Digital public goods: understanding the role of generativity in fostering digital innovation for development

Background: District Health Information Software 2 (DHIS2) is an open source, web-based, health management information system (HMIS) recognized as world's largest HMIS platform, customized for health information system of Bangladesh for decentralized data entry since 2011. Health care managers and employees should be well informed about the health information system for accurate, appropriate, precise, timely, valid information and also interpretation of information which are the basis for policy planning and decision-making at various levels of the organization. The study aimed at exploring the limitations of DHIS2 in decision making process for health service management among the Upazila (Sub district) level health managers of Bangladesh. Methods: The cross sectional study was conducted among the Upazila Health and Family Planning Officers (UH&FPOs) of Bangladesh during the period of January to December 2018. All (482) UH&FPOs of Bangladesh posted as regular, current charge or in-charge were included for the study. Data were collected by a pre-tested semi-structured email-based questionnaire. Results: Response rate was 88.8% (428 out of 482). The mean age of the respondents was 47.08 (±6.33 SD). Mean duration of job experiences as UH&FPO was 1.9 years (±1.635 SD). Regarding limitation, the study revealed that 76.2% (of 424) UH&FPOs think that lack of rrealizing the Importance of DHIS2 by Doctors, Nurses and other Staffs is the most important “Facility Centered Barriers” for using DHIS2 as a decision support tool of Upazila health service management. Beside this 71.2% UH&FPOs think that lack of effective training of the staffs concerned with DHIS2 operation are the second most important barrier. The study also revealed that 59.7% (of 402) UH&FPOs think that absence of the option for automatically displaying the summary reports of various datasets in the respective Upazila dashboard is the most important “Software Centered Barriers” for using DHIS2 as a decision support tool of Upazila health service management beside this 58.5% UH&FPOs think difficulties in identifying the management related data elements from various data sets of DHIS2. Conclusion: So, this study recommends scaling up DHIS2 by redesigning training programs with more focus on the ways of its’ application in the decision making process, create awareness among all categories of health staffs, customization of its contents and more research on this ground. These initiatives will explore several innovative approaches to monitor health indicators by DHIS2, measure and plan health interventions to ensure quality health service and will lead towards achieving Sustainable Development Goal 3 (SDG-3). JOPSOM 2023; 42(2): 43-50

BackgroundThe District Health Information Software 2 (DHIS2) is the primary digital platform for health management information systems (HMIS) in Ethiopia, aligning with the nation’s digitization strategy. Despite widespread implementation, its effectiveness on key health service indicators, particularly maternal and child health (MCH) services, remain unclear.ObjectiveThis study aimed to evaluate the contribution of DHIS2 on data use and the performance of selected MCH indicators in Ethiopia, comparing data before and after the implementation of DHIS2.MethodsWe analysed data from primary health care units (PHUs) across five diverse regions of Ethiopia, encompassing urban, agrarian, and pastoralist settings. A mixed-methods approach was employed, combining quantitative and qualitative methods to provide a comprehensive understanding of the data. The quantitative component involved examining performance reports of selected maternal and child health (MCH) indicators from 2013 to 2022 to assess changes before and after the implementation of the District Health Information System 2 (DHIS2). Data were collected electronically and analysed using descriptive statistics and interrupted time series (ITS) analyses to identify trends and patterns. The qualitative component included interviews and focus group discussions with health workers and stakeholders to explore contextual factors influencing MCH service utilization and performance. The data were analysed thematically using OpenCode 4.1 software.ResultsThe implementation of DHIS2 significantly contributed to the enhancement of MCH data utilization within PHU facilities. This improvement supported decision-making processes in various aspects of maternal and child healthcare delivery, including target setting, resource allocation, program monitoring, and clinical service provision. Specifically, DHIS2 led to increased monthly mean performance of key indicators such as antenatal care visits, skilled birth attendance, and immunization rates. Notable improvements in service delivery were observed, with significant increases in institutional delivery rates over time.ConclusionsThe study highlights DHIS2’s significant contribution to improving MCH services in Ethiopia, with increased institutional delivery rates and ANC coverage reflecting enhanced data-driven decision-making. Most facilities relied on DHIS2 for resource allocation and program monitoring, though challenges like offline usage and accessibility persist. To maximize impact, improving offline data management, training staff, leveraging real-time reporting, and addressing accessibility through connectivity investments are recommended.

This chapter seeks to contribute to the ongoing debates in the domain of Participatory Design by discussing the various trends and questions within the context of the Health Information Systems Programme (HISP) initiative ongoing globally over the last 15 or so years (see Braa et al. 2004). The empirical basis for this chapter is provided by the efforts – technical, educational and political – in developing and evolving the HISP network with a key focus on the design, development, implementation and scaling of the DHIS (District Health Information Software) within an action research framework for the public health sector in developing countries. HISP can be described as a global research, development and action network around healthinformation systems (HIS) for the Global South, enabled through South-South-North collaboration. The network is by no means homogeneous and static, nor in harmony following a single goal, including how Participatory Design techniques have been and should be used. HISP was initiated through the efforts of a few as a bottom-up Participatory Design project in South Africa in 1994/5, and has today evolved into a global and thriving network spread across multiple countries and contexts. This development has been non-linear and followed different trajectories, experiencing successes and setbacks, as well as radical technological changes: the Internet and mobile network revolutions in Africa and Asia and the shift from stand-alone desktop application to networked web applications. HISP evolution has gained further impetus through increased focus on global health, including on the achievement of the Millennium Development Goals (MDGs). During times of rapid policy, technological and other changes, HISP has all along tried to be ‘on top of ’ the changing environment, but has many times been victim to changing policies; as an example, being literally thrown out of Ethiopia after years of work as a result of political decisions at the national level. At no point in time have the HISP actors been able to foresee moves into the future, as the context of funding and politics has been constantly changing and uncertain. Maybe the only consistent element in the history of HISP has been a stubborn willingness to apply participatory approaches in designing HIS in cooperation with various levels of users in a variety of contexts. A key focus of the application of Participatory Design techniques has been around the designand development of the DHIS software. The DHIS is a tool for collection, validation, analysis and presentation of aggregate statistical data, tailored to supporting integrated health information management activities. It is designed to serve as a district-based country data warehouse to address both local and national needs. DHIS is a generic tool rather than a pre-configured database application, with an open meta-data model and a flexible user interface that allows the user to design the contents of a specific information system without the need for programming. DHIS development has evolved over two versions. The first – DHIS v1 – has been developed since 1997 by HISP in South Africa on MS Access, a platform selected because it was at that time a de facto standard in South Africa. The second – DHIS v2 – building on the v1 data model is a modular web-based software package built with free and open source Java frameworks, developed since 2004 and coordinated by the University of Oslo. The flexible and modular DHIS software application has all along been the pivotal elementin the HISP approach; both as a tool with which to communicate design to users and as a software application suite which may provide results from day one and thereafter expand while in full production, as more functionalities, datasets and other elements are added. This chapter attempts to describe this rather complex movement over the last 15 years of theHISP network and its associated dimensions of software development and Participatory Design processes in a multiplicity of contexts. We have interpretively developed a historical reconstruction of this movement to depict the following three broad phases of HISP development. Inaddressing the first phase (1995-2000), we discuss HISP in relation to ‘traditional’ Participatory Design based primarily on the experience in South Africa. In the second phase (2000-6), which was characterised by pilot projects and ‘networking Participatory Design’, we focus on how networks of action were created outside South Africa, also encompassing educational programmes. In the third phase (2006-10), development of the fully open source and web-based DHIS platform gained momentum and challenges were experienced in applying distributed Participatory Design and scaling HISP during a time of significant technological change, including rapid spread of Internet and mobile networks in developing countries. Finally, we discuss the future direction for HISP and Participatory Design in the age of cloud computing. In our coverage of HISP, we highlight the important role that context plays in each country, which we illustrate through cross-country comparisons.

A significant number of health applications have been developed at various levels, including primary care, hospitals, district and provincial health offices, private sectors, and the national level, resulting in the fragmentation of health data at primary health center level. This situation has prompted the government released Ministerial Regulation No. 18 of 2022 on “One health data” to address the fragmentations. While digital health transformation focuses on individual health services through the digital technology, the one health data focuses on data integration, analysis, visualization, and cross-sectoral utilization of health data. We proposed the use of an open-source technology to facilitate the process of data integration in district level to achieve “one health data”. District Health Information Software 2 (DHIS2), an open-source application was introduced to the district health office as data warehousing, data management, data analysis, data validation, visualization dan information sharing. DHIS2 was used to mitigate health data fragmentation in District Health Office of Kulon Progo that has been struggle since 2018 to integrate a number of routine health data from different programs. Assisted by the Department of Health Policy and Management at the Faculty of Medicine, Public Health, and Nursing, DHIS2 was implemented incrementally that involves a number of data manager at district and primary health care level. The data integration referred as Aplikasi Satu Data Kesehatan (ASDK) Kulon Progo. The objective of ASDK Kulon Progo includes data integration, health program monitoring, evaluation, and support for the development of data-driven policies. In 2022, the Department of Health Policy and Management FK-KMK UGM together with alumni and students facilitated the implementation of ASDK in Kulon Progo as part of the community service program targeting organization that serve community.

BackgroundThe District Health Information Software-2 (DHIS2) is widely used by countries for national-level aggregate reporting of health-data. To best leverage DHIS2 data for decision-making, countries need to ensure that data within their systems are of the highest quality. Comprehensive, systematic, and transparent data cleaning approaches form a core component of preparing DHIS2 data for analyses. Unfortunately, there is paucity of exhaustive and systematic descriptions of data cleaning processes employed on DHIS2-based data. The aim of this study was to report on methods and results of a systematic and replicable data cleaning approach applied on HIV-data gathered within DHIS2 from 2011 to 2018 in Kenya, for secondary analyses.MethodsSix programmatic area reports containing HIV-indicators were extracted from DHIS2 for all care facilities in all counties in Kenya from 2011 to 2018. Data variables extracted included reporting rate, reporting timeliness, and HIV-indicator data elements per facility per year. 93,179 facility-records from 11,446 health facilities were extracted from year 2011 to 2018. Van den Broeck et al.’s framework, involving repeated cycles of a three-phase process (data screening, data diagnosis and data treatment), was employed semi-automatically within a generic five-step data-cleaning sequence, which was developed and applied in cleaning the extracted data. Various quality issues were identified, and Friedman analysis of variance conducted to examine differences in distribution of records with selected issues across eight years.ResultsFacility-records with no data accounted for 50.23% and were removed. Of the remaining, 0.03% had over 100% in reporting rates. Of facility-records with reporting data, 0.66% and 0.46% were retained for voluntary medical male circumcision and blood safety programmatic area reports respectively, given that few facilities submitted data or offered these services. Distribution of facility-records with selected quality issues varied significantly by programmatic area (p < 0.001). The final clean dataset obtained was suitable to be used for subsequent secondary analyses.ConclusionsComprehensive, systematic, and transparent reporting of cleaning-process is important for validity of the research studies as well as data utilization. The semi-automatic procedures used resulted in improved data quality for use in secondary analyses, which could not be secured by automated procedures solemnly.

BackgroundThe ability to report complete, accurate and timely data by HIV care providers and other entities is a key aspect in monitoring trends in HIV prevention, treatment and care, hence contributing to its eradication. In many low-middle-income-countries (LMICs), aggregate HIV data reporting is done through the District Health Information Software 2 (DHIS2). Nevertheless, despite a long-standing requirement to report HIV-indicator data to DHIS2 in LMICs, few rigorous evaluations exist to evaluate adequacy of health facility reporting at meeting completeness and timeliness requirements over time. The aim of this study is to conduct a comprehensive assessment of the reporting status for HIV-indicators, from the time of DHIS2 implementation, using Kenya as a case study.MethodsA retrospective observational study was conducted to assess reporting performance of health facilities providing any of the HIV services in all 47 counties in Kenya between 2011 and 2018. Using data extracted from DHIS2, K-means clustering algorithm was used to identify homogeneous groups of health facilities based on their performance in meeting timeliness and completeness facility reporting requirements for each of the six programmatic areas. Average silhouette coefficient was used in measuring the quality of the selected clusters.ResultsBased on percentage average facility reporting completeness and timeliness, four homogeneous groups of facilities were identified namely: best performers, average performers, poor performers and outlier performers. Apart from blood safety reports, a distinct pattern was observed in five of the remaining reports, with the proportion of best performing facilities increasing and the proportion of poor performing facilities decreasing over time. However, between 2016 and 2018, the proportion of best performers declined in some of the programmatic areas. Over the study period, no distinct pattern or trend in proportion changes was observed among facilities in the average and outlier groups.ConclusionsThe identified clusters revealed general improvements in reporting performance in the various reporting areas over time, but with noticeable decrease in some areas between 2016 and 2018. This signifies the need for continuous performance monitoring with possible integration of machine learning and visualization approaches into national HIV reporting systems.

High-quality vaccine-preventable disease (VPD) surveillance data are critical for timely outbreak detection and response. In 2019, the World Health Organization (WHO) African Regional Office (AFRO) began transitioning from Epi Info, a free, CDC-developed statistical software package with limited capability to integrate with other information systems, affecting reporting timeliness and data use, to District Health Information Software 2 (DHIS2). DHIS2 is a free and open-source software platform for electronic aggregate Integrated Disease Surveillance and Response (IDSR) and case-based surveillance reporting. A national-level reporting system, which provided countries with the option to adopt this new system, was introduced. Regionally, the Epi Info database will be replaced with a DHIS2 regional data platform. This report describes the phased implementation from 2019 to the present. Phase one (2019-2021) involved developing IDSR aggregate and case-based surveillance packages, including pilots in the countries of Mali, Rwanda, and Togo. Phase two (2022) expanded national-level implementation to 27 countries and established the WHO AFRO DHIS2 regional data platform. Phase three (from 2023 to the present) activities have been building local capacity and support for country reporting to the regional platform. By February 2024, eight of 47 AFRO countries had adopted both the aggregate IDSR and case-based surveillance packages, and two had successfully transferred VPD surveillance data to the AFRO regional platform. Challenges included limited human and financial resources, the need to establish data-sharing and governance agreements, technical support for data transfer, and building local capacity to report to the regional platform. Despite these challenges, the transition to DHIS2 will support efficient data transmission to strengthen VPD detection, response, and public health emergencies through improved system integration and interoperability.

The Public Health Inspector (PHI) Monthly Report is a critical document that provides insights into environmental, occupational health and food safety aspects within each Medical Officer of Health area in Sri Lanka. Currently, PHIs use a paper format to track these key health indicators, resulting in incomplete and inaccurate national data. This study evaluates the usability of a DHIS2 (District Health Information Software 2) based digital solution to improve PHI reporting. The DHIS2 system was customised to address the gaps in the current reporting process, and its usability was evaluated using the System Usability Scale (SUS) with 50 stakeholders who tested the system. The DHIS2 platform was flexible enough to be customised to meet the requirements of the new electronic Environmental, Occupational Health and Food Safety Information Management System (eEOHFSIMS). The system achieved an average SUS score of 72.25, exceeding the accepted benchmark of 68, with a high SD of 13.37. However, a 92% knowledge gap remained. Digitising the PHI monthly report using DHIS2 addresses the challenges of traditional paper-based reporting, enabling timely monitoring of public health indicators. The favourable SUS score confirms the system's high usability, yet the knowledge gap underscores the need for ongoing user training to ensure data quality. The eEOHFSIMS demonstrated its capacity to deliver accurate, complete and timely data, greatly benefiting Sri Lanka's primary healthcare services. This system enhancement supports better-informed decision-making, aligns with national health policies and enables continuous monitoring and evaluation of public health services.

Tuberculosis (TB) is a major public health problem in Guinea, where many cases are undetected and untreated. A robust health information system is needed to improve TB case detection and treatment outcomes. DHIS2 (District Health Information Software 2) is a web-based system that collects, analyses and reports data on TB indicators. However, its use and use in Guinea is affected by various factors. We explored these factors using a qualitative survey with health workers and managers who use DHIS2 for TB surveillance. We collected data through a survey with open-ended questions and analysed them using classical content analysis. We conducted a qualitative survey with 35 health workers and managers who use DHIS2 for TB surveillance at different levels of the health system in Guinea. We collected data through an online survey with open-ended questions and analysed them using classical content analysis with NVivo software. We identified four main themes: technical issues (such as internet connection, data synchronisation, and validation rules), data quality issues (such as data validation, data aberrations, and data completeness), training and support issues (such as data analysis techniques, online training, orientation on DHIS2), and organisational issues (such as integration of community data, standardisation of data elements, meetings for data validation). We discussed how these findings could inform the improvement of DHIS2 for TB surveillance in Guinea and other similar settings. Keywords: DHIS2, Health information system, Surveillance, Tuberculosis, Qualitative study.

BackgroundAccurate and timely infectious disease surveillance is pivotal for effective public health responses. An important component of this is the disease surveillance tools used. Understanding views and experiences of users is crucial for informing policy decisions and ensuring the seamless functioning of surveillance systems.ObjectiveIn this study, we aimed to assess the user perceptions of 3 disease surveillance tools used in Côte d’Ivoire, namely, MAGPI, District Health Information Software 2 (DHIS2), and Surveillance Outbreak Response Management and Analysis System (SORMAS), the latter was implemented in 2021 within a pilot scheme.MethodsWe conducted interviews and a web-based survey distributed to users of the 3 surveillance tools. The survey assessed users’ views of the surveillance tools’ usefulness, ease of use, feelings toward the tool, conditions that may influence the use, and other characteristics. The descriptive analysis compared responses from SORMAS, MAGPI, and DHIS2 users, providing a comprehensive evaluation of their experiences.ResultsAmong the 159 respondents who actively use one of the systems, MAGPI was the most widely used surveillance tool among respondents (n=127, 79.9%), followed by DHIS2 (n=108, 67.9%), and SORMAS (n=25, 15.7%). In terms of users’ perceptions, SORMAS, despite its limited implementation, emerged as a tool that allows for data analysis and had the most comprehensive set of functionalities. DHIS2 was appreciated for its frequency of report provision, although users reported occasional IT system failures. MAGPI was recognized for its ease of use but was reported to lack certain functionalities offered by the other surveillance systems.ConclusionsThis study offers valuable insights into the perceptions of disease surveillance tools users in Côte d’Ivoire. While all systems were positively regarded, each exhibited strengths and weaknesses addressing different needs and functionalities. Policy makers and health officials can use these findings to enhance existing tools or consider a unified approach for infectious disease surveillance systems. Understanding users’ perspectives allows them to optimize the choice of surveillance tools, ultimately strengthening public health responses in Côte d’Ivoire and potentially serving as a model for other countries facing similar decisions in their health care systems.

Estimating effective coverage of childbirth care requires linking population based data sources to health facility data. For effective coverage to gain widespread adoption there is a need to focus on the feasibility of constructing these measures using data typically available to decision makers in low resource settings. We estimated effective coverage of childbirth care in Gombe State, northeast Nigeria, using two different combinations of facility data sources and examined their strengths and limitations for decision makers. Effective coverage captures information on four steps: access, facility inputs, receipt of interventions and process quality. We linked data from the 2018 Nigerian Demographic and Health Survey (NDHS) to two sources of health facility data: (1) comprehensive health facility survey data generated by a research project; and (2) District Health Information Software 2 (DHIS2). For each combination of data sources, we examined which steps were feasible to calculate, the size of the drop in coverage between steps and the resulting estimate of effective coverage. Analysis included 822 women with a recent live birth, 30% of whom attended a facility for childbirth. Effective coverage was low: 2% based on the project data and less than 1% using the DHIS2. Linking project data with NDHS, it was feasible to measure all four steps; using DHIS2 it was possible to estimate three steps: no data was available to measure process quality. The provision of high quality care is suboptimal in this high mortality setting where access and facility readiness to provide care, crucial foundations to the provision of high quality of care, have not yet been met. This study demonstrates that partial effective coverage measures can be constructed from routine data combined with nationally representative surveys. Advocacy to include process of care indicators in facility summary reports could optimise this data source for decision making.

Oral health is essential to overall health but faces significant challenges in low- and middle-income countries like Angola due to inequalities in access to care, worsened by a lack of infrastructure and resources. DHIS2 (District Health Information Software 2) emerges as a viable solution to improve health data management and promote equity in access to dental care. Objective to identify opportunities and challenges in implementing DHIS2 to promote oral health in Angola. The research, conducted according to the Joanna Briggs Institute (JBI) guidelines, used specific descriptors in the PUBMED, SCOPUS, and WEB OF SCIENCE databases, resulting in the selection of 11 studies, which were analyzed through content analysis. The analysis revealed four main categories: 1) oral health as a priority, 2) electronic health systems, 3) benefits and challenges of EHR/POE, and 4) DHIS2's contribution to equity. It is concluded that, although DHIS2 has the potential to optimize data management and support inclusive policies, its implementation requires investments in infrastructure, professional training, and intersectoral support to overcome structural challenges.

Estimating effective coverage of childbirth care requires linking population based data sources to health facility data. For effective coverage to gain widespread adoption there is a need to focus on the feasibility of constructing these measures using data typically available to decision makers in low resource settings. We estimated effective coverage of childbirth care in Gombe State, northeast Nigeria, using two different combinations of facility data sources and examined their strengths and limitations for decision makers. Effective coverage captures information on four steps: access, facility inputs, receipt of interventions and process quality. We linked data from the 2018 Nigerian Demographic and Health Survey (NDHS) to two sources of health facility data: (1) comprehensive health facility survey data generated by a research project; and (2) District Health Information Software 2 (DHIS2). For each combination of data sources, we examined which steps were feasible to calculate, the size of the drop in coverage between steps and the resulting estimate of effective coverage. Analysis included 822 women with a recent live birth, 30% of whom attended a facility for childbirth. Effective coverage was low: 2% based on the project data and less than 1% using the DHIS2. Linking project data with NDHS, it was feasible to measure all four steps; using DHIS2 it was possible to estimate three steps: no data was available to measure process quality. The provision of high quality care is suboptimal in this high mortality setting where access and facility readiness to provide care, crucial foundations to the provision of high quality of care, have not yet been met. This study demonstrates that partial effective coverage measures can be constructed from routine data combined with nationally representative surveys. Advocacy to include process of care indicators in facility summary reports could optimise this data source for decision making.

PurposeUganda’s digital health transformation anchored on District Health Information Software 2 (DHIS2) and the FAIR (Findable, Accessible, Interoperable, Reusable) Data Principles has reshaped health data governance. Nevertheless, systemic constraints in privacy, infrastructure, and human resources threaten sustainability and equity.ObjectiveTo compare DHIS2 and FAIR-based approaches on (i) privacy protection, (ii) interoperability and data usability, and (iii) regulatory/institutional readiness for privacy-preserving health data analytics in Uganda.MethodsSystematic review of 84 peer-reviewed and grey-literature sources (2010–2025) following PRISMA 2020; extracted indicators on reuse, interoperability, privacy, and institutional readiness.Results36% of included studies were Uganda-specific; 50% were published in 2020–2024. DHIS2 reached near-national coverage, ~12,000 trained users, and integration across >20 programmes. Persistent gaps include limited rural internet (≈12% of facilities with stable connectivity), high staff turnover (~35%), and low analytics literacy (~25% with intermediate skills). FAIR efforts (since ~2019) remain early: ~10% of institutions with formal policies; low dataset reuse (~22%), machine-readable metadata (~18%), and documented digital consent (<10%). Privacy infrastructure is weak: <30% of facilities with formal privacy frameworks/secure platforms and <10% with Data Protection Officers.ConclusionDHIS2 improved reporting and availability, while FAIR initiatives began enabling governed, interoperable reuse. To achieve ethical analytics at scale, priorities are legal enforcement, secure rural ICT, standardized machine-readable metadata/consent, and workforce development.

Adequate functionality of electronic routine health information systems (eRHISs) is crucial for data use, yet few studies explored it in relation to newborn and stillbirth data in Africa. We conducted this cross-sectional study between November 2022 and July 2024 in data offices at central and subnational levels in 12 regions and 4 city administrations in the Central African Republic (CAR), Ethiopia, Tanzania, and Uganda. Except for end-user perspectives (collected via interviews), we collected data related to eRHIS functionalities by direct observation following standard operating procedures as for the Every Newborn-Measurement Improvement for Newborn & Stillbirth Indicators (EN-MINI) Tool 3.1, based on the Performance of Routine Information System Management (PRISM) framework. We analysed data according to the PRISM Users' Kit. We assessed 53 data offices in total. All countries used the same software application, the District Health Information Software 2 (DHIS2). Settings were heterogeneous across countries, with a tendency for DHIS2 to offer fewer functionalities to users in the CAR. Overall functionalities for generating facility annual summary reports (100% in all countries) and for calculating percentage of reports received/expected (75.0% in Ethiopia to 88.9% in Tanzania) were widely available. Data integration and data disaggregation, meanwhile, had lower availability. Functionalities for calculating coverage on specific indicators, such as respectful care, were lacking in all countries, those for quality assurance varied across countries, while those related to data visualisation were almost always available in Uganda and Tanzania, but showed specific gaps in Ethiopia (i.e. for early initiation breastfeeding), and most often lacked in the CAR. Most end-users indicated needs for eRHIS improvement (ranging from 37.5% in Ethiopia to 100% in the CAR; P = 0.001), with 17.0% reporting needs for major improvement (from 10.0% in Uganda to 28.6% in the CAR; P = 0.001). Subgroup analyses suggested high within-country heterogeneity and more eRHIS functionalities available at central vs. subnational level. Identified strengths and gaps in existing DHIS2 functionalities can inform the design of context-specific interventions that will enhance data use for reducing neonatal mortality and stillbirth rates.