Reforming Uganda's digital health data systems: A policy analysis for inclusive,equitable,and decolonised data governance

Abstract

Uganda has rapidly digitised many health services, but persistent challenges in data governance − including fragmented systems, variable data quality, and the exclusion of vulnerable populations − hinder effective care and equity. This analysis reviews recent developments (2023–2025) in Uganda's digital health policy and practice, drawing on strategy documents, conference reports, and stakeholder input. It highlights how the COVID-19 pandemic accelerated innovation while exposing systemic weaknesses. For example, the Ministry of Health’s (MoH) 2023 strategy explicitly targets data accessibility and integration, and the 2024 guidelines standardise management across the sector. Yet, execution gaps remain due to resource constraints and organisational silos. This article proposes an inclusive data governance framework with five pillars (inclusive governance, equity, interoperability, privacy, and capacity) and recommends concrete actions. By adopting these reforms, Uganda can transform its digital health systems into people-centred, equitable platforms that build trust, protect rights, and advance universal health coverage.

Introduction

Digital health governance refers to the institutional arrangements, legal frameworks, and policy mechanisms that oversee the design, implementation, and regulation of digital technologies within a health system. It ensures that data is collected, managed, and utilised in ethical, secure, and equitable ways, while aligning technology deployment with broader public health goals.^1,2 Within this governance framework, digital health technologies, including electronic medical records (EMRs), mobile health applications, and telemedicine, hold substantial promise for enhancing Uganda's healthcare system. These innovations offer pathways to improved efficiency, more informed data-driven decision-making, and expanded access to essential care across the nation.^3,4 However, the realisation of these transformative benefits is fundamentally contingent upon the establishment of robust data governance − the comprehensive set of rules, structures, and oversight mechanisms that ensure health data is collected, managed, and utilised in an ethical, secure, and transparent manner. ⁵

At the global level, digital health systems have become integral to health sector agendas. The World Health Organisation (WHO) and its regional office for Africa have urged member states to implement national digital health strategies consistent with the Global Strategy on Digital Health 2020–2025, which emphasises interoperability, ethical data use, and equity as core principles. Regionally, the African Union's Data Policy Framework (2022) and the Africa CDC's Health Data Governance Initiative (2023) provide foundational blueprints for harmonised standards, privacy protection, and cross-border data collaboration.^6,7 Several African countries − such as Kenya, Rwanda, and South Africa − have already operationalised digital health councils or interoperability frameworks that domesticate these regional commitments into practice. Uganda's evolving strategy emerges within this broader movement, offering a context-specific example of how global and continental governance norms are being localised to strengthen national health systems. ⁸

Uganda's journey in health governance is deeply influenced by its colonial past, with some existing laws and organisational norms reflecting outdated structures inherited from colonial or missionary eras, such as restrictive reproductive health policies and the prominence of faith-based health providers. ⁹ Furthermore, the nation's profound diversity − spanning geographical variations (highlands versus plains), linguistic richness (over 40 languages), and socio-economic disparities − presents a complex challenge. A uniform, one-size-fits-all digital solution risks marginalising significant portions of the population, particularly if technology design fails to accommodate local contexts and cultural nuances.^10,11 Therefore, the adoption of inclusive and culturally sensitive approaches is not merely beneficial but essential for the successful and equitable implementation of digital health initiatives.

The recent outbreaks served as an unexpected yet profound stress test for Uganda's nascent digital health infrastructure. It dramatically illustrated both the immense power and inherent pitfalls of digital health technologies. The crisis rapidly accelerated the deployment of online information campaigns, telemedicine services, and real-time disease-tracking systems in Uganda. ¹² This rapid adoption, however, simultaneously exposed deep-seated systemic weaknesses, including significant infrastructure and equity gaps. For instance, disparities in smartphone ownership and internet connectivity meant that many rural and marginalised communities remained largely unreached by these digital interventions. Movement restrictions and lockdowns further impeded the work of field health workers, underscoring that data-driven tools alone cannot succeed without comprehensive and inclusive coverage.^13,14 The pandemic, therefore, acted as both an accelerant for innovation and a revealer of pre-existing vulnerabilities, making their resolution a matter of urgent national priority.

In recognition of these complex challenges and the lessons gleaned from the pandemic, Uganda's Ministry of Health (MoH) has undertaken significant policy advancements. In May 2023, the MoH officially launched its first National Health Information and Digital Health Strategic Plan (2023–2025). This ambitious plan explicitly commits to accelerating access to quality-assured data and institutionalising patient-level digital records at points of care by 2025. ¹⁵ Complementing this strategic blueprint, the MoH released a comprehensive Compendium of National Digital Health Guidelines in September 2024. These guidelines aim to standardise data management practices across the health sector, establishing common technical frameworks, including data standards, messaging protocols, and privacy safeguards, to ensure that diverse digital health projects can interoperate effectively. ¹⁶ While these policy documents represent a robust foundation, their effective execution remains a critical challenge, often hampered by resource constraints and organisational silos.

This article undertakes a comprehensive policy analysis of Uganda's evolving digital health governance framework with the specific objective of identifying gaps in inclusivity, interoperability, and accountability within existing policies and proposing feasible, evidence-informed reforms to address them. Rather than designing entirely new policy instruments, the analysis seeks to strengthen and refine existing structures to deliver equitable, rights-based digital health outcomes more effectively. The study, therefore, aims to bridge the gap between Uganda's current policy aspirations and their practical implementation through actionable, context-sensitive recommendations.

Methodology

This article employs a rigorous policy analysis approach to systematically examine the landscape of digital health data governance in Uganda. Health policy analysis is inherently a multidisciplinary field dedicated to elucidating the intricate interplay among institutions, various interest groups, and prevailing ideas within the policy process. This analytical lens is valuable for both retrospective understanding of past policy successes and failures and for prospective planning of future policy implementation. The present analysis broadly aligns with established frameworks in the field, such as Longest's four general elements of policymaking − policy formulation, implementation, evaluation, and modification. Furthermore, it incorporates insights from Walt and Gilson's policy triangle framework, which emphasises the critical interaction of policy content, the actors involved, the specific context in which policies operate, and the processes through which they are enacted. ¹⁷ This structured approach ensures that the examination extends beyond merely what policies state, to who is involved, where policies are applied, and how they are put into practice, providing a more holistic and nuanced understanding of the policy environment.

The foundational data for this analysis were derived from a comprehensive review of recent literature, with a particular emphasis on scholarly articles and reports about Uganda and the broader Sub-Saharan African region. A core component of the data collection involved a thorough examination of key official policy documents issued by the Ugandan government and its Ministry of Health. These included: Uganda's National Health Information and Digital Health Strategic Plan (2023–2025); the detailed Compendium of National Digital Health Guidelines (September 2024); Uganda's foundational Data Protection and Privacy Act (DPPA, 2019); and the draft eHealth regulations circulated in 2024.

Beyond formal policy documents, the analysis also incorporated information from significant conference reports and documented stakeholder input. This included the Report on the First Edition of the Uganda National Digital Health Conference held in November 2023, ¹⁸ which brought together diverse participants from government, academia, donors, and civil society. Additionally, insights from the Africa CDC workshop on health data governance, co-hosted by Uganda in February 2025, were considered. The inclusion of stakeholder input, as referenced in the development of the strategic plan and discussions at these conferences, was crucial. This approach acknowledges that policy analysis must be deliberative and interpretive, taking into account people's experiences, understandings, values, and beliefs as expressed through language and behavior.

The collected research material was systematically subjected to thematic analysis. This involved identifying recurring challenges, extracting pertinent lessons learned from Uganda's national experiences (particularly its response to the COVID-19 pandemic), and drawing on regional and global best practices. These findings were then synthesised into a coherent proposed framework and actionable policy recommendations. The methodology emphasised transparency and scholarly rigour throughout, ensuring that all observations and conclusions were firmly grounded in documented evidence and aligned with recognised policy analysis methodologies. This commitment to a structured and evidence-based approach underpins the credibility and utility of the report's findings.

Limitations

While this policy analysis adopts a rigorous and systematic approach, certain limitations must be acknowledged. The study primarily relied on secondary sources, including official government publications, policy documents and peer-reviewed literature, which may reflect institutional or political biases. The absence of extensive primary data also limits insight into lived experiences, particularly among marginalised groups. However, these limitations were mitigated through triangulation of diverse sources and comparison with regional and global best practices to strengthen validity and interpretive rigour.

Current policy landscape in Uganda

Uganda's journey toward digital health governance has evolved gradually over the past two decades. Early efforts in the late 1990s and early 2000s focused on strengthening the Health Management Information System (HMIS) to improve routine data reporting from public health facilities. ¹⁹ The introduction of the electronic HMIS (eHMIS) in the mid-2000s and the subsequent rollout of pilot projects such as EMRs in HIV clinics and the mTrac SMS-based reporting platform marked the country's first tangible steps towards digitalisation.^20,21 These early initiatives were largely donor-driven and programme-specific, implemented under vertical projects without a unifying national framework. ²² By the 2010s, Uganda began aligning with emerging global and regional digital-health agendas, participating in WHO and Africa CDC consultations on national eHealth strategies. However, the absence of a coherent governance structure led to what stakeholders termed ‘pilotitis’ − a proliferation of unintegrated, unsustainable digital health projects. ²³ The launch of the National Health information and Digital Health Strategic Plan (2023–2025) thus represents the culmination of this two decade evolution − from fragmented, donor-driven experimentation to a government-led effort to institutionalise comprehensive digital health governance (MOH, 2023) This historical trajectory underscores that Uganda's digital health governance has evolved not as a single policy event but as a continuous learning process shaped by both domestic experimentation and global policy diffusion.

The strategic plan articulates a clear commitment to strengthening governance for health information, scaling interoperable patient-level systems, and expanding the utilisation of data for planning purposes by 2025. The strategic plan's objectives directly address lessons from past fragmentation, emphasising the consolidation of investments, the establishment of national infrastructure, such as a HIE, and the democratisation of health data. ²⁴ To operationalise the ambitious goals outlined in the strategic plan, the MoH subsequently issued comprehensive technical guidelines. In September 2024, the Ministry released the ‘Compendium of the National Digital Health Guidelines, September 2024, Republic of Uganda, Ministry of Health’. ¹⁶ This extensive 10 MB document is meticulously aligned with Uganda's broader health sector strategies and lays down common technical frameworks. These include standardised data dictionaries, messaging formats, and interoperability profiles, all designed to ensure that new digital projects adhere to a unified architecture.

The compendium also incorporates robust data security and privacy protocols, mandating data encryption and consistent user authentication across systems. By codifying these rules, Uganda aims to prevent the recurrence of the fragmentation that plagued earlier efforts and to facilitate seamless data sharing across its diverse health systems. The compendium's detailed structure, covering Digital Health Standards, a Digital Health Enterprise Architecture Framework (DHEAF), a Digital Health Workforce Capacity Building Framework, and a Digital Health Monitoring and Evaluation Framework, signifies a sophisticated technical governance strategy that addresses not just policy but also the underlying technical and human infrastructure required for digital transformation. ¹⁶

On the legal front, Uganda's DPPA of 2019 provides a foundational statutory basis for safeguarding health information. Enacted on 1 March 2019, the Act broadly defines data and extends its applicability to all individuals, institutions, and public entities involved in processing personal data, whether within or outside Uganda. ²⁵ It confers essential rights to individuals, including the right to consent to, access, and correct their data. The Act mandates that consent be obtained for data collection, with specific exceptions for public duty or national security. It requires data controllers to implement stringent security measures and, under certain conditions, appoint Data Protection Officers (DPOs).

While the DPPA has been instrumental in promoting patient confidentiality, its enforcement in specific health settings is still in its early stages. ²⁶ In a significant step towards operationalising its general principles, draft eHealth regulations under this Act were circulated for public comment in 2024. These proposed regulations aim to introduce sector-specific rules for hospitals and laboratories, indicating a deliberate progression towards greater accountability and clarity in health data management. ²⁷ This development highlights the evolving nature of Uganda's legal framework, moving from broad legislation to detailed, practical regulations that address the unique complexities of health data management.

Stakeholder coordination has also shown marked improvement, a development exemplified by the inaugural Uganda National Digital Health Conference held in November 2023. ¹⁸ This significant event attracted hundreds of participants from various sectors, including government, academia, donor organisations, and civil society. The conference served as a platform to review progress, such as the expansion of telemedicine during the pandemic, and to collectively chart a future course. It underscored the importance of aligning all digital health efforts with the national strategy. It fostered a call for sustained collaboration among key partners, including the WHO, USAID, the World Bank, local NGOs, and universities. ¹⁸

Furthermore, Uganda's health leaders actively engaged in regional initiatives, co-hosting a February 2025 Africa CDC workshop on health data governance with counterparts from Ethiopia, Rwanda, and other African nations, signalling a commitment to peer learning and regional harmonisation. ²⁸ Development partners have played a crucial role in this landscape by providing technical assistance for interoperability projects and data literacy initiatives, thereby significantly strengthening local capacity in Uganda. ²⁰

In summary, Uganda has successfully established a robust policy toolkit for digital health, comprising strategic plans, technical standards, legal frameworks, and coordination mechanisms. This foundational infrastructure is stronger than ever before. The ongoing challenge lies in effectively translating these comprehensive policies into tangible action on the ground, ranging from upgrading facility connectivity to deeply embedding equity considerations, ensuring that the digital health revolution genuinely benefits all Ugandans. ²⁹

Challenges to inclusive digital health data governance

Despite the significant policy foundations laid, Uganda's aspiration for equitable health data governance faces several deeply interwoven and persistent barriers. These obstacles are not merely technical but also organisational, socio-cultural, and resource-driven, creating complex impediments to a truly inclusive digital health system.

A primary challenge is the pervasive fragmentation of systems and data silos across the health sector. Many health programs, particularly those supported by various NGOs or focused on specific disease control initiatives, continue to operate with standalone data systems. ³⁰ These systems often utilise separate patient identifiers, meaning that a patient's comprehensive health history − for example, their maternal health records and HIV status − may reside in disparate, unconnected databases. ³¹ Without a universal health identifier or mandated, seamless data sharing protocols, patient records do not automatically flow between these systems. This creates significant ‘blind spots’ for epidemiologists and policymakers, hindering a holistic view of public health trends and individual patient care. ³² This fragmentation contributes to what a Lancet commentary aptly describes as ‘health data poverty’ in Africa: despite a multitude of data sources, aggregated national health information remains incomplete and difficult to leverage effectively. ²³ The digital health landscape in Uganda is notably ‘plagued by problems with interoperability and sustainability’ due to this fragmentation and a discernible lack of integrated digital health solutions. This issue is partly attributable to the absence of clear policies on data interoperability and to a lack of a common, overarching objective across the entire data ecosystem. ³³ This situation illustrates how fragmentation and poor data quality are not isolated problems but rather mutually reinforcing, creating a detrimental cycle that undermines effective health management.

Compounding the issue of fragmentation are pervasive concerns about data quality and completeness. Incomplete records are common, with essential fields such as diagnoses and demographic details frequently left blank in clinic registries. ³⁴ Transcription errors are also prevalent, often arising when health workers, managing busy clinics, must manually enter data from paper records into digital systems. ³⁵ Furthermore, duplicate patient records proliferate when individuals register at multiple facilities under slightly different names, leading to fragmented longitudinal data and an inaccurate count of unique patients. ²² These data inaccuracies frequently stem from fundamental resource constraints. For instance, in areas with unreliable internet connectivity, data may initially be recorded on paper and uploaded later, increasing the risk of information loss or inaccuracies during the manual process. As a World Health Organisation report warned, low-quality datasets inevitably lead to ‘garbage in, garbage out’ analytics, severely undermining the reliability and utility of public health decision-making. ³⁵ Studies confirm that the limited use of health data in Uganda's healthcare system is directly influenced by factors such as the absence of standardised data formats and the poor quality of available data.^22,36

Another critical barrier is the limited representation and inclusion of all populations within digital health systems. Marginalised groups often have less frequent interaction with formal health channels, leading to their underrepresentation in collected data. This includes rural communities located far from health clinics, refugee populations, nomadic groups, and residents of urban slums. ³⁷ Social factors also play a significant role; for example, persons with disabilities may encounter substantial access barriers to clinics, resulting in their systemic omission from health records. ³⁸ A particularly illustrative example from Uganda highlights this issue: a disability advocacy group (DASUNS) successfully challenged national census figures by demonstrating that a more inclusive counting methodology raised the reported disability rate from 5.2% to 13.2%. ³⁹ This case powerfully demonstrates how biases embedded in data collection processes can lead to the systematic exclusion of entire demographic groups. If digital health systems similarly overlook these communities − perhaps by employing inaccessible interfaces or failing to disaggregate data by relevant social markers − these populations risk being left out of crucial health planning and resource allocation, perpetuating existing inequities. The inconsistency in reported disability prevalence rates across different surveys, ranging from 11.7% to 19%, further underscores the unreliability of current data for vulnerable populations, highlighting an urgent need for standardised and inclusive data collection methods. ⁴⁰ This problem extends beyond mere statistics; it represents a fundamental issue of social justice, where flawed data collection directly contributes to inadequate resource allocation and continued marginalisation.

Privacy, trust, and security constitute another non-negotiable challenge. Protecting patient privacy is not only an ethical imperative but also a practical concern, as a lack of public trust in how their information will be handled can lead citizens to withhold sensitive data or avoid seeking services altogether. ⁹ While Uganda's DPPA (2019) formally grants individuals rights over their data, public awareness of these rights remains limited. Reports or rumours of data misuse, or actual security breaches, can rapidly erode public confidence. ⁴¹ The threat of cyberattacks is escalating globally, and African health systems have increasingly become targets for ransomware attacks that compromise data access and integrity. For instance, the South African National Health Laboratory Services (NHLS) experienced a significant ransomware attack in June 2024, resulting in the theft of 1.2 terabytes of sensitive patient data and substantial disruption to patient services. ⁴² This incident underscores the critical need for robust safeguards and transparent practices to assure public trust. Without strong security measures and clear communication, trust in digital health systems cannot be guaranteed. Impediments to accessing patient data in Uganda include insufficient security and privacy measures and weak eHealth governance. ⁹ This demonstrates that cybersecurity is not just a technical problem but a foundational issue of trust, with direct implications for patient safety and system adoption.

Finally, capacity and resource constraints pose a significant hurdle, as the ambitious vision for digital transformation often clashes with realities on the ground. Uganda faces a notable shortage of trained health informatics professionals and data analysts, who are essential to managing and interpreting complex digital health systems. ⁴³ In many clinics, computer availability is severely limited (e.g., one computer for dozens of staff), and there are few technicians available to maintain these systems. ⁴³ Training for health workers on new digital tools has been inconsistent and unevenly distributed. ³⁵ Furthermore, funding for digital health initiatives frequently relies on short-term donor grants rather than stable, long-term domestic budgets. When project-specific funds conclude, systems can fall into disrepair due to a lack of sustained financial support. Basic infrastructure remains a challenge in many parts of the country, with numerous rural clinics struggling with unreliable electricity and limited internet connectivity, making it difficult to run even simple digital applications. ²⁰ This highlights that effective governance must be complemented by substantial and sustained investments in both human capital and physical infrastructure. The need to contextualise international standards for digital health communication infrastructure is also apparent, as high-end specifications may not be achievable in low-resourced settings like Uganda due to intermittent internet connectivity and low data rates (Table 1).

Table 1.

Summary of challenges to inclusive digital health data governance in Uganda.

Challenge category	Specific manifestations in Uganda	Underlying causes	Consequences/impact
Fragmented systems and data silos	Standalone NGO/disease-specific databases; separate patient identifiers; no automatic flow of records. 44	Lack of universal health identifier, absence of clear data interoperability policies, and independent funding structures.	‘Blind spots’ for epidemiologists/policymakers, including ‘health data poverty’ and incomplete national health information, hinder a holistic view of patients.
Data quality and completeness	Incomplete records (missing data); transcription errors from manual entry; duplicate patient records. 45	Resource constraints (unreliable internet, forcing paper-based entry), busy clinics, and a lack of standardised data formats.	‘Garbage in, garbage out’ analytics undermines public health decision-making, leading to unreliable data for planning.
Limited representation and inclusion	Underrepresentation of rural, refugee, nomadic, and urban slum dwellers; access barriers for persons with disabilities. 46	Biases in data collection, inaccessible interfaces, failure to disaggregate data, and inconsistent reporting of disability prevalence.	Systematic exclusion from planning/resource allocation; perpetuates inequities; disability rate underestimated (e.g., 5.2% vs. 13.2% by DASUNS).
Privacy, trust, and security	Limited public awareness of data rights; rumours/real breaches; rising cyber threats (ransomware attacks). 47	Insufficient security/privacy measures; weak eHealth governance; rapid digitisation outpacing cybersecurity infrastructure.	Erosion of public trust; citizens withhold data/avoid services; disruption of critical health systems (e.g., NHLS attack); ethical concerns.
Capacity and resource constraints	Shortage of trained health informatics professionals/data analysts; limited computers/technicians; uneven staff training. 48	Reliance on short-term donor grants; unstable domestic budgets; inadequate basic infrastructure (electricity, internet) in rural areas.	Systems fall into disrepair, hindering effective digital transformation, limiting the adoption/sustainability of digital tools, and making it difficult to contextualise international standards.

Lessons from the COVID-19 pandemic

The COVID-19 pandemic provided Uganda with an unprecedented, real-time ‘stress test’ for its digital health systems, revealing both the strengths and profound weaknesses within its infrastructure and governance. ¹² The crisis acted as a powerful catalyst, accelerating digital transformation efforts that might otherwise have taken years to materialise.

One of the most significant lessons was the accelerated adoption of digital health under emergency conditions. The Ministry of Health rapidly scaled up its digital surveillance capabilities, leveraging the District Health Information System 2 (DHIS2) to collect case data and track infection trends and resource utilisation daily. ⁴⁹ Mobile networks became a critical channel for disseminating health advisories to millions of people nationwide. ¹² Furthermore, some districts swiftly piloted telemedicine solutions to ensure continuity of chronic care follow-ups when physical clinics were forced to close. This period witnessed a ‘prominence and unprecedented rise in the use of digital health technologies’ for delivering health information and services remotely, including tele-consultation and mobile phone-based information dissemination. The emergency context effectively legitimised digital tools and fast-tracked bureaucratic approvals for new technology projects, demonstrating Uganda's inherent capacity to deploy a wide array of eHealth innovations rapidly when under pressure. ¹⁴ For example, the Smart Health app, utilised by Community Health Workers (CHWs) through organisations like Living Goods, was quickly adapted to provide critical health services and COVID-19-specific messaging, an adaptation estimated to have saved thousands of lives. ⁵⁰ This period showed that external shocks can bypass traditional bureaucratic inertia, forcing rapid digital transformation and revealing the actual state of existing systems.

Despite this rapid adoption, the pandemic sharply exposed pre-existing equity and infrastructure gaps. The benefits of digital health were not uniformly distributed. Uneven smartphone ownership and inconsistent internet connectivity meant that digital tools could not effectively reach a significant portion of rural and marginalised communities. Movement restrictions and lockdowns severely hampered the work of field health workers, underscoring that digital tools alone are insufficient without inclusive coverage and robust human support. Qualitative studies of frontline health workers in Uganda and neighbouring countries confirmed that poor connectivity severely impeded their pandemic response efforts. ¹² Conversely, areas that had already invested in CHW connectivity demonstrated greater resilience, with routine services such as immunisations and antenatal visits experiencing less disruption. ⁵⁰ This experience underscored the critical imperative of equipping CHWs and peripheral health staff with reliable digital tools and comprehensive training, recognising these as non-optional components for health system resilience. The pandemic also highlighted the lack of adequate data infrastructure to identify eligible individuals and ensure follow-up for vaccination campaigns effectively. ⁵¹ This amplification of the ‘last mile’ challenge demonstrated that digital tools are only as effective as their reach, emphasising the persistent digital divide and the crucial role of human intermediaries.

A significant lesson emerged regarding the importance of interoperability under crisis conditions. The fragmentation inherent in Uganda's existing health systems became acutely costly when COVID-19 cases surged. ³⁰ Health leaders observed in early 2020 that even the country's relatively mature surveillance systems functioned as ‘isolated repositories’. ⁵² A practical consequence was the manual reporting of laboratory test results for COVID-19 to clinical units, which significantly slowed the identification of hotspots and delayed public health responses. ¹² In response to this urgent need, the government redoubled its efforts to link disparate systems. By mid-2021, the DHIS2 platform was enhanced to import data directly from laboratory information systems and vaccine registries, enabling more integrated, real-time outbreak tracking. ⁴⁹ The sheer urgency of the pandemic effectively pushed the interoperability agenda forward at a pace that would have been unachievable during peacetime.

Finally, the pandemic significantly influenced public attitudes toward data and privacy. In the face of an emergency, Uganda adopted pragmatic measures, such as mandatory case reporting linked to mobile numbers. ⁵³ However, these measures also heightened public awareness and sparked essential debates about data rights. Civil society organisations began to demand greater transparency, as citizens increasingly wanted to understand how their sensitive information, particularly their infection status, would be used. ⁵⁴ This shift in public sentiment indicated that future digital health tools would necessitate transparent consent processes and robust communication strategies to maintain public trust. Public concerns regarding vaccine safety and the proliferation of misinformation further underscore the critical need for credible information dissemination. ⁵⁴ This period marked an evolution in the social contract of data, transforming data collection from a purely technical exercise into a matter of public trust and fundamental rights.

In summary, the pandemic experience provided Uganda with an intensive ‘crash course’ in digital health. It unequivocally demonstrated that technology can be a powerful ally during a crisis, but only if foundational governance, infrastructure, and social considerations are robust. Ugandan policymakers now return from this crisis with a dual understanding: the imperative to embrace data-driven innovation, coupled with the equally vital need to ensure that such innovation is deployed equitably and inclusively from the outset (Table 2).

Table 2.

Digital health tools and initiatives leveraged during COVID-19 in Uganda.

Digital tool/initiative	Key functionality during COVID-19	Impact/outcome	Associated challenges/limitations	Source
DHIS2 (District Health Information System 2)	Rapidly scaled digital surveillance, case data reporting, and national dashboards for tracking infection trends and resource use. Enhanced to import lab and vaccine data by mid-2021.	Enabled real-time outbreak tracking and data-driven decision-making; improved completeness and timeliness of monthly OPD reports in most districts.	Initially, it functioned as ‘isolated repositories’, which slowed hotspot identification, led to data quality issues (incomplete, untimely, inaccurate) at the facility level, and did not provide individual-level data for tracking.	55
Mobile Networks/SMS-based systems (e.g., mTrac)	Sent health advisories to millions; SMS-based reporting of suspected cases to DHIS2 in limited internet areas.	Facilitated mass public awareness campaigns; enabled basic data submission from remote regions.	Uneven smartphone ownership and connectivity limit access for rural/marginalised communities.	56
Telemedicine/Tele-consultation	Piloted for chronic care follow-ups; remote consultations via voice, chat, video platforms; telepsychiatry.	Maintained some continuity of care when clinics closed; helped patient triage and reduced facility congestion; addressed mental health needs.	Uneven smartphone ownership/connectivity; limited access for vulnerable groups; reliance on existing private/donor-funded initiatives.	57
Smart Health App (Living Goods CHW program)	Guided Community Health Workers (CHWs) for routine diagnostics, care protocols (pregnancy, childhood diseases, nutrition, immunisation), and COVID-19 messaging.	Enabled CHWs to provide services with minimal interruption; adapted for no-touch workflows, remote supervision; saved thousands of lives.	Effectiveness is tied to existing CHW connectivity/training, highlighting the ‘last mile’ challenge where digital tools need human infrastructure.	58
General Digital Health Tools (various)	Online information campaigns, real-time disease tracking, and fast-tracked approvals for new tech projects.	Demonstrated potential of technology in crisis; accelerated bureaucracy and innovation.	Exposed underlying infrastructure and equity gaps; poor connectivity hampered frontline workers; lack of adequate data infrastructure for follow-up (e.g., vaccine doses).	56

Regional and global best practices

Uganda's ongoing reform efforts in digital health data governance can significantly benefit from a rich body of African best practices from peer countries that have achieved notable progress in similar contexts. Kenya and South Africa, in particular, provide valuable benchmarks − the former for its participatory governance structures and the latter for its advanced technical interoperability standards. ⁵⁹ These, alongside broader continental and global best practices, offer concrete guidance for building inclusive and equitable data systems that balance innovation, local ownership, and accountability. Several common themes consistently emerge across successful models, providing valuable advice for creating inclusive and equitable data systems.

A fundamental principle is human-centred governance, which posits that data systems should be designed ‘with, by, and for people’, rather than merely existing about them. ⁶⁰ True inclusivity begins with actively identifying and engaging those who have historically been excluded. This is a core tenet underscored by initiatives such as the Digital Impact Alliance's Africa Data Leadership Initiative, which emphasises that ‘missing voices must be heard at every governance stage’. ²⁶ In practical terms, this translates to actively involving community representatives in decision-making bodies. For instance, Kenya's digital health forum allocates seats for non-governmental organisations (NGOs) and clinicians. ⁶⁰ Establishing similar participatory structures in Uganda would ensure that diverse perspectives genuinely shape policies and that digital tools are developed to meet the real needs of all populations, fostering greater ownership and utility.

There is a growing global emphasis on equity and decolonisation in data governance. This movement actively warns against ‘data colonialism’, a phenomenon in which data extracted from low-income contexts are disproportionately used to serve the interests of wealthy stakeholders in high-income countries. ⁶¹ The call is for equitable data practices that deeply respect cultural realities and local contexts. Reflecting this critical shift, the African Union's Data Policy Framework (2022) explicitly designates health data as a special category, necessitating rigorous protection and robust local governance. It strongly urges member states to enact comprehensive personal data protection laws and to tailor regulations to specific sectoral needs. ⁶² The overarching lesson here is the imperative to assert local ownership of data, ensuring that the benefits derived from data − including insights, products, and investments − flow back directly to the communities that generated them. Furthermore, systems must be designed to address historical inequities rather than inadvertently perpetuate them. ⁶³ This includes a strong emphasis on supporting African-led artificial intelligence (AI) solutions and investing in local computational infrastructure, thereby fostering self-reliance and equitable development.

Effective digital health governance also relies heavily on multistakeholder collaboration. Successful programs consistently leverage partnerships across various sectors. In many African countries, digital health governance is strategically placed under inter-agency committees or national eHealth councils. These bodies bring together a diverse array of actors, including ministries of health, information and communication technology (ICT) authorities, donor agencies, private technology firms, and civil society organisations. ⁶⁴ A notable example is Ghana's Data Protection Commission, which formed a dedicated health data working group comprising doctors and patients to draft guidelines for hospital records collaboratively. ⁶⁵ Such broad-based collaborations are instrumental in aligning disparate efforts, pooling financial resources, and crucially, preventing the duplication of initiatives − a known issue in Uganda's past, characterised by numerous isolated pilots.

On the technical front, there is a strong global consensus on adopting data standardisation and interoperability. Leading health systems worldwide now mandate the use of open standards for data exchange, such as HL7 FHIR (Fast Healthcare Interoperability Resources) for clinical information, alongside standardised coding systems like ICD (International Classification of Diseases), SNOMED (Systematised Nomenclature of Medicine), and LOINC (Logical Observation Identifiers Names and Codes).^66,67 An expert review of Uganda's specific needs has highlighted that these global standards provide a ‘common language’ that is indispensable for effective healthcare information sharing. ³⁰ Practical implementations of this principle are evident across the continent: South Africa's national health data repository, for instance, utilises FHIR to seamlessly pull data from its various provinces. ⁶⁸ Kenya has developed an interoperability layer that enables linking HIV and maternal health records. ⁶⁹ Uganda's own 2024 guidelines already reference these international standards, indicating an alignment with this crucial best practice. This emphasis on a ‘common language’ for data is not merely a technical requirement but a fundamental facilitator of broader collaboration and enhanced data utility.

Inclusivity and accessibility are paramount for digital health solutions to achieve widespread impact. Technologies must be designed to accommodate diverse user abilities and linguistic backgrounds. ⁷⁰ In the African context, a maternal health messaging service in Zambia successfully sends voice prompts in local tongues, effectively overcoming literacy barriers and expanding its reach. ⁷⁰ The clear lesson is that embedding inclusivity into the design phase of digital health tools significantly broadens their reach and effectiveness, directly impacting adoption and overall utility.

Finally, transparency and accountability mechanisms are indispensable for fostering trust and ensuring responsible data governance. Progressive governments consistently publish aggregated health data and progress reports on their digital strategies online, enabling researchers and citizens to monitor trends, identify gaps, and raise concerns. ⁷¹ Civil society organisations in several countries actively monitor digital health projects, providing an external layer of scrutiny. ⁷² Uganda can effectively emulate these best practices by regularly publishing aggregate health indicators (while strictly safeguarding personal identifiers) and digital health metrics. Crucially, establishing accessible channels for people to contest or question data use is vital, ensuring that accountability is not merely theoretical but practically enforceable. This ensures that even well-intended systems do not inadvertently replicate injustices in the absence of formal accountability mechanisms.

By synthesising these diverse experiences − especially Kenya's inclusive governance model and South Africa's FHIR-based interoperability framework − it becomes evident that Uganda's reforms are aligned with continental momentum toward people-centred digital transformation. Kenya demonstrates how participatory decision-making fosters legitimacy and shared ownership, while South Africa exemplifies the impact of enforcing open technical standards. Uganda's emerging framework now stands to integrate these dual lessons: strengthening participatory governance and accelerating technical standardisation. As an Africa CDC analysis succinctly captures this vision: when data-driven approaches are built upon principles of equity, dignity, and ethical governance, they possess the transformative power to ‘ensure the most disadvantaged communities have access to quality care, leaving no one behind’.^28,73 Uganda's reform efforts should therefore strive to fulfil this profound promise, learning from its peers while meticulously adapting these best practices to its unique local realities.

A proposed inclusive data governance framework

Guided by Uganda's specific context, the challenges identified, and lessons from the COVID-19 pandemic and international best practices, a comprehensive framework for inclusive digital health data governance is proposed. This framework is structured around five interlocking pillars, each addressing critical dimensions of governance, technology, and equity, and is designed to be mutually supportive.

Pillar 1: inclusive governance and stakeholder engagement

Uganda must institutionalise participatory data governance to ensure that digital health initiatives are genuinely responsive to the needs of all its citizens. A permanent digital health council, as already envisioned in the nation's strategic plan, is essential. This council must be broadly representative, extending beyond government officials and technocrats to include active representatives from rural communities, diverse patient advocacy groups (including women's organisations and disability networks), local government leaders, and technical experts. ⁶⁴ A concrete mechanism for formalising community voices could involve enabling village health team members to elect delegates to district health boards, thereby creating direct channels for grassroots input. Transparency in decision-making processes is paramount; meeting minutes and policy documents should be publicly accessible, and citizens must have clear, accessible mechanisms, such as hotlines or web portals, to question data use and raise concerns. ⁷² Furthermore, establishing dedicated data stewardship roles at the district level would serve to train local staff and facilitate direct liaison with communities, ensuring that digital health investments are genuinely aligned with the needs of all demographic groups, not merely the most vocal or influential stakeholders.

Pillar 2: equity and decolonisation

Every proposed reform within Uganda's digital health landscape must be rigorously filtered through an equity lens. This necessitates conducting regular ‘data equity audits’ to systematically identify populations currently undercounted or underserved in existing data systems. ⁷⁴ Should these audits reveal significant gaps − for instance, poor data coverage for certain ethnic groups or remote regions − targeted interventions must be swiftly implemented. These could include additional funding for health centres in those areas, deployment of mobile clinics, or the development of language-tailored outreach programs. ⁷⁵ Policy frameworks must explicitly allocate resources to address these identified disparities. From a regulatory standpoint, data retention guidelines and data sharing policies should be crafted to prioritise local benefit. This means requiring that any international collaboration involving Ugandan health data include explicit provisions for Ugandan leadership in data analysis, interpretation, and publication. ⁶³ This approach directly counters the dynamics of data colonialism, ensuring that the insights and innovations derived from Ugandan data primarily serve the health and well-being of Ugandan communities. This operationalisation of decolonisation through concrete policy mechanisms is vital for equitable data governance.

Pillar 3: standardisation and interoperability

From a technical standpoint, establishing a unified data architecture is critical to Uganda's digital health future. The Compendium of National Digital Health Guidelines, released in 2024, should be strictly enforced, mandating that any new health software − whether developed locally or introduced through donor projects − adheres to the prescribed international standards, including ICD-11, SNOMED, LOINC, and HL7 FHIR, and fully conforms to the national interoperability framework. ⁶⁷ The Ministry of Health must accelerate the development and rollout of a national HIE platform. This HIE would serve as the central nervous system, connecting disparate EMRs, laboratory information systems, pharmacy databases, and the DHIS2, thereby enabling a seamless, automatic flow of patient data across different healthcare facilities. ³³ To foster research and innovation, Uganda should proactively adopt FAIR data principles (Findable, Accessible, Interoperable, and Reusable). This involves publishing metadata about datasets, making anonymised aggregate data discoverable through a central catalogue, accessible via clear data use agreements, and reusable with transparent licensing terms. ³⁰ By ensuring robust interoperability and data portability, Uganda can maximise the utility of every piece of health data while significantly reducing duplicated efforts across the system.

Pillar 4: privacy, security, and legal enforcement

The protection of patient data is a non-negotiable cornerstone of this framework. Uganda should establish a dedicated Chief Health Data Officer role within the Ministry of Health or the Data Protection Commission. This officer would be responsible for overseeing comprehensive compliance with the 2019 DPPA within the health sector. Their duties would include auditing hospitals and laboratories to ensure the effective implementation of data encryption, stringent access controls, and robust breach notification protocols. Critically, any new digital health tool proposed for deployment must undergo a thorough privacy impact assessment (DPIA) before implementation. This assessment should ensure that the tool collects only the minimum necessary data and obtains explicit, informed consent from users, provided in local languages where appropriate. Ongoing training for health workers is also vital, ensuring staff fully understand confidentiality rules, such as never sharing passwords and securing computer systems when unattended. Legislatively, Uganda should clarify data retention rules (e.g., defining periods for deleting or archiving old records) and establish clear conditions for data sharing. If data are to be shared regionally, binding agreements must be in place to ensure that Ugandan privacy law continues to apply and that data usage is strictly limited to agreed public health purposes. ⁷⁶ This pillar directly addresses the implementation gap in privacy by moving from policy to practical enforcement mechanisms.

Pillar 5: capacity building and infrastructure

The successful implementation of this framework fundamentally rests on robust human and physical infrastructure. Uganda must significantly scale up its health informatics training programs. This includes introducing specialised courses and certification programs at universities and integrating modules on data use and ethics into existing public health curricula. ⁴³ A ‘train-the-trainer’ approach can effectively equip district health officers to mentor and support local staff, thereby creating a sustainable learning ecosystem across the country. On the public side, widespread digital literacy campaigns are necessary. Community health clubs and local media can play a crucial role in explaining, in an accessible language, how digital records can improve care and what rights patients possess regarding their data. ⁷⁷ Physical infrastructure must also be substantially bolstered. The government should prioritise upgrading electricity and internet connectivity in health clinics, with a particular focus on remote centres where solar backup solutions can ensure reliability. ²⁰ Partnerships with telecommunications providers can be leveraged to extend mobile network coverage and subsidise data costs for health workers, recognising that a strong telecommunications backbone is a fundamental prerequisite for the success of all other governance reforms.

These five pillars are intricately interconnected and mutually reinforcing. For example, the effective implementation of strong interoperability standards (Pillar 3) is dependent on adequately trained personnel (Pillar 5). Similarly, inclusive governance structures (Pillar 1) are essential for guiding equitable resource allocation (Pillar 2). The framework is designed to be operationalised iteratively, allowing Uganda to achieve quick gains − such as formalising participatory committees and strengthening privacy policies − while simultaneously building the long-term capacity required for more complex initiatives, such as the nationwide HIE rollout. Critically, this framework embodies a decolonised ethos by emphasising local ownership, cultural context, and social justice as central tenets of digital health transformation ⁷⁸ (Figure 1 and Table 3).

Figure 1.

Proposed five-pillar framework for equitable and decolonised digital health data governance.

Table 3.

Proposed inclusive data governance framework pillars and key actions.

Framework pillar	Core principle	Key actions/strategies	Expected outcome
1. Inclusive Governance and Stakeholder Engagement	Data systems are designed ‘with, by, and for people’, ensuring all voices are heard.	Establish a permanent digital health council with diverse representation (rural communities, patient advocates, local government, technical experts). Formalise community voice channels (e.g., elected delegates to district boards). Ensure transparent decision-making (public minutes, citizen feedback mechanisms). Establish district-level data stewardship roles.	Digital health investments align with diverse community needs, increased public trust and ownership, and multi-stakeholder accountability.
2. Equity and decolonisation	Data practices respect cultural realities, prioritise local benefit, and address historical inequities.	Conduct regular ‘data equity audits’ to identify undercounted/underserved populations. Implement targeted interventions (funding, mobile clinics, language-tailored outreach) for identified gaps. Require Ugandan leadership in analysis/publication for international data collaborations.	Data systems actively reduce health disparities; insights and innovations primarily serve Ugandan communities; counter data colonialism.
3. Standardisation and interoperability	Unified data architecture for seamless data flow and maximum utility.	Strictly enforce 2024 guidelines for new health software (ICD-11, SNOMED, LOINC, HL7 FHIR). Accelerate national Health Information Exchange (HIE) development. Adopt FAIR data principles (Findable, Accessible, Interoperable, Reusable) for research.	Reduced data fragmentation and duplication; improved data utility for patient care, planning, and research; efficient information sharing across facilities.
4. Privacy, security, and legal enforcement	Non-negotiable protection of patient data and robust legal compliance.	Designate a Chief Health Data Officer within the MoH/DPC to oversee health sector compliance. Mandate Privacy Impact Assessments (DPIA) for all new digital health tools. Ensure explicit informed consent in local languages. Provide comprehensive training for health workers on confidentiality. Clarify data retention rules and cross-border sharing conditions.	Increased public trust in digital health systems, reduced data breaches and misuse, strong legal safeguards for patient rights, and ethical data handling.
5. Capacity building and infrastructure	Substantial human capital and physical infrastructure underpin all reforms.	Significantly scale up health informatics training (university courses, public health curricula). Implement a ‘train-the-trainer’ approach for district staff. Launch public digital literacy campaigns. Upgrade clinic electricity and internet (prioritise solar backup) − partner with telecom providers for coverage/subsidised data for health workers.	Skilled digital health workforce; digitally literate public; reliable and accessible digital infrastructure, especially in rural areas.

Potential implementation barriers

While the proposed five-pillar framework provides a feasible pathway towards equitable and decolonised health data governance, its implementation will require overcoming several structural obstacles. Politically, Uganda's digital health agenda is influenced by competing sectoral priorities, fragmented institutional mandates, and periodic leadership changes that can hinder long-term reform efforts. Financially, sustained investment remains difficult, as most digital health initiatives depend heavily on donor funding, raising concerns about continuity once external support decreases. Operationally, the chronic shortage of specialised health informatics personnel, weak procurement and maintenance systems, and ongoing infrastructure gaps − particularly electricity and broadband connectivity in rural districts − pose significant challenges. Lastly, social factors such as low public awareness of data rights, limited digital literacy, and historical mistrust of government data systems can undermine adoption and participation. Recognising and planning for these barriers is crucial to ensuring the framework moves beyond policy aspiration into practical, scalable, and context-appropriate implementation.

Policy recommendations

This analysis reveals a critical juncture in Uganda's digital health evolution, where policy must intentionally pivot toward inclusive, equitable, and decolonised data governance. While the existing policy landscape provides a foundation, execution must prioritise action that translates policy goals into tangible, rights-based outcomes. The following five recommendations represent the highest-priority, actionable interventions required to safeguard public trust, drive equity, and realise the full potential of digital health data for Universal Health Coverage (UHC).

Establish a multi-stakeholder digital health data council

The fragmentation of governance and lack of unified oversight must be addressed immediately. We recommend establishing an independent, high-level Digital Health Data Council to oversee all major digital health policy decisions, align digital health strategy, and enforce data standards. This Council's composition must be diverse, including representatives from the Ministry of Health (MoH), the National IT Authority (NITA-U), civil society organisations, patient advocacy groups, ethical data experts, technology developers, and private sector providers. The central goal is to decentralise decision-making power from a purely government-led silo and ensure that policy is informed by the lived experiences and needs of the diverse communities it serves.

Mandate data equity impact assessments (DEIAs)

To prevent new systems from perpetuating or exacerbating existing health inequities, a proactive assessment framework is essential. The MoH must mandate a Data Equity Impact Assessment (DEIA) as a compulsory stage for the deployment of any new digital health system, software, or data collection initiative (e.g., EMRs, mobile health apps, and data dashboards). The DEIA should rigorously evaluate how the proposed system will affect vulnerable, marginalised, and geographically isolated populations (e.g., assessing language barriers, digital literacy requirements, and resource availability). This action aims to ensure that digital health initiatives are designed by default to be inclusive, accessible, and non-discriminatory, thereby actively reducing the risk of digital exclusion.

Implement mandatory national health data exchange standards

System fragmentation is the single greatest obstacle to efficient, patient-centred care and national data analysis. The MoH and NITA-U must jointly adopt and enforce a mandatory, open-source national data dictionary and technical standards (e.g., standards based on Fast Healthcare Interoperability Resources [FHIR]). Compliance with these standards must be a strict requirement for all public and private health facilities and vendors contracting with the government before deployment or integration into the national system. The overarching goal is to create a genuinely seamless National Health Information Exchange (NHIE) that enables safe, standardised, and real-time data flow across different health systems, thereby improving diagnostics, continuity of care, and outbreak response.

Enforce a context-specific digital health data protection framework

While the National Data Protection Act exists, digital health data requires sector-specific, enhanced safeguards due to its sensitive nature. This necessitates the development and enforcement of clear Guidelines for Health Data Consent, Use, and Retention that clarify the context-specific application of the national law, including the creation of user-friendly, layered consent models that patients with varying literacy levels easily understand. Furthermore, mechanisms for independent data audits must be strengthened, and significant penalties must be introduced for data breaches or unauthorised data sales by private or public entities. The ultimate goal is to build public trust in digital systems by guaranteeing the security and confidentiality of personal health information and empowering patients with clear rights over their data.

Launch a national digital health data literacy program

Insufficient user capacity and a lack of public understanding of data rights undermine system quality and public engagement. Therefore, we recommend implementing a two-pronged national literacy program. The first prong involves establishing mandatory, continuous training for all frontline health workers and administrators on ethical data practices, robust data quality assurance, and the proper use of systems. The second involves launching targeted public awareness campaigns to educate citizens, especially in local languages, about their digital data rights, how their health data is used, and how to report misuse. This comprehensive program is intended to professionalise data handling across the health sector and create an informed citizenry that can demand accountability and actively participate in data governance dialogues.

Implementation priorities and timelines

To guide implementation, the proposed reforms can be categorised by timeframe and feasibility. The five key policy recommendations naturally fall into a phased approach; short-term priorities (1–2 years) must focus on securing the governance and foundational elements of the reform agenda. These include establishing the Multi-Stakeholder Digital Health Data Council, enforcing national health data exchange standards for all new systems, and developing the sector-specific Digital Health Data Protection Framework and Guidelines (focused on consent and audit mechanisms). These actions secure early wins in governance, interoperability, and privacy.

Medium to long-term priorities (3–5 years and beyond) involve institutionalising the cultural and operational shifts required for sustained change. These priorities include mandating and integrating DEIAs into system procurement cycles, fully scaling digital infrastructure and the national Health Exchange across all health facilities, and launching and institutionalising the comprehensive National Digital Health Data Literacy Program (for both workforce capacity and public awareness). Sequencing reforms in this way enables policymakers to secure early wins while building the foundations for sustained digital transformation.

By pursuing these actions in a coordinated, parallel manner, Uganda can ensure that its policies, funding, and on-the-ground practices are aligned to achieve truly inclusive data governance. Sustained political commitment, transcending electoral cycles, will be essential for success. Experience from other countries demonstrates that initial momentum can dissipate without continuous leadership; therefore, building cross-party consensus on the value of equitable eHealth is highly advisable. Furthermore, Uganda's reforms should be harmonised with broader regional commitments, such as the Africa CDC's 2023 flagship initiative on health data governance, to amplify impact and foster collective regional advancement.

Conclusion

Uganda stands at a pivotal juncture in the evolution of its health sector. The rapid and widespread adoption of digital technologies during the unprecedented challenges of the COVID-19 pandemic unequivocally demonstrated their profound potential to save lives and significantly improve healthcare delivery. Yet, this period also starkly revealed how pre-existing governance gaps could exacerbate existing inequities, highlighting that technological advancement alone is insufficient without robust foundational structures. As this analysis has shown, Uganda has, in recent years, established a strong strategic foundation for digital health, marked by the introduction of new plans, comprehensive laws, and standardised guidelines.

The central challenge now lies in translating this ambitious vision into a tangible reality by deeply embedding principles of inclusivity and equity into every policy, system, and practice. Without this deliberate integration, digital health initiatives risk inadvertently reinforcing existing disparities rather than effectively alleviating them. The proposed reforms are anchored in a simple yet profound premise: health data must serve the people who generate them, rather than the other way around. Achieving this requires a fundamental reimagining of power structures, alongside technological advancements. As global advocates emphasise, truly inclusive data governance ‘begins with recognising whose voices have been missing’ from the discourse and design. Suppose Uganda successfully enacts multi-stakeholder governance, fosters community-driven design principles, implements robust privacy protections, and integrates deliberate equity measures. In that case, its digital health system has the potential to become a powerful catalyst for broader social transformation and a benchmark for other countries in the region. Such a system would not only enhance efficiency but also cultivate public trust and genuinely empower its citizens.

To underscore the profound human stakes embedded within this technological and policy endeavour, it is vital to remember what health data truly represents. As an African health informatics expert eloquently stated, ‘Health data is not some random characters or numbers… it is the record of real people, and their real experiences navigating various health statuses… We should treat health data, and every use we make of it, with respect and dignity’. By embedding this fundamental ethic into its digital health strategy and systems, Uganda can ensure that its technological progress translates directly into genuine human progress. The transformative promise of digital health − to reach the unreached, to close persistent gaps, and ultimately, to achieve health justice − is well within reach if data are governed with wisdom, fairness, and a profound respect for the individuals they represent. Implementing the comprehensive reforms outlined in this analysis will be instrumental in helping Uganda seize this promise.