Available via license: CC BY 4.0
Content may be subject to copyright.
Received: April 12, 2023. Revised: July 24, 2023. Accepted: August 2, 2023
© The Author(s) 2023. Published by Oxford University Press. All rights reserved.
Oxford Open Digital Health, 2023, 00,1–8
https://doi.org/10.1093/oodh/oqad015
Research Article
Critical factors influencing data use and utilization in
health systems: a focus on data and interoperability
standards for health information exchange (HIE) in
Uganda’s health care system
Moses Bagyendera, Peter Nabende and Josephine Nabukenya*
Department of Information Systems, Makerere University, P.O Box 7062, Kampala, Uganda
*Corresponding address. Tel.: +256 776 658800; Fax: +256 540628; E-mail: josephine@cit.ac.ug
Abstract
Limited use and utilization of health data in Uganda’s health care system is influenced by various factors including: absence of
standardized data formats, lack of data governance policies, unskilled data management human resources, limited data use culture,
poor data quality,complacency, limited political will and lack of interoperability. Worse still, the existing data interoperability standards,
primarily designed for developed world health systems, may not be suitable for Uganda due to differences in health information
maturity levels. This paper examines the critical factors affecting data use and utilization in Uganda, specifically focusing on
interoperability and data standards.
A cross-sectional design was used in this study in selected health facilities with electronic systems in Uganda. Purposive sampling
was used to select sites and participants based on predetermined criteria. The study included 28 health center IVs, referral hospitals,
government entities and eHealth stakeholders.
The findings highlight key factors including limited data collection and management systems, poor data quality, inadequate data
analysis capacity, absence of data exchange standards,limited technology access, inadequate funding and deficiencies in data sharing
and dissemination.
These factors, if addressed through data and interoperability standards, can play a pivotal role in promoting efficient and effective
health care delivery and outcomes in Uganda.
Keywords: interoperability standards; data use; utilization; health information exchange
INTRODUCTION
The meticulous adoption and compliance with health data stan-
dards in Uganda’s health systems play a pivotal role. These stan-
dards promote effective health care delivery, leading to improved
outcomes for patients. In addition, they foster research and inno-
vation, unlocking the full potential of health data for the benefit
of the country’s health care ecosystem.
Uganda faces several challenges related to the use and utiliza-
tion of health data. These challenges include limited data collec-
tion and management systems, poor quality data, limited data
analysis capacity, limited technology access, inadequate funding
and poor data sharing and dissemination. Addressing these chal-
lenges requires a multi-pronged approach that involves investing
in health information systems and technology, improving data
collection and management practices, increasing data analysis
and interpretation capacity promoting data sharing and dissem-
ination and fostering a culture of data use and evidence-based
decision-making [1]. Data use and utilization are crucial in a
well-functioning health delivery system. It helps in planning and
monitoring disease interventions, ensuring continuity of patient
care, making informed decisions, allocating resources effectively
and developing strategies. However, it is important to have data
policy guidelines, adaptive standards and prevailing guidelines to
support data use and utilization [2].
The practice of public health use and utilization regarding the
data management process can be considered to comprise a three-
data management process (Marjanovi´
cet al., 2018). First, data
on some aspects of a health issue are gathered (data collection)
[3,4]. Second, the data are studied and analysed (data analysis)
[5–7] and in the process, they are transformed from data into
information (data processing) [8]. Third, this information guides
a course of action (data use) aimed at changing for an improved
social health condition (data utilization) [9].
Uganda has made advancements in utilizing information
technology for health data reporting through the electronic
Health Management Information System (HMIS) [12,14,15].
Policy guidelines and frameworks, such as the ICT Policy, eHealth
Policy and eHealth Strategic Plan, have been implemented to
guide and enhance the use and utilization of health data [11,13].
These policy guidelines are essential for promoting evidence-
based decision-making, improving health outcomes and ensuring
accountability [10].
HMIS have played a significant role in addressing health deliv-
ery problems and generating credible evidence about the client’s
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Tab le 1. Study respondents
Sub-regional study area Facilities Respondents
Central 4 HCIV 13
South Western 4 HCIV, 2 referral hospitals 15
Northern 4HCIV, 3 referral hospitals 13
West Nile 4 HCIVs 11
National 4 MoH national programs & 3 health implementation partners 16
Tota l 28 68
health status [3,4]. They are crucial for decision-making at every
level of the health system. HMIS collect and manage epidemiolog-
ical and administrative information, allowing for the appropriate
identification of disease burden and service utilization [10].
The adoption of data standards is crucial for seamless health
information exchange and interoperability across the health
ecosystem [16,17]. The National eHealth capacity roadmap high-
lights the need for data standards, communication infrastructure,
health information management, interoperability and security
standards to facilitate the exchange of patient information
and aid decision-making [18]. The power of health data lies in
its aggregation, interpretation and use for actionable decision-
making. Therefore,standards data formats, interoperable systems
and consistency in quality assurance are essential for the effective
use of health data in research, innovation, health care delivery
and health policy [10].
Despite the formulation of the National eHealth Policy and
Strategic Framework, there is need for more implementation
regarding adopting data standards and guidelines to achieve
seamless health information exchange and enhance data use
and utilization. This study aims to explore the factors affecting
data use and utilization, with specific focus on interoperability
and data standards in Uganda’s health care system.
METHODS
Study Area: The researchers used a cross-sectional design to
capture a big picture of the study subjects at a single time point.
The research primarily concentrated on specific health facilities
equipped with electronic systems, which were chosen as case
studies based on the support received from donors for data report-
ing and routine health information systems indicators. Notably,
∼70% of HMIS (Electronic Health Management Information Sys-
tem) implementation in Uganda is backed by implementing part-
ners, particularly at the HCIV (health center IV) level,making it a
significant factor in the selection process. Among the electronic
systems studied were District Health Information Systems ver-
sion 2 (DHIS2), mTrac, UgandaEMR, Integrated Clinical Enterprise
Application (ICEA) and RxSolution. These systems are integral
components of the HMIS and play a crucial role in capturing,
managing and analysing health data for improved health care
services and decision-making [19,20].
The study area encompassed four key regions in Uganda: Cen-
tral, West Nile, South-Western and Northern, which represented
a high rate of HIV and TB prevalence rates in Uganda [21] as illus-
trated in Table 1. Sample selection of facilities was predominantly
based on the availability of electronic health information systems
(eHIS) primarily supported by health development partners. The
regions included urban high-prevalence areas characterized by
mobility, slum dwelling and limited social support,as well as rural
areas prone to the influx of refugees [21].
Besides sampling the study facilities, the respondents (indi-
cated in Table 1) were purposively sampled. This sampling
method was chosen to identify cases that focused on well-
supported eHIS at the Health Centre four (HCIV) facility
level, meeting predetermined criteria of importance [22]. The
study included 16 HCIVs, 5 regional referral hospitals (RRH)
or district hospitals (DH), 4 Ministry of Health (MoH) national
program areas and 3 health implementation partners that
had eHIS supported by development partners [23]. These
participants were selected based on their involvement in
developing the Uganda national eHealth strategy/policy, research
in eHealth development/investment and implementation of
eHIS [23]. The total sample size comprised 52 responses from
the sub-national level and 16 respondents from the national
level.
The selection of health workers as participants was based on
their roles as officers-in-charge of health facilities, information
and communication technology (ICT)/data/records/Monitoring
and Evaluation (M&E) officers, or users of eHealth in various cat-
egories such as clinical off icers,nurse pharmacists and laboratory
technologists. National-level participants included eHealth poli-
cymakers, standard/guideline developers, health implementation
partners and health systems and health informatics researchers.
Only participants who consented to participate in the study were
interviewed.
Ethical Considerations: Ethical considerations were addressed
by obtaining consent from the Ministry of Health to access the
study sites and obtaining ethical clearance from the institu-
tional review board (IRB) of the School of Public Health, Makerere
University. Informed consent was also obtained from the study
participants before conducting interviews.
Data Collection and Analysis: Data collection involved the use
of interviews and questionnaires administered to stakeholders
at the facility level. Follow-up interviews were conducted at the
national level to show the status quo regarding challenges of
data use and accessing relatively,and integrated patient data. The
qualitative data (i.e. predominantly collected at the national level)
were analysed following the framework method [6,24].
For data collection (quantitative), Open Data Kit (ODK) was
used, and facility-level data analysis was performed using
Microsoft Excel 2019 (Excel 16.0). This enabled the exploration
of relationships within the data, and the results were presented
through graphs to illustrate challenges related to data use and
accessibility effectively. Regarding qualitative data collected at
the national level, NVivo 12 software was used for coding during
qualitative analysis. This approach facilitated the identification
of key factors influencing data use and utilization in the
sector. By combining quantitative and qualitative methods, the
study achieved a comprehensive understanding of the issues
at hand, enhancing the overall validity and reliability of the
findings [25].
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Oxford Open Digital Health, 2023, Vol. 00, No. 00 |3
Tab le 2. Categorization of Respondents
Categorization of respondents Regions Percent
Nurses (HCIVs/RHs) Sub-national 26%
Medical officers (HCIVs/RHs) Sub-national 15%
Laboratory (HCIVs/RHs) Sub-national 14%
Pharmacy (RHs) Sub-national 13%
Facility-in-charges (HCIVs) Sub-national 11%
Health systems and health informatics researchers’ departments and agencies (MDAs) National 6%
Policymakers from ministries National 4%
Health care development partners (HDPs) National 3%
Figure 1. Types of health data collected
RESULTS
Results of this study were based on 68 responses obtained
from the HCIVs, sub-national and national levels as shown in
Table 2. Results show that health facility information sharing in
Uganda lacks data standards, hindering interoperability. Standard
operating procedures (SOPs) for sharing health information are
incomplete, and procedures for accessing electronic medical
records (EMRs) are poorly documented. Capacity gaps, lack of
evidence-based decision-making and limited funding further
impeded timely health data access and electronic sharing,
affecting patient care continuity.
Uganda’s current state of health data use – the health sector in
Uganda faces challenges due to fragmented ICT projects and data
silos, impeding information sharing among stakeholder’s players
[26]. The lack of interoperability, varying data guidelines and
limited coordination between health programs contribute to the
problem. Insufficient funding and shortage of skilled personnel
further worsen the situation.
Type of data collected – health care workers in Uganda collect
various types of data based on their facility’s mandate and role.
Some institutions collect health data directly, whereas others
gather non-health data that supports different health systems
in the country. The types of data collected include demographic
data, physical examination results, investigation findings, med-
ical history, treatment information, diagnosis data and referral
information. Figure 1 shows the different types of data that health
workers collect in performing their duties.
Health workers in Uganda collect a variety of health care data
in their roles. The data collection rates for different types of
information were as follows: demographic data (23%), physical
examination results (13%), investigation findings (13%), medical
history (12%), treatment information (9%) and diagnosis data
(8%). Referral information was the least gathered, reported at 4%.
This is supported by responses from respondents who mentioned
collecting biodata, symptoms, signs, treatments, referral informa-
tion and statistics related to various health conditions. ‘We collect
biodata, symptoms and signs, treatments and referral information; we
also keep the number of households in the community.’ - HSL4_01.
‘We collect biodata and the symptoms, diagnosis, treatment, prescription,
referrals, statistics of mothers who have given birth, newborn, pregnant
mothers and HIV clients’ details and death in the community (cause, time,
name).’ - HSL4_09.
Data collection methods – health workers use various methods
to collect health data. These include manual processes such as
using plain books, well-formatted registers and specific program
forms. Respondents mentioned registration at triaging points,
record processes including laboratory tests, and using exercise
books and registers when patients are present. ‘We just have
registration at the triaging point and go through different record processes
including lab before treatment.’ - HSL4_09. ‘We use exercise books to
record patient treatment and the registers and records when the patient
is there.’ - HSL2_06. In addition, some respondents mentioned the
use of electronic devices, particularly for HIV patients. For exam-
ple, in the ART Clinic, EMR managed by a data officer are used,
and files are sent to the officer for updating. In the outpatient
department (OPD), registers are taken to the records officer for
data entry. Electronic methods are also used on a smaller scale
in other contexts. ‘In ART Clinic, they use EMR, which a data officer
manages; the staff there, send the files to the officer to be updated. For
us in the OPD, the registers are taken to the records officer to enter the
data.’ - HSL4_08. ‘We use electronic methods to record data apart from
the ART clinic on small scale.’ - HSL4_07.
Howdataisused–the collected health data are used in various
ways to benefit the health care system. It supports continuous
monitoring and evaluation processes, helps assess the impact
of programs on reducing mortality and aids in understanding
the extent of program implementation. ‘This information is used
to identify problems of particular patients and feedback.’ - HSL4_04. In
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4|Oxford Open Digital Health, 2023, Vol. 00, No. 00
Figure 2. Guidelines implemented
addition, health data are valuable for planning and budget analy-
sis, providing insights into periodic disease trends and facilitating
proper resource management in health care facilities. The data
are often summarized in charts and graphs at the primary source
health facility and reports are submitted monthly to the district
and national office at the Ministry of Health to aid decision-
making. ‘At my level, nursing officer, I make a summary which is
used for reporting.’ - HSL4_05. Furthermore, health data are used
to identify problems in individual patients and provide feedback.
‘This information is used to identify problems of particular patients and
feedback.’ - HSL4_04. Nursing officers also utilize the data to create
summaries for reporting purposes. ‘At my level, nursing officer, I
make a summary which is used for reporting.’ - HSL4_05.
What Standards/Guidelines support data use – standards and
guidelines play a crucial role in facilitating effective and efficient
collection, management and use of health data within organiza-
tional and health care environments. These guidelines provide a
framework for ensuring data quality, privacy and interoperability,
thereby supporting the timely and integrated collection, analysis
and exchange of patient data. Figure 2 illustrates the state of stan-
dards and guidelines for implementing and using ICT to support
the collection, analysis and exchange of patient data. It includes
guidelines for security and privacy. However, the study found
challenges with these guidelines, which impeded the expected
quality, security and timeliness of patient data across various
data systems. For instance, guidelines for monitoring eHealth use
received a neutral response from 41.7% of respondents. Similarly,
42.4% expressed neutrality toward guidelines for accessing EMRs,
and 43.2% showed neutrality toward guidelines for implementing
ICT at health facilities.
Despite respondents acknowledging the existence of guide-
lines, their responses lacked documentation supporting the
applicable standards and guidelines beyond flowcharts on the
walls. This suggests that the guidelines may not have been
effectively rolled out to lower level facilities, resulting in a lack
of integration and interoperability among systems, thus affecting
data use. Respondent HSL4_24, mentioned that the guidelines
were reviewed and posted on the wall without further details or
documentation. One respondent, HSL4_26, even mentioned the
absence of SOPs for using ICT while providing HIV/TB services
in their district hospital, indicating a lack of awareness of data
guidelines in lower facilities.
Among the respondents, 20% agreed on the existence of data
sharing guidelines, whereas 24.2% acknowledged the presence of
security guidelines. Most (71.2%) agreed that there are guidelines
in place to safeguard the privacy of personally identifiable patient
data. However, there was limited understanding of the distinction
between data guidelines and standards, indicating inadequate
involvement of stakeholders in the development, implementation
and use of guidelines. Although some guidelines exist, their imple-
mentation and compliance have been minimal.
Factors influencing data use in Uganda health
systems
Several factors affect data use and utilization in Uganda’s health
care system, with particular focus on interoperability and data
standards. Respondents who indicated that they use health infor-
mation systems (data management) identified seven challenges/-
factors that they experienced in using electronic medical/health
records as shown in Fig. 3.
Poor data quality: In relation to the impact of poor data quality
on the decision-making process, 30% of the respondents were in
accord. They highlighted that inaccurate or incomplete data can
have a detrimental effect on decision-making outcomes. Several
contributing factors to poor data quality, such as inconsistent
data entry practices, insufficient training and the absence of data
validation procedures,were identified. It is important to note that
poor data quality can undermine the effective use and utilization
of data in the health care sector as evidenced by this respondent,
who said ‘Some data we produce from facilities are not good data; there
are skill gaps in a way data are collected, health care professionals want
to spend taking care of patients, not collecting data.’ - HSL4_04.Another
respondent argued that ‘Health care professionals have to attend
to patients instead of data management.’ - HSL4_06.‘Facedwiththe
dilemma, health workers often choose alternative patient care activities
to data capture, and issues of data are always questionable, sometimes
it doesn’t look like ours.’ Then, ‘The government or MoH should educate
people in analysing data.’ - HSL4_03.
Lack of standardized data formats: Different health care
providers use different data formats or systems, making it
difficult to exchange and use data effectively. Limited guidelines
and manual forms hinder interoperability and data integration
from different sources, as indicated by 45% of the respondents.
This was evidenced by several respondents who reported that ‘It
would be better for me when the information is just written on paper
because as long as you put it on electronic, sometimes it looks different
using different systems. In any, case we can’t afford gadgets like phones
and computers.’ - Implementing Partner_02. ‘There is a big gap in the
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Oxford Open Digital Health, 2023, Vol. 00, No. 00 |5
Figure 3. Factors affecting data use and utilization
use of ICT, people lack ICT skills and have phobia. The network is very
poor, and often, there is no electricity. When the computers break down,
there is no contact person to repair them, leaving them unutilized for a
long time, hence affecting data quality and removal of errors. The work
on supplying the HMS forms was left to IPs whose agenda is different;
they supply different versions, and they are also interested in collecting
different data, e.g. HIV data.’ - HSL4_04.
Limited interoperability: Among the respondents,a consensus
of 34% was reached, highlighting the prevalent practice of health
care providers in Uganda utilizing distinct electronic health record
(EHR) systems. Furthermore, it was noted that these systems may
lack interoperability,indicating a lack of seamless communication
and data exchange between different EHR platforms as evidenced
by this respondent, who said ‘Yes, we have many systems generating
data that are different or can’t be used together for our work and
reporting. This has become challenging, with most hospitals equipped
with computers and connected to the Internet yet not being able to share
data.’ - PM_04.
Inadequate technical infrastructure: Many health care facili-
ties lack the necessary technical infrastructure for effective data
collection, storage and use.This includes reliable Internet connec-
tivity, servers and storage systems and data analysis and visual-
ization software tools. Forty-five percent of participants indicated
poor infrastructure as a big factor and made statements such as
‘We don’t have the ICT infrastructure.’ - HSL2_0; ‘There is limited ICT
infrastructure.’ - HSL2_04; ‘Our infrastructure is still poor.’ - HSL4_14;
‘There is a limitation in Internet access countrywide.’ - HSL4_15; and
‘There’s still low Internet penetration.’ - HSL2_03.Such challenges
remain technological hindrances to the implementation of data
capture, processing and presentation platform. Thus, participants
suggested that ICT infrastructure for health be extended to cover
the entire country, electrical power be extended to the last mile
of a health facility, avail respective health care personnel with
devices for data capture and access and each district or health
center should have an Internet connection and adequate comput-
ers and procure developed system applications compatible with
both mobile and desktop computing devices. Despite improve-
ments in ICT infrastructure like the extension of the Internet
backbone, inaccessibility remains a challenge in hard-to-reach
rural health facilities across the country.
Lack of data governance policies: Effective data governance
policies are essential for managing data quality and ensuring
the ethical use of patient data. In the context of health care
in Uganda, 36% of the respondents pointed out the absence of
effective data governance policies and practices in a significant
number of health care facilities. This deficiency has the poten-
tial to impede the effective use and utilization of data in the
health care sector. Weak data governance, including limited data
management policies, poor data security protocols and weak data
privacy regulations, make it difficult to use data effectively as
evidenced by these respondents, who said ‘We have systems that
don’t share datasets for use, they are work in silos not interoperable and
guidelines to enforce interoperability. The is a huge gap of no standards
in place. Everyone develops a system and this piloted system happening
a lot with no sustainability plans.’ - IP_03 and ‘There are limited
guidelines documented for use but no compliance measures to apply
these.’ - HSL4_15. This can lead to mistrust in the data and prevent
its use in decision-making.
Limited data security and privacy: Data security and privacy
are key concerns in health care, and the lack of adequate data
security and privacy measures can undermine data use and uti-
lization efforts. Health care data are highly sensitive, and ensuring
that patient data are kept secure and private is critical. Data
security and privacy concerns can strongly affect data exchange
and use across different systems. Health data/information pri-
vacy and security emerged as a matter of great importance, as
agreed on by 32% of the respondents. These individuals, such
as HSL2_02 and HSL4_13, expressed concerns over the lack of
capacity and guidelines to safeguard their data and systems
from external threats. Incidents like the robbery of equipment
further emphasized the need for robust security measures. This
sentiment was shared by decision-makers, patients and health
workers alike, underlining the universal significance placed on
health data privacy and security.
Human Resources with inadequate data skills: Health care
providers and other stakeholders were recognized by 35% of the
respondents as having limited skills and knowledge required to
effectively utilize data. This deficiency in skills and training was
evident in the comments provided by participants. For instance,
HSL4_01 highlighted the time lapse between training and imple-
mentation, resulting in forgotten skills and a lack of practice.
Similarly, HSL4_02 emphasized the constant influx of new tech-
nologies and advanced equipment that health care providers
struggle to use proficiently, indicating the need for change man-
agement. To address this issue, providing training and capacity-
building opportunities becomes crucial in establishing a strong
foundation of skills and knowledge to support effective data use
and utilization. Without adequate training and capacity building,
health care providers may encounter difficulties in utilizing the
available data. Limited capacity for data use may stem from
factors such as a lack of training, unawareness of data importance
or absence of clear data use policies. These sentiments were
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echoed by respondents like HSL4_02, who mentioned a shortage
of computers and staff unfamiliarity with their usage, and DHO
Wakiso District, who highlighted low staff turnout in training
due to the desire for allowances. Other challenges included the
considerable time required to learn the system, as indicated by
IP_01 and several other respondents.
Scanty resources: In addition to the challenges previously
mentioned, Uganda’s health care system also grapples with
financial constraints that restrict investments in health infor-
mation systems, data infrastructure and capacity building. As
highlighted by 40% of the respondents, insufficient funding
emerges as a significant concern. This sentiment is echoed by
HSL4_06, who emphasizes the pervasive nature of funding issues
and the bureaucratic hurdles surrounding data due to a lack
of awareness. Moreover, HSL4_27 draws attention to the limited
resource envelope at the national level,which poses hindrances to
data use initiatives. The financial limitations faced by Uganda’s
health care system further compound the existing difficulties
in effectively utilizing health data and implementing robust
information systems.
Inadequate political will and leadership: To ensure effective
data use and utilization in Uganda’s health care system, it is
crucial to establish robust policies and practices supported by
strong political will and leadership at all levels. This entails defin-
ing clear priorities and goals for data use, allocating resources
toward data infrastructure and capacity building and fostering
a culture of data-driven decision-making. However, an alarm-
ing 50% of respondents indicated that limited political support
hampers effective data utilization. The presence of fragmented
information systems directly results from uncoordinated donor
initiatives. As highlighted by implementing partner_03, numerous
pilot projects without standardized data practices result in incom-
patible and non-interoperable systems, lacking any sustainability
plans. Furthermore,the influence of multiple implementing part-
ners without unified guidance, as expressed by PM_04, adds to the
challenges faced by many implementing partners who set prior-
ities not necessarily beneficial to the government. The absence
of strong leadership and political will undermines health care
providers’ prioritization of data collection and use, thus limiting
the potential utility of the available data. Addressing these gaps
and fostering a culture of data-driven decision-making necessi-
tates strong political commitment and leadership to elevate the
importance of data use and utilization efforts.
DISCUSSION
The current state of data use and utilization – health data has
the potential to offer significant benefits for patients, research
and innovation [27]. However, realizing the full potential of health
data requires a sustainable and effective health data ecosystem
[28]. Core competencies in data analysis, interpretation, synthesis,
presentation and the development of data-informed recommen-
dations are essential at all health system levels to improve the
demand and use of data [29]. Unfortunately, these skills are often
deprioritized compared with capacity-building initiatives focused
on data management, verification and validation, resulting in a
lack of technical capacities and skills in data use core competen-
cies among the workforce [30–36]. Organizations that intend to
share data should deploy data sharing standards as part of their
integration efforts [35,36]. Data sharing standards are imperative
to support the integrated and timely sharing of health informa-
tion and patient data [37]. These standards ensure the capture of
proper and interpretable data formats and govern the exchange
of health data, allowing only authorized personnel to access
patient data and ensuring the security and privacy of patient
information [38].
Consistency in data definitions and formats with agreed-on
data standards and standardized vocabularies is crucial for data
reliability [12]. Without adherence to data standards, data transfer
from one EMR or system to another is prone to error [13]. The
provision of health care services is complex, time-consuming and
includes potential errors at various stages [39,40]. Health care
providers must gather vital data, communicate with partners and
share information to reach appropriate decisions [16]. The inte-
gration of eHealth systems into modern health care has exposed
a growing range of health care professionals to the challenges of
using and benefiting from such systems [41–43]. For eHealth to
provide timely, accessible and integrated health data, users must
have the necessary skills and knowledge [19].
Factors that influence data use and utilization – several fac-
tors inf luence data use and utilization, including intra-facility and
inter-facility data sharing [44,45]. However, field findings indicate
that current SOPs for sharing health information are not compre-
hensive and lack the adoption of data standards to guide patient
data sharing[46–49]. Documentation of procedures for accessing,
storing and disseminating data guidelines is either lacking or not
widely shared, hindering timely access and electronic sharing of
patient data [23]. In addition, [11] insufficient technology skills
among human resources and a lack of political will and coordi-
nated donor support further contribute to challenges in data use
and utilization [24].
To address these challenges, there is a need to train health
care providers in disciplines related to ICT [50–53]. Equipping
health care providers with ICT skills and demonstrating the
eHealth benefits is essential to influencing their attitudes
toward eHealth and generate quality health data essential
[53]. Efforts should also be made to make eHealth culturally
appropriate by customizing it according to local language and
appearance [54,55].
In Uganda, as in other low- and middle-income countries
(LMICs), the adoption and use of data standards in eHealth
systems are limited [56–59]. Uganda’s Ministry of Health has not
formally adopted or contextualized data standards for eHealth,
leading to fragmented implementation and a lack of integrated
data sharing for patient care eHealth [59]. Uganda needs to
adopt, contextualize or develop data standards to support
reliable, timely and integrated access to patient data [43,59–62].
Developed health systems focus on harmonizing standards for
data exchange, protecting personally identifiable information
(PII) and evaluating conformity with these standards [63–68].
This study highlights health care providers’ lack of sufficient
skills and knowledge accessing timely, reliable and integrated
patient data [4]. Gaps in user skills of eHealth applications and
data managing technologies, including understanding security
measures and patient digital information privacy concerns,
directly affects full utilization of health information systems in
order to capture, share and use health data for prompt decision-
making workforce [31–35]. Therefore, achieving successful use of
eHealth requires a highly skilled eHealth critical mass [35,36].
CONCLUSION
This study provided the critical challenges obstructing the uti-
lization of health data within Uganda’s health care ecosystem.
These barriers included but are not limited to: limited data use,
insufficient awareness of data standards, lack of interoperability,
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Oxford Open Digital Health, 2023, Vol. 00, No. 00 |7
governance issues, inadequate data management support and
resource constraints. To overcome these hurdles, proactive mea-
sures and effective strategies are imperative. A key recommenda-
tion is the establishment of interoperability data standards and an
interoperability framework. This approach will enable seamless
data integration and sharing across various systems, emphasizing
data privacy and security.Implementing this framework can opti-
mize decision-making processes, enhance operational efficiency
and lead to improved outcomes for health care providers and
organizations. By addressing these critical factors and adopting
the suggested strategies, Uganda can fully unlock the potential of
health data use and utilization, resulting in significant improve-
ments in health care services and better health outcomes for
its population. The availability of reliable and comprehensive
data will support health care providers in making well-informed
decisions and elevating patient care standards. Accordingly, this
study emphasizes the urgency of addressing data utilization chal-
lenges in Uganda’s health care system. By doing so, the country
can make substantial advancements in health care delivery, ulti-
mately enhancing the well-being of its population.
AUTHORS’ CONTRIBUTIONS
M.B. conceptualized the research goal, management of the data
and led the manuscript preparation. J.N. grounded and signifi-
cantly shaped the research problem as well as provided over-
sight and leadership throughout the research and manuscript
preparation. P.N. provided oversight throughout the research and
manuscript preparation.
DATA AVAILABILITY
Data are available on request. The data underlying this article will
be shared on reasonable request by the corresponding author.
CONFLICT OF INTEREST
None declared.
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