an XDS Affinity Domain to
cooperate in the care of a patient by sharing clinical records
from heterogeneous systems.
7 Discussion
In the Namibian healthcare sector, the process of cap-
turing disease surveillance is a manual process which is
time consuming. Disease surveillance is captured manu-
ally following the 5 levels of reporting which includes the
community level, health facility level, the district level, and
the national level. At each level, the process of captur-
ing disease surveillance data is captured manually which
causes delays when a health professional wants to access
such information in real time using data from all the levels.
Therefore, the study developed a prototype that aggregates
disease surveillance data from the 14 regions in Namibia
which can enable disease service offices to capture disease
surveillance data through the use of mobile devices.
The system users
The system will be used by health professionals in min-
istry of health and social services in Namibia such as
nurses, doctors and COVID-19 management committees.
The Cross-Enterprise Document Sharing diagram below
represents a mechanism how surveillance data can be
Figure 4. Cross-Enterprise Document Sharing-b (XDS.b)
diagram.
(Source: IHE IT Infrastructure Technical Framework, 2018)
34 Nikodemus Angula et al.
exchanged and communicated among different health
stakeholders in the Namibian health domain.
This is a type of integrated profile that does not define
specific policies and business rules; however, which has
been designed to accommodate a wide range of such poli-
cies to facilitate the deployment of standards-based infras-
tructures for sharing patient clinical documents. In addi-
tion, this integrated profile managed through federated
document repositories and a document registry to create
a longitudinal record of information about a patient within
a given XDS Affinity Domain.
8 Conclusion
The Ministry of Health and Social Services uses a manual
process of capturing disease surveillance data which under
goes five levels of reporting and which includes five levels
of reporting which includes the community level, health
facility level, district level, and national level. The Ministry
of Health and Social Services does not have a platform that
interlinks the hospitals’ silo systems with ministry systems.
There is no system that tracks contagious disease and as it
stands, the ministry or hospitals rely on the person in the
hospital or the ministry. Therefore, this study developed
a prototype that aggregates disease surveillance data from
the 14 regions in Namibia that can enable the disease ser-
vice office to capture disease surveillance data through the
use of mobile devices.
References
Angula, N., Dlodlo, N., & Mtshali, P. Q. (2019). Enabling semantic
interoperability of crowdsourced disease surveillance data for Namibia
through a health-standards-based approach. IST Africa 2019. Kenya,
Nairobi, 34–35. Retrieved from https://www.semanticscholar.org/
paper/Enabling-Semantic-Interoperability-of-Crowdsourced-Angu
la-Dlodlo/1f5096bc2787e27357fe0b65592407d1a6035a40.
Ashrafi, N., Kuilboer, J. P., & Stull, T. (2018). Semantic interoperability
in healthcare: Challenges and roadblocks. CEUR Workshop Proceed-
ings, 2107, 119–122. Retrieved from http://ceur-ws.org/Vol-2107/
Paper1.
Asuncion, C., & van Sinderen, M. (2010). Pragmatic interoperability: A
systematic review of published definitions. Enterprise Architecture, Inte-
gration and Interoperability, IFIP Advances in Information and
Communication Technology, Springer, pp. 164–175. Retrieved from
https://link.springer.com/chapter/10.1007/978-3-642-15509-3_15.
Candela, L., Castelli, D., & Thanos, C. (2010) Making digital library con-
tent interoperable. Digital Libraries – 6th Italian Research Confer-
ence, IRCDL 2010, Padua, Italy. Revised Selected Papers, pp. 13–25.
Retrieved from https://www.researchgate.net/publication/22133
3809_Making_Digital_Library_Content_Interoperable.
Diallo, S. Y., Herencia-Zapana, H., Padilla, J. J., & Tolk, A. (2011). Under-
standing interoperability. Emerging M and S Applications in Industry
and Academia Symposium 2011, EAIA 2011 – 2011 Spring Sim-
ulation Multiconference, (May 2014), 84–91. Retrieved from https:
//www.odu.edu/vmasc/research/simulated-empathy.
European Commission (2004). European Interoperability Framework for Pan-
European eGovernment Services. Luxembourg: European Commis-
sion. Retrived from https://ec.europa.eu/idabc/servlets/Docd552.
Heiler, S. (1995). Semantic interoperability. ACM Computing Surveys
(CSUR), 27(2), 271–273. Retrieved from https://doi.org/10.1145/
210376.210392.
Kuechler, B., & Petter, S. (2012). D Esign S Cience R Esearch in, 1–66.
Retrieved from https://doi.org/1756-0500-5-79 [pii]r10.1186/
1756-0500-5-79.
MoHSS. (2014). National technical guideline for integrated disease surveillance
and response division of epidemiology subdivision: Disease surveil-
lance and emergency preparedness and response. Retrieved from
https://www.researchgate.net/publication/266778090_Technical_
Guidelines_for_Integrated_Disease_Surveillance_and_Response_
in_the_African_Namibia.
Pagano, P., Candela, L., & Castelli, D. (2013). Data interoperability.
Retrieved from https://doi.org/10.2481/dsj.GRDI-004.
Rights, P. (2016). HL7 Interface Specifications 2016, 44(0), 0–52. Retrieved
from https://www.interfaceware.com/iguana.html?utm_medium.
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Enabling Semantic Interoperability of Regional Trends of Disease Surveillance Data for Namibia Through a Health-Standards-Based Approach

  • 1. International Journal of Smart Computing and Information Technology 2020, Vol. 1, No. 1, pp. 30–34 Copyright © 2021 BOHR Publishers www.bohrpub.com Enabling Semantic Interoperability of Regional Trends of Disease Surveillance Data for Namibia Through a Health-Standards-Based Approach Nikodemus Angula1, Nomusa Dlodlo2 and Progress Qhaphi Mtshali1 1Durban University of Technology, 41/43 M. L. Sultan Road, Durban, 4001, South Africa 2Rhodes University, 94 Drodsty Road, Grahamastown, 6139, South Africa E-mail: chcangula@gmail.com; n.dlodlo@ru.ac.za; ProgressM@dut.ac.za Abstract. The Ministry of Health and Social Services in Namibia under the division of epidemiology uses a manual paper-based approach to capture disease surveillance data through 5 levels of reporting which include the commu- nity level, the health facility level, the district level, and the national level. As a result, this method of communicating and exchanging disease surveillance information is cost and time consuming, which delay disease surveillance infor- mation from reaching the head office on time. The current method that is being used to exchange and communicate disease surveillance data is a manual process which very time consuming due to the fact that surveillance officers have to organise and store the files and hunt down the information when it is needed and this can take time. There- fore, the study developed a prototype that aggregates disease surveillance data from the 14 regions in Namibia and can thus enable the disease service office to capture disease surveillance data through the use of mobile devices. The functionality of the prototype would allow a disease surveillance office in one regional office to access disease surveillance data of other regional office in real time. The method used to communicate disease surveillance data is through the excel spreadsheet (IDSR) which is called the integrated disease surveillance and response. Furthermore, the excel file will be sent to the relevant authority through email. However, we still do not have a web based system to report cases of diseases, instead this is a process starting from the intermediate hospital disease surveillance data which is captured then sent to the regional office and from the regional office the information is sent to the district office and then sent to the national office and from the national office the information is further sent to the WHO and other development partners as well as to the top management or to the highest authority. So it does not end at the national level but goes to management such as the Permanent Secretary, and the data is used to inform the develop- ment partners and the national surveillance office prepares official letters to the management as a form of reporting disease surveillance data. The symphonic surveillance office helps to detect a particular disease. The doctors send an investigation case form to the laboratory for testing the disease that has been identified. Keywords: Interoperability, HL7, Semantic Interoperability. 1 Introduction The Ministry of Health and Social Services in Namibia under the division of epidemiology currently faces chal- lenges of using a manual paper-based process of capturing disease surveillance data from the regional level, national level and eventually to the World Health Organization (Angula, Dlodlo, & Mtshali, 2019). This is the department in the Ministry of Health and Social Services that deals with disease surveillance data which includes different lev- els. Communicable diseases are the most common cause of illness, disability and death in Namibia. While these dis- eases present a large threat to the well-being of the Namib- ian communities, there are well-known interventions that are available for controlling and preventing them. Namibia has a relatively efficient surveillance and emergency pre- paredness and response (EPR) system in place (MoHSS, 2014). The Ministry of Health and Social Services has three levels of exchanging disease surveillance information such 30
  • 2. Enabling Semantic Interoperability of Regional Trends of Disease Surveillance Data 31 as the regional level which does not have a mandate to declare the outbreak of a disease in the region through monthly meetings and the CDC manager, facilities meet- ings and sharing information with other colleagues, col- lecting malaria statistics, and collecting data through other staff members that attend regional meetings. However, in these instances they don’t get real data as data is collected through a manual process through an investigation case form for malaria. The second one is a national surveil- lance office which deals with 5 levels of reporting, namely at community level, health facility level, district level, regional level, and national level which includes different offices such as one administrative office (IDSR) (integrated disease surveillance and response) which is responsible to report disease surveillance data as received every Monday and then submitting the data to the World Health Organ- isation and other development partners every Tuesday of the week (MoHSS, 2014). All the 35 district hospitals have a surveillance office that is responsible for facilitating the process of ensuring that disease surveillance data passes all the 5 levels of reporting disease surveillance data as well all the 14 regions which have a surveillance office that is responsible for reporting disease surveillance data to the right channel and the management health infor- mation office. If the community health worker detects an incident of an epidemic, he/she completes an investiga- tion case form and sends it to the health facility for further identification. Diseases are classified into a different cate- gory called case definition depending on the symptoms of that particular disease and then doctors determine if it is a known disease or an unknown disease. The community health worker in the field can gather disease surveillance data and send it to the intermediate hospitals such as Rundu hospital, Oshakati hospital, Katutura hospital and Windhoek Central hospital and at each intermediate hos- pital there is one surveillance officer who is responsible to complete an investigation case form and then sends it to the next level. In each health facility there is a dis- ease surveillance office that is responsible for receiving and sending disease surveillance data to the district office through completing an investigation case form. At the district level there is a disease surveillance office that is responsible for receiving disease surveillance data from the health facility and they send such information to the head office through completing an investigation case form. The national level receives disease surveillance data through the district level and the national level sends this informa- tion to the laboratory for testing purposes to identify what type of disease that is affecting a particular region and then the disease surveillance office has to go and physically col- lect the investigation case form from the laboratory and eventually sends the results to top management to declare that particular epidemic officially on media such as televi- sion and newspapers. So the process does not end only at national level but it further proceeds to the administrative office that is responsible for managing the integrated dis- ease surveillance and response system which is in excel format, and they report all the disease surveillance data weekly, monthly, quarterly, yearly. Moreover every Mon- day the disease surveillance data is received from all the four levels of reporting disease surveillance data and the submission of disease surveillance data is submitted to the World Health Organisation and development partners every Tuesday on a weekly basis. The national surveillance office is responsible for preparing official letters to report disease surveillance data. 1.1 Problem Statement In the Namibian health sector, different public health insti- tutions face challenges of lack of interoperability of health information systems (MoHSS, 2014). The Namibian health sector has many heterogeneous health systems which are not integrated in order to share and communicate with each other for the purpose of exchanging disease surveil- lance data from the 14 regional health directorates under the Ministry of Health and Social Services. This has been a major concern for the MoHSS because if one health profes- sional is in one health institution, then they cannot access information from the other health institution. The current method used by health institutions is a manual process that causes delays and this is time consuming when a health professional is capturing disease surveillance data from the regional level to the national level (Angula & Dlodlo, 2019). The current system being used by the Ministry of Health and Social Services to communicate and exchange health related information is through emails, telephone, What- sApp groups or taking a picture of something and sending it to whoever needs it and also through monthly meetings. The other method that is used to share disease surveil- lance data is through filling what is called an investigation case form. When sharing disease surveillance data, there is a form to be completed manually which is completed in one facility and then sent to the district office and from the district office, finally the form will be sent to the head office under the division of epidemiology where disease surveillance is done by the surveillance focal person. At the present moment, the Ministry of Health and Social Ser- vices does not have a health integrated system for disease surveillance data. With the DHIS2, you cannot view data that is entered from the regions and the regional people will view data that is entered by another region. In other words, there is no platform to exchange and communi- cate disease surveillance data in real time. The department of epidemiology in the Ministry of Health and Social Ser- vices usually receives disease surveillance data from the district office and regional office before the 5th of every month and all activities are done over a month and all
  • 3. 32 Nikodemus Angula et al. disease surveillance data is reported weekly and monthly, and at the same time the reports that are presented monthly and weekly are different and not the same reports. It takes time to capture data from the health facilities manually, and there is no access to other silo systems, and as such all systems do not communicate with each other. There are duplicate systems. 2 Literature Review 2.1 Interoperability Interoperability is a defined as way of exchanging and use of information in heterogeneous network made up of many local area networks (Diallo, Herencia-Zapana, Padilla, & Tolk, 2011). In other words, interoperability deals with information exchange whereby interoperable systems are characterised by their ability to exchange information. The definition stresses the fact that information exchange must be direct which conforms to the view depicted in figure one below (Diallo et al., 2011). The IEEE defines interoperability as inherent to a system (its ability to exchange information) which implies that systems are interoperable. Interoper- ability is defined as “the ability of two or more systems or components to exchange information and to use the information that has been exchanged” (Pagano, Candela, & Castelli, 2013, pp. 122–134). Asuncion and van Sin- deren (2010) discuss “pragmatic interoperability” as the interoperability dealing with mutual understanding in the use of data between collaborating systems. Recently, com- prehensive frameworks have been proposed to capture the many facets of interoperability (Candela, Castelli, & Thanos, 2010; European Commission, 2004). 2.2 HL7 HL7 International is one of several American National Standards Institutes (ANSI) accredited Standards Devel- oping Organizations (SDOs) operating in the healthcare arena (Working, Meeting, & Beebe, 2018). Most of these SDOs produce standards (sometimes called specifications or protocols) for a particular healthcare domain such as a pharmacy, medical devices, imaging or insurance (claims processing) transactions. According to Working, Meeting and Beebe (2018), HL7 international is a not-for-profit stan- dards Development Organisations (SDO). A “message” is considered the minimal unit of data transferred between systems using HL7. For example, an admission transaction would be sent as an HL7 “ADT” message. Messages are comprised of two or more “segments” that act as building blocks for each message (Rights, 2016). 2.3 Semantic Interoperability Semantic interoperability pertains to the possibility that information distributed over the net can be processed by programmes that understand the meaning of the bits and bytes in which the information items are encoded without the need for constant human interpretation (and trans- lation) (Heiler, 1995). Semantic interoperability plays a pivotal role in healthcare organisations through enabling ubiquitous forms of knowledge representations (Ashrafi, Kuilboer, & Stull, 2018). By integrating heterogeneous information, it strives to answer complex queries and pur- sue information sharing in healthcare. In healthcare, data exchange schema and standards allow data sharing across clinicians, labs, hospitals, pharmacies, and patients regard- less of the application or application vendor. However, the absence of interoperability within and across organi- sational boundaries impedes the ability to exchange infor- mation in a complex network of computerised systems developed by different manufacturers. 3 Methodology Two hospitals in the Khomas region of Namibia, the MoHSS, the CDC and members of the Khomas commu- nity participated in this study. The first phase of the study was qualitative, applying an interpretive approach and a qualitative multi-case study research design. Face-to-face interviews, focus group interviews, questionnaires and document sampling were used as data collection methods to identify the requirements for a semantic interoperability prototype that enables the integration of disease surveil- lance information in real time across the entire health sector in Namibia. Through laboratory experimentation, the second phase of the study led to the development of a prototype. Design science research was used to guide the development of the prototype. 4 Architecture of the System Different health facility can access disease surveillance data from heterogeneous health information and as a result, hospital statistics from different health facilities can pro- duce hospital statistics, malaria statistics, TB statistics and patients’ records statistics as long as the data is in JSON format. Figure 1 below represents the architecture of the pro- totype and its functionality which means surveillance data from different data sources can be aggregated and produces real time report to different health facilities in Namibia which aid in fast and informed decision making in the health sector in Namibia.
  • 4. Enabling Semantic Interoperability of Regional Trends of Disease Surveillance Data 33 Figure 1. Aggregated disease surveillance information. 5 Technology Demonstrator This is a login interface that can allow users who are regis- tered into the system to login. This shows the disease surveillance data captured in dif- ferent towns in Namibia, which indicates title and reports of a specific disease, possible disease name, severity and status, whether a disease is normal or unknown, and the name of town where disease occurred. Figure 3 below represents reports from different town in Namibia with possible disease cases such as Cholera in Figure 2. Login interface. (Own source: Prototype developed, 2018) Figure 3. Community surveillance report. Henties bay and Afghanistan in Windhoek. This means real time surveillance data can be accessed at the same time from different town in Namibia which enables health pro- fessionals to make fast and informed decisions timely. 6 The Profile Cross-Enterprise Document Sharing (XDS) is an integrated health profile that enables several healthcare service deliv- ery organisations that belong to an XDS Affinity Domain to cooperate in the care of a patient by sharing clinical records from heterogeneous systems. 7 Discussion In the Namibian healthcare sector, the process of cap- turing disease surveillance is a manual process which is time consuming. Disease surveillance is captured manu- ally following the 5 levels of reporting which includes the community level, health facility level, the district level, and the national level. At each level, the process of captur- ing disease surveillance data is captured manually which causes delays when a health professional wants to access such information in real time using data from all the levels. Therefore, the study developed a prototype that aggregates disease surveillance data from the 14 regions in Namibia which can enable disease service offices to capture disease surveillance data through the use of mobile devices. The system users The system will be used by health professionals in min- istry of health and social services in Namibia such as nurses, doctors and COVID-19 management committees. The Cross-Enterprise Document Sharing diagram below represents a mechanism how surveillance data can be Figure 4. Cross-Enterprise Document Sharing-b (XDS.b) diagram. (Source: IHE IT Infrastructure Technical Framework, 2018)
  • 5. 34 Nikodemus Angula et al. exchanged and communicated among different health stakeholders in the Namibian health domain. This is a type of integrated profile that does not define specific policies and business rules; however, which has been designed to accommodate a wide range of such poli- cies to facilitate the deployment of standards-based infras- tructures for sharing patient clinical documents. In addi- tion, this integrated profile managed through federated document repositories and a document registry to create a longitudinal record of information about a patient within a given XDS Affinity Domain. 8 Conclusion The Ministry of Health and Social Services uses a manual process of capturing disease surveillance data which under goes five levels of reporting and which includes five levels of reporting which includes the community level, health facility level, district level, and national level. The Ministry of Health and Social Services does not have a platform that interlinks the hospitals’ silo systems with ministry systems. There is no system that tracks contagious disease and as it stands, the ministry or hospitals rely on the person in the hospital or the ministry. Therefore, this study developed a prototype that aggregates disease surveillance data from the 14 regions in Namibia that can enable the disease ser- vice office to capture disease surveillance data through the use of mobile devices. References Angula, N., Dlodlo, N., & Mtshali, P. Q. (2019). Enabling semantic interoperability of crowdsourced disease surveillance data for Namibia through a health-standards-based approach. IST Africa 2019. Kenya, Nairobi, 34–35. Retrieved from https://www.semanticscholar.org/ paper/Enabling-Semantic-Interoperability-of-Crowdsourced-Angu la-Dlodlo/1f5096bc2787e27357fe0b65592407d1a6035a40. Ashrafi, N., Kuilboer, J. P., & Stull, T. (2018). Semantic interoperability in healthcare: Challenges and roadblocks. CEUR Workshop Proceed- ings, 2107, 119–122. Retrieved from http://ceur-ws.org/Vol-2107/ Paper1. Asuncion, C., & van Sinderen, M. (2010). Pragmatic interoperability: A systematic review of published definitions. Enterprise Architecture, Inte- gration and Interoperability, IFIP Advances in Information and Communication Technology, Springer, pp. 164–175. Retrieved from https://link.springer.com/chapter/10.1007/978-3-642-15509-3_15. Candela, L., Castelli, D., & Thanos, C. (2010) Making digital library con- tent interoperable. Digital Libraries – 6th Italian Research Confer- ence, IRCDL 2010, Padua, Italy. Revised Selected Papers, pp. 13–25. Retrieved from https://www.researchgate.net/publication/22133 3809_Making_Digital_Library_Content_Interoperable. Diallo, S. Y., Herencia-Zapana, H., Padilla, J. J., & Tolk, A. (2011). Under- standing interoperability. Emerging M and S Applications in Industry and Academia Symposium 2011, EAIA 2011 – 2011 Spring Sim- ulation Multiconference, (May 2014), 84–91. Retrieved from https: //www.odu.edu/vmasc/research/simulated-empathy. European Commission (2004). European Interoperability Framework for Pan- European eGovernment Services. Luxembourg: European Commis- sion. Retrived from https://ec.europa.eu/idabc/servlets/Docd552. Heiler, S. (1995). Semantic interoperability. ACM Computing Surveys (CSUR), 27(2), 271–273. Retrieved from https://doi.org/10.1145/ 210376.210392. Kuechler, B., & Petter, S. (2012). D Esign S Cience R Esearch in, 1–66. Retrieved from https://doi.org/1756-0500-5-79 [pii]r10.1186/ 1756-0500-5-79. MoHSS. (2014). National technical guideline for integrated disease surveillance and response division of epidemiology subdivision: Disease surveil- lance and emergency preparedness and response. Retrieved from https://www.researchgate.net/publication/266778090_Technical_ Guidelines_for_Integrated_Disease_Surveillance_and_Response_ in_the_African_Namibia. Pagano, P., Candela, L., & Castelli, D. (2013). Data interoperability. Retrieved from https://doi.org/10.2481/dsj.GRDI-004. Rights, P. (2016). HL7 Interface Specifications 2016, 44(0), 0–52. Retrieved from https://www.interfaceware.com/iguana.html?utm_medium. Working, H. L., Meeting, G., & Beebe, C. (2018). Introduction to Health Level Seven (HL7) International Organization & Process Ori- entation. Retrieved from https://www.hl7.org/documentcenter/ public/calendarofevents.