SAJIM South African Journal of Information Management 2078-1865 1560-683X AOSIS SAJIM-28-2060 10.4102/sajim.v28i1.2060 Original Research Managers’ perspectives on using routine health information systems for effective child healthcare programmes in Namibia https://orcid.org/0000-0002-6811-6507 Namukwambi Rauna N. 1 https://orcid.org/0000-0002-4163-9092 Ramukumba Mokholelana M. 2 Department of Community and Mental Health Nursing Science, Faculty of Health Sciences and Veterinary Medicine, University of Namibia, Keetmanshoop, Namibia Department of Health Studies, Faculty of Human Sciences, University of South Africa, Pretoria, South Africa Corresponding author: Rauna Namukwambi, rnamukwambi@unam.na 26032026 2026 28 1 2060 21072025 20102025 © 2026. The Authors 2026 Licensee: AOSIS. This work is licensed under the Creative Commons Attribution 4.0 International (CC BY 4.0) license. Background

Routine health information systems (RHISs) are critical for evidence-based child health programme management, yet limited research exists on healthcare managers’ experiences with RHIS implementation in resource-constrained settings.

 Objectives

This study explored healthcare managers’ perspectives on using RHISs to enhance child healthcare programme effectiveness in Namibia.

 Method

A qualitative case study design employed semi-structured interviews with 24 healthcare managers. Purposive sampling ensured representation across management hierarchies, and Braun and Clarke’s six-stage thematic analysis guided data analysis.

 Results

Three themes emerged: RHIS implementation challenges, capacity and governance gaps, and pathways for sustainable development. Namibia’s hybrid paper-digital system creates inefficiencies, with poor connectivity and technical glitches undermining data reliability. While managers demonstrated conceptual understanding of RHIS importance, significant disparities existed in practical data management skills and DHIS2 access. Despite data availability, strategic planning remained constrained by political influences, absent policy frameworks, and fragmented parallel systems lacking interoperability. Managers primarily used routine data for operational decisions rather than strategic planning.

 Conclusion

Effective RHIS implementation requires simultaneously addressing technical infrastructure, human capacity, and institutional governance. Priority interventions should target system reliability, practical data competencies, and legislative frameworks mandating evidence-based planning.

 Contribution

This study provides a new understanding of the complex technical, capacity and governance factors that influence the effectiveness of RHISs in resource-constrained settings.

 child healthcare data quality health information system healthcare managers information use routine health information system Funding information This research received grant from the University of South Africa for data analysis. Introduction

The health information system (HIS) broadly involves collecting health data from health facilities and communities as part of a routine health information system (RHIS) (Mboera et al. 2021). The primary objective of HISs is to generate high-quality data that can be utilised by managers and all stakeholders in the health system to inform evidence-based decisions (Sako et al. 2022). An effective HIS is characterised by strong maintenance and reliability, providing comprehensive and accurate data that facilitates evidence-based decision-making and supports the design and execution of sustainable health interventions (Rajkumar et al. 2024). Health information systems can be captured and managed in paper-based, electronic or hybrid formats. Paper-based records are types of health information that are collected using hard copies and processed manually. An electronic health record is a compilation of software routines that provide all the features and functions, designed to fulfil the needs of an automated health information management system (Sitting 2017). The most commonly used software for capturing routine health information is District Health Information Software 2 (DHIS2). District Health Information Software 2 was developed by the HIS Programme and is an open-source platform that includes data validation, visualisation and analysis tools readily available, allowing for access and manipulation of health data at central levels (Farnham et al. 2023). The platform can be customised to allow user to adapt the system to meet their specific data needs and organisational workflows. Namibia customised the software to add specific needs, such as geographic aggregation of data or creating metadata, such as data elements, indicators and data sets related to child healthcare (DHIS2 2025).

Child healthcare services are planned and managed at all levels within Namibia’s Ministry of Health and Social Services (MoHSS), with support from developmental partners, such as the United Nations Children’s Fund (MoHSS 2011). Child health programmes are initiated nationally, where policies and guidelines are formulated. At the regional level, a unit supports districts in training health professionals on child healthcare programmes and activities. At the district level, healthcare managers play a crucial role in ensuring that facilities receive the necessary resources to deliver quality services for child healthcare initiatives (MoHSS 2020).

Namibia has established effective policies related to child health, including the Namibia Child Health Survival Strategy 2010–2014, Integrated Management of Neonatal and Childhood Illnesses (IMNCI), National Health Policy Framework 2010–2020, Expanded Programme on Immunisation, Infant and Young Children Feeding Policy practices guideline and nutrition policy. However, policy monitoring, evaluation and linkage to the Health Management Information System (HMIS) are not yet fully established (MoHSS 2020). Child healthcare providers need complete, accurate and timely data for informed decision-making to plan and manage service delivery related to children under the age of five. In Namibia, the most common challenges that cause child morbidity and mortality are diarrhoea, malaria, pneumonia and HIV-associated illnesses. Furthermore, undernutrition among children under 5 years persists in 2022. The prevalence of chronic malnutrition remains high, with 23% stunted and 24% underweight in Namibia (Albanus & Ashipala 2023).

Routine health information systems offer systematic insights into health status indicators, service utilisation patterns and resource distribution. Routine Health Information services are foundational infrastructure for health service planning and management across all system levels, particularly within child health domains. It further plays critical roles in enabling effective service delivery and evidence-based programme improvement (Ayele et al. 2024). In many instances, routine data remain in databases and are not adequately utilised in programme development, policy development and strategic planning. This can be attributed to insufficient data quality to support its use, as well as the lack of integration of data use into the decision-making process at the operational and policy-making levels. Furthermore, the information needs of decision-makers are not addressed in data collection efforts (Asemahagn 2017).

Therefore, all routinely collected data are a crucial source of information for estimating healthcare coverage. However, routine health data from developing countries, including Namibia, face significant challenges with unreliable HIS, characterised by substandard data quality and weak use of routine health information for decision-making (Tolera et al. 2024). A study by Sako et al. (2022) demonstrated that 63.1% of health professionals working in public health facilities across the South Ethiopia Region utilised routine health information. A systematic review conducted by Tadele et al. (2023) found that, generally, routine health information usage rates were 53.7% in Ethiopia, compared to 66% in Kenya and 58% in Tanzania. Regarding healthcare managers, Yusuph et al. (2024) stated that primary healthcare managers in the Dodoma region use routine health data for decision-making purposes, which revealed that 84% of primary healthcare managers use routine health data, 16% never use routine health data for decision-making. The findings suggest that a significant portion of healthcare managers make decisions without being guided by routine health data. This could potentially compromise the effectiveness of health planning interventions.

Significant challenges in Namibia’s HISs include a lack of HIS policies and guidelines guiding the implementation of HIS, thus harming data collection quality, processing, dissemination and actual use (Kapepo & Yashik 2018). Namibia has a disintegrated HIS; the system does not integrate data from all the MoHSS, and some critical child health programmes, such as HIV and tuberculosis (TB) child-related data, are not routinely included in DHIS2. Hence, decision-makers in need of health information often struggle to acquire and utilise it promptly (MoHSS 2020). Better-performing systems are linked to improvements in the utilisation of health information for the efficient allocation of resources and the effective targeting of interventions. To support decision-making in areas of policy, planning, implementation, management, monitoring and evaluation of healthcare services, healthcare managers at various levels of the healthcare system should be provided with accurate and timely information (Dufera & Box 2018).

There was a need to understand healthcare managers’ views, beliefs and opinions on using RHISs to effectively manage child healthcare programmes, focusing on identifying benefits, challenges and strategies for improvement.

The main research question was: What are the managers’ perspectives on using RHISs to enhance the effectiveness of the child healthcare programme in Namibia?

Sub-questions were:

What are the current RHISs used in processes in Namibia?

How do managers perceive the role of RHISs in managing child healthcare programmes?

What are the facilitators and challenges to effective use of RHISs?

How does RHIS data influence planning, resource allocation and monitoring child health outcomes?

What recommendations do managers have for improving RHISs to better support child healthcare programme?

This study adopted the logic model to provide a structured framework for mapping out key components, including inputs (HIS design and policies, skilled health professionals, child health indicators, standardisation), processes (RHIS data management processes and information use), outputs (quality routine information available on child health care, data reporting and feedback mechanisms) and short-term outcomes (improved data use by manager for programme monitoring, resource allocation and intermediate outcomes) (RHIS integration in programme planning, increased immunisation coverage, improved nutritional indicators, reduced mother-to-child transmission of HIV and reduced childhood illnesses) (see Figure 1).

Diagrammatic presentation of the logic model.

 Research methods and design Study design

A qualitative case study design approach was employed to explore managers’ perspectives on using RHISs to enhance the effectiveness of child healthcare programmes. The case study was the appropriate approach because it addressed the ‘when, how, and why’ questions that informed the core of the study (Yin 2018). The unit analysis was of healthcare managers, as the focus was on their individual perspectives.

The qualitative case design is based on a constructivist paradigm, which builds on participants’ own experiences of a phenomenon (Flick 2014).

 Study setting

The study was conducted at district and regional offices in the ||Kharas region and included national offices in Namibia. The inclusion of national offices aimed to obtain opinions from managers in higher positions to enrich the data, thereby providing a clearer understanding of the Namibian context.

 Study population and sampling strategy

The study population consisted of healthcare managers from the district and regional healthcare managers in the ||Kharas region who were responsible for managing child healthcare programmes. Healthcare managers at all levels use DHIS2 for data management. Some managers were from the national authority. A non-probability, purposive sampling method was used to recruit knowledgeable participants in HISs and provide oversight in managing child healthcare programmes. Specific criteria were also set for recruitment, and only managers who were using RHISs were recruited. Recruitment continued until data saturation was achieved. Fifteen managers participated in the study (see Table 1).

Healthcare managers’ profiles.

Descriptions Site Number of participants
Healthcare managers managing child healthcare District 4
Regional 3
Healthcare managers’ health managing the health information system District 3
Regional 2
National 3
Data collection instruments

The semi-structured interview was developed based on existing literature and the study’s objectives. The interview guide was developed in English, as participants were conversant with English. The concepts of the theoretical framework provided the primary focus for the line of questioning, facilitating in-depth probing to explore issues more comprehensively.

 Data collection procedure

The study used individual in-depth interviews, using a semi-structured interview guide. The grand tour questions were as follows: What are your views regarding the implementation of HIS and the RHIS in Namibia? Could you please share your experiences with the data management processes and how you use data from the routine health information system? Describe the facilitators and barriers in using RHIS data to manage the child healthcare programme. Individual interviews were suitable for this study because they enabled participants to share their personal experiences with data management processes and decision-making. They also had an opportunity to ask questions.

Data collection commenced after obtaining ethical clearance (Ref. no. HSHDC/1012/2020) from the University of South Africa, and participants had signed the consent forms.

The in-depth interviews provided support for a focus on specific areas of RHIS implementation and use in managing child healthcare. The researcher facilitated the interviews using either face-to-face or virtual calls. All interviews lasted between 1 h and 1 h and 30 min. Interviews were audio-recorded using the Otter.ai software. Data collection continued until data saturation was achieved.

 Data analysis

The study employed inductive thematic analysis, following the six-phase process proposed by Braun and Clarke (2021). Braun and Clarke’s thematic analysis is essentially a process for identifying patterns or themes within qualitative data. Phase one involved familiarisation with the data and transcription of data from Otter.ai software. Then, transcripts were read carefully, highlighting all relevant information and referencing specific research questions. In phase two, researchers began manually coding the transcripts. The codes represent basic elements identified that relate to the research question. The aim of coding and category construction was based on information characteristics to obtain a theme related to the phenomenon (Grove & Gray 2019). Key concepts from the Logic Framework guided the analysis process, as illustrated in Figure 1. In phase three, codes were organised into broader sub-themes, aligned with the research questions. Phase four comprised reviewing and refining the initial themes to ensure coherence and relevance. In Phase Five, the researchers further defined and clarified the themes, comparing them to explore interconnections and construct a coherent narrative. The final phase involved a comprehensive analysis of the themes, grounded in adequate evidence from the literature, to interpret the study findings. Thematic analysis was used to understand the meaning behind participants’ experiences and perspectives and to provide a deeper interpretation of the data. In recognising the reflexivity in Braun and Clarke’s data analysis process, the researchers were conscious of their own biases. This led to initiating several pauses and reflecting on how decisions were made, understanding the co-creator role in knowledge generation. Biases that could potentially skew the analysis were kept in check.

 Trustworthiness of qualitative data

Lincoln and Guba’s (2021) four criteria – credibility, transferability, dependability and confirmability – enhanced the study’s trustworthiness (Stahl & King 2020).

Credibility was enhanced through prolonged participant engagement, and data collection continued until saturation was achieved, allowing participants to confirm or dispute the accuracy and interpretation of the data. While conformability was completed, an electronic audit trail and thematic analysis were transparent. Recordings and transcripts were juxtaposed.

Dependability was enhanced by clear documentation of the research design and the implementation of the findings. Additionally, data were collected from healthcare managers at various levels of healthcare, including district, regional and national levels, to gain a broader understanding of how managers utilise RHISs to manage child healthcare. In order to enhance transferability, purposive sampling was performed to gain information from healthcare managers who have experience and knowledge in HIS. Rich and detailed descriptions were obtained from participants to ensure the transferability of the findings to similar contexts.

 Ethical considerations

Ethical clearance and approval were obtained from the University of South Africa’s Health Studies Research Ethics Committee, with ERC reference number HSDHDC/1012/2020. Permission was also obtained from the Executive Director of the MoHSS, and written informed consent was obtained from healthcare managers to participate in the study and to audio-record the interviews. Participation in the study was voluntary, and participants had the right to withdraw from the research process at any stage without penalty. Confidentiality and privacy were enhanced by limited access to Zoom interviews, and face-to-face interviews were done in a private room. Additionally, the names of the participants were not included in field notes, transcripts, reports or on audio tapes. Hence, there is no link between participants, and their data and transcripts were given pseudonyms.

 Results

The study intended to explore the perspectives of healthcare managers on using the RHIS for effective child healthcare programmes.

Demographic profile of participants

Most participants were female, comprising 60% (n = 9), while males made up 40% (n = 6). Namibia’s healthcare system is primarily staffed with female health professionals compared to males, which implies a slight disparity in representation between the two genders. The findings did not identify any disproportion in the use of routine health information between the two genders.

Regarding age, most healthcare managers fell within the 30–39 years and 50–59 years age ranges, with 33% (n = 5) in each category, while the rest comprised 20% or less. In terms of highest qualification, the majority of healthcare managers held a bachelor’s degree (Honours) at 47% (n = 7), followed by those with a master’s degree at 27% (n = 4). Those with diplomas accounted for 20% (n = 3), and 5% (n = 1) held a bachelor’s degree.

Among healthcare managers in this study, 60% (n = 9) were district-level managers, while 20% (n = 3) were regional managers. Additionally, technical advisers and national managers collectively accounted for 50% of the total, reflecting a diverse representation of managerial roles. This distribution highlights the study’s comprehensive coverage of healthcare managers with varying levels of expertise in RHIS implementation. Regarding experience, the majority, 47% (n = 7), had 1–3 years of managerial experience, followed by those with 4–6 years and 7–9 years of experience, each at 20% (n = 3). Managers with over 10 years of experience constituted 13% (n = 2).

This suggests that the majority of healthcare managers had relatively limited experience in decision-making related to health information and child healthcare, likely because of the high staff turnover in the MoHSS. However, the number of managers with 4–9 years of experience indicated a stable core of professionals. This implies that the level of data use represents both the insights of newer managers and the accumulated experience of those who have been in the system for several years.

 Themes

Three themes emerged from the data: the implementation of HISs in Namibia, the use of RHIS, and the role, challenges and pathways for sustainable development. Ten sub-themes emerged from these three themes.

Theme 1: Implementation of health information systems in Namibia

In this theme, two sub-themes emerged from the mapping of primary data: Structure and organisation of HISs in Namibia and Design of Namibian District Information Software two. The research question: What are the current RHIS processes used in Namibia?

Structure and organisation of health information systems in Namibia: Healthcare managers stated that the District Health Information Software is primarily used at the district, regional and national levels. However, Primary Health facilities still use paper-based reporting tools. Namibia is provided with financial and technical expertise in customising DHIS2 in the Namibian context by external donors. Additionally, external donors in Namibia support data quality by mentoring data producers and developing standard operating procedures (SOPs). Donors also acquired various pieces of equipment used in the HIS.

There is a lack of policies and guidelines on data management processes. A draft of HIS strategy still needs to be promulgated into policy or law. However, an outdated guideline on data collection remains in place.

Others referred to a manual embedded in DHIS2, which provides some directives on data management.

However, the manual does not address the use of health information. Participants lamented the lack of legislation that compels different health information software developers to exchange data with the ministry:

‘DHIS2 is the main system used in capturing, but the health facilities are using paper-based data capturing.’ (Participant 2; Female; District level)

‘The donors provide technical support through funding, capacity-building of staff through training or procuring equipment such as computers and other ICT equipment.’ (Participant 14; Female; Regional level)

‘We have what we call the HIS2K reference manual, the only official document or guiding document for HIS operation in the ministry that provides directions on how to collect data per service. It is silent on data analysis and use, and it is outdated. However, we do have a strategy that is in a draft mode.’ (Participant 5; Female; Regional level)

‘With regards to the legislation, policies, and guidelines, I think it is a domain which is lagging; Namibia does not have a specific policy on HIS, which is why there is software running parallel to DHIS2 and do not have an obligation to integrate into DHIS2 or exchange their data with the government.’ (Participant 5; Male; National level)

Design of Namibian district information software two: Most participants could explain the functionality of DHIS2 clearly and how the system generates data routinely captured from various sources in health facilities. District Health Information Software 2 has two types of modules: the aggregated module captures monthly summary forms collated from health facilities, while the tracker module is a client-based monitoring system that supports direct monitoring, follow-up and data analysis within a health programme.

Most participants described the advanced features of DHIS2 for data visualisation. The dashboard enables a high-level overview of data. Most managers expressed that the system has built-in security features for data security and confidentiality. Information captured in the system is transmitted to the users, who can access it at different points. They further indicated that only authorised users can access data; some have viewing responsibilities, and others have analysis responsibilities. Only national users can affect changes to the system. Thus, DHIS2 enables management to control access on a per-user and per-role basis and set expiration dates for user access.

Data revealed the absence of e-Health standards in the MoHSS, with current use being customised according to the programme or user needs. The participants also indicated that other HIS, such as electronic patient management systems, use e-Health Standards designed to serve patients’ day-to-day activities in HIV care:

‘DHIS2 has two modules, which are aggregated as well as tracker module; DHIS2 aggregated is at the district level and it collects mostly summaries of primary healthcare programmes such as maternal and child health, while the tracker is a more likely surveillance tool that is client-based monitoring system. We assigned different roles on DHIS2 at district, which is to enter data, at the regional level they view and analyse data and at the national level is to change the system design and add indicators.’ (Participant 5; Male; National level)

‘Let me say that the security measures we have in place are that the data is protected and cannot be accessed by anyone, only those authorised, after they are captured in the system.’ (Participant 5; Female; Regional level)

‘We are assigning roles to different users regarding DHIS2 security. At the district level, DHIS officers enter data. At the regional level, they analyse data; they cannot change the system. At the national level, they add indicators, change the design, and rectify errors.’ (Participant 3; Female; National level)

‘We do not have general standards of e-health; we utilise a common pool of standards; the development and implementation of the Health Information System is flexible to match the user’s needs.’ (Participant 1; Male; National level)

‘Other Health Information Systems, like the Electronic Patient Monitoring System for HIV patients (EPMIS), are designed to capture each patient’s HIV care during daily visits.’ (Participant 2; Male; Regional level)

 Theme 2: Using the routine health information system

The primary data revealed five sub-themes under the main theme using RHIS, which are: support for data processes, data management processes, data quality monitoring, data demand and information use.

Research questions:

What do managers perceive the roles of RHISs in managing child healthcare programmes?

How does RHIS data influence planning, resource allocation and monitoring child health outcomes?

Support for data processes: A sound feedback system should be interactive and connect all stakeholders across different levels of the health system to support data processes. However, a moderate number of participants expressed that national and regional levels provide feedback to the district and facility levels on performance against the targets of child health programmes. Most managers acknowledged the significance of feedback in improving data management processes. Even so, there were variations as some participants had different experiences. They expressed that performance information did not flow between the levels at desired frequencies.

Support supervision fosters programme improvement by facilitating the acquisition of basic knowledge and skills at all levels. However, the majority of managers indicated that they conduct supervisory visits to lower structures once or twice a year to evaluate data quality. Additionally, managers reported conducting supervisory visits to lower structures to assess the performance of different health programmes using data. Participants further indicated that support supervisory visits review whether data in paper-based registers at the health facility level corresponds with data entered in DHIS2:

‘We constantly provide feedback on a monthly and quarterly basis. Once we analyse data, we try to identify the gaps; if there are any discrepancies, we communicate them to health facilities to verify the data accuracy.’ (Participant 11; Female; Regional level)

‘There is no feedback from the national level on the quality of data that is entered into HIS software.’ (Participant 13; Female; District level)

‘We usually go down to the facility to check data in the registers, tally sheets, and summary reports and compare with what is in DHIS2 and whether it is the same. If not, we harmonise data.’ (Participant 4; Female; Regional level)

Data management processes: Participants acknowledged that using the correct tools for data capturing is critical for producing valuable data. They indicated that data from health facilities are entered into DHIS2 at the district level, and once data are entered into DHIS2, it becomes available to all those with access. After that, they extract data using various data elements to run comparisons across different facilities in different formats. The dashboard allows them to generate and share reports with the teams.

Some participants reported using Excel pivot tables to obtain data from DHIS2. Hence, most expressed confidence in data analysis and making decisions regarding child healthcare programmes. They utilise key performance indicators, such as immunisation coverage, nutritional indicators for children under 5 years old and HIV-negative status among HIV-exposed babies.

However, some participants, particularly district medical managers, reported a lack of access to DHIS2 and inadequate training in using the software. Information is typically conveyed to health facilities through graphic representations and shared during monthly district and regional management meetings. These meetings serve as a platform to identify gaps in service delivery and develop strategies to enhance health programme implementation:

‘I receive monthly reports from various health facilities, which I then enter into DHIS2. Once the data is entered, it becomes available at the regional level.’ (Participant 3; Female; District level)

‘As a manager, I analyse my data by looking at the key performance indicators such as immunisation coverage, underweight rate, stunting rate, and HIV-negative among HIV-exposed babies; I can interpret my data.’ (Participant 12; Female; District level)

‘Some of us do not have access to DHIS2 as I was not trained to use that software.’ (Participant 11; Female; Regional level)

Data quality monitoring: Some managers indicated that supervisors from different levels in the health system should verify data to ensure its quality. The focus is on assessing completeness and data consistency by comparing similar variables from various data sets.

However, in some instances, supervisors do not verify data because of the high workload, meaning data are sent directly to the district’s HIS office without undergoing the verification process. Most managers acknowledged that DHIS2 has built-in validation functionalities that enhance data quality. It gives alerts if there are massive variations between previously captured data elements. The system can pick up specific data elements and their minimum and maximum values. This ensures consistency and errors are picked up on time. In addition, DHIS2 has built-in features that enable the users to assess the completeness and timeliness of data in the system.

Regular meetings are held with data producers, users and health information stakeholders, and these meetings are coordinated at the regional or national level. Managers reiterate the purpose of engaging health programme managers on data quality initiatives, such as verifying data in DHIS2:

‘The supervisor at the clinic and ward at the department level needs to verify the statistics compiled by registered nurses or from the department. At district level, the primary health care supervisor or the matron also has to verify.’ (Participants 6; Female; District level)

‘At most times PHC supervisors are busy, then as HIS officer, I verify the variables which are on summary forms to ensure that data are of good quality.’ (Participant 3; Female; District level)

‘The system identifies errors or outliers. If you enter the information, a pop-up window will warn you that the data entered is out of range because there are maximum and minimum numbers embedded in DHIS2 to allow you to review and rectify the errors.’ (Participant 4; Female; Regional level)

‘DHIS2 has a feature that checks the data set, shows which data is not completed, as well as the time the data were entered and when all reports were completed.’ (Participant 1; Male; National level)

‘We invite programme managers to participate at our data review workshop, where we engage them on the use of DHIS2.’ (Participants 2; Male; Regional level)

Data demand: Child health indicators were cited as the primary mechanism for seeking specific data. Some participants indicated they require information on headcounts for various services provided to children, nutritional status, the status of HIV among HIV-exposed children, immunisation status of children and diseases causing ill-health among children under the age of 5 years.

However, participants expressed concerns about the delayed availability of data in DHIS2, noting that information becomes accessible for analysis approximately 24 h after it is entered. This lag impedes timely decision-making, as stakeholders must wait a full day before accessing updated data through Internet-connected devices such as computers, laptops or tablets.

Some participants raised concerns that the data obtained from RHISs are insufficient to meet managers’ information needs. Although some services were provided to patients, data on those services were not captured, making it difficult to determine the outcome of the interventions. These include many children who were provided with Albendazole for deworming and zinc supplements:

‘In order for me to make decisions regarding the nutrition of children under the age of five years. I looked for information on such as undernutrition, stunting, overweight children under five years, children born by HIV-positive mothers, and the top five causing illnesses, as well as information on how many children are immunised and what is immunisation coverage in that specific catchment and population.’ (Participant 9; Male; Regional level)

‘Once data is entered in DHIS2, it first goes to the central server; data is unavailable at that time, and you can only run reports and analyse reports after 24 hours when it’s computed at the central point.’ (Participants 10; Female; District level)

‘Health information needs are not 100% addressed because not all are captured on RHIS, like the deworming of children with Albendazole, Zinc supplements of children under five years, and services are provided routinely; now how do we assess our performance in that regard?’ (Participants 9; Male; Regional level)

Information use: Participants stated that they use routine health data to ensure an adequate supply of appropriate resources, such as vaccines, and to deploy the health workforce according to workload in different health facilities. Furthermore, most participants indicated that they utilise routine health data to monitor the implementation of various child health programmes. Data are also used to determine if the health facilities or district are reaching their immunisation coverage target and identify the causes of underperformance in different health facilities. Additionally, they utilise data to track the growth and nutritional status of children under the age of five. They identify the percentage of children seen at health facilities with different nutritional statuses. The majority of the participants also use data to monitor the elimination of mother-to-child transmission of HIV programmes as well as the outcomes of the prophylactic treatment given to babies born to HIV-positive mothers. The participants also indicated that routine health data are mainly utilised to monitor disease trends and to be alert for possible disease outbreaks. If the number of specific diseases is unusually high in the health facilities, they investigate and plan for intervention. Routine health data were viewed as critical when compiling annual plans.

However, participants noted that routine health data remains underutilised in the MoHSS’ decision-making and budgeting processes. The primary barrier identified was political interference in financial management. The interference appeared to be a longstanding systemic issue within Namibia’s health sector:

‘We use immunisation data to order different vaccines from our health facilities. They enable us to know how many children we get per month for immunisation per vaccine antigen, in order accurately in order to prevent stock-outs.’ (Participant 9; Male; Regional level)

‘We use data for staff distribution around the health facilities and in the districts and also determine which services require more staff than the others by the data that are generated; this also helps us to motivate for additional staff.’ (Participant 10; Female; District level)

‘I monitor the immunisation coverage by looking at Expanded Programme on Immunisation, using data and check if children have completed their immunisation schedule.’ (Participant 12; Female; District level)

‘The information collected can give us an idea of how healthy the children under the age of five years are by monitoring their growth or how stunted they are or how unhealthy in terms of nutrition.’ (Participants 8; Female; District level)

‘Data collected in health facilities can alert us on possible or maybe possible outbreak or an outbreak of disease by monitoring the trends.’ (Participant 9; Male; Regional level)

‘We use data mainly for planning purposes, especially in strategic, annual, and quarterly plans.’ (Participant 13; Female; District level)

‘Data is not well used, it appears that decision-makers and policy makers do not need routine health data because budgeting is not based on data but on past expenditures, political influence or availability of resources.’ (Participant 15; Male; National level)

 Theme 3: Pathways for sustainable development

Under the theme of pathways for sustainable development, four sub-themes emerged from the primary data collected from participants which are: supportive role of HIS officers, factors that impact the implementation of HIS, road map for RHISs in Namibia and measures for improvement of RHISs.

Research question: What are the facilitators and challenges to the effective use of RHISs?

Supportive role of health information system officers: Some managers at the national level indicated that they manage and provide a plan of action for HISs in the country. This level of government also coordinates the technical working committee that guides the implementation of HISs in Namibia. They further stated that the DHIS2 database is managed at a central warehouse, a function under the national level. The HIS officers and system analysts regularly run backups on the DHIS2 database to ensure that the data captured is retrievable. They can configure DHIS2 settings by adding new data sets and elements.

Furthermore, the national level facilitates the development of policies, guidelines and SOPs in collaboration with technical working groups and other lower health system groups. Currently, the technical working group is supporting the development of a regulatory framework for HIS.

The regional level coordinates the HIS programme and ensures that HISs are implemented in all the districts under their jurisdiction. Training is a crucial activity for enhancing the quality of routine health information. Managers from the regional level conduct data analysis to ensure that the data are correct and ready for use. Based on the findings, corrective initiatives are recommended to the districts.

Most participants at the district level indicated that Namibia’s current health system structure mandates the district to ensure the effective implementation of HISs at the health facility level. They also articulated the district’s other role in data capturing. Officers at this level enter data from paper-based summary forms from various health facilities into DHIS2.

These District HIS officers disseminate the information to management through presentations on health programme performance and data quality. In addition, they also provide feedback on disease trends and programme performance to improve service delivery in their catchment areas:

‘The national level is more strategic in terms of managing and providing directions for HIS; the national level coordinates technical working groups, which are comprised of different stakeholders, who are representatives from key partners that support the Ministry of Health and Social Services in the domain of health information systems.’ (Participant 14; Female; Regional level)

‘We run continuous backups to ensure that data is not lost. This is a central system, and it’s easily managed; the data is at the central point at the national level.’ (Participant 5; Female; Regional level)

‘DHIS 2 is managed centrally, and there is a central server at headquarters; our headquarters staff can change settings and add or remove variables based on users’ needs.’ (Participant 4; Female; Regional level)

‘We have a technical working group and subgroup responsible for developing various documents, including HIS policies and strategies, in consultation with our technical agencies and lower structures HIS.’ (Participant 5; Female; Regional level)

‘At the regional level, people coordinate the HIS programme and ensure that HIS activities are up and functional across all the districts in their territory; they also have a responsibility to ensure that health workers are trained on HIS so that they can generate quality data.’ (Participant 14; Female; Regional level)

‘At the district-level, we have district health information system officers. These are staff who are mandated to ensure that HIS activities are implemented. They are the actual implementers of strategies and various data collection tools, and coordinate HIS at the district-level.’ (Participant 14; Female; Regional level)

Factors that impact the implementation of health information systems: Some participants indicated that data are used poorly in Namibia, especially at higher critical levels. Programme managers were trained in DHIS2, indicators, and data use and supported by creating profiles on DHIS2 to access data. In addition, a few stated that routine health data are not adequately used for decision-making and budgeting in the MoHSS. The key issue seemed to be the historical political influences on financial management.

Managers stated that some districts have poor Internet connectivity, which delays the routine flow of health information. These challenges result in late reporting, which is exacerbated by staff shortages and a lack of transportation to bring paper-based reports to the DHIS Office, where they are then captured into DHIS2. Other managers cited DHIS2 technical glitches, especially towards the end of the month. Most participants noted that Namibia’s HIS is fragmented, with multiple parallel systems operating alongside the public DHIS2.

The challenge with multiple systems is interoperability, and privately owned information systems have high annual licensing fees. The standalone programmes were preferred because they generated relevant information according to their needs. Managers lamented these donor-funded systems because they had their own agenda, which was not congruent with the ministry’s.

Managers find it time-consuming to gather information from various systems and manually consolidate it to make decisions regarding child health. The data regarding children obtained from systems other than DHIS2 includes several children with TB and HIV, as this information is collected from the Electronic Patient Management Information System (EPMIS) and the Electronic Tuberculosis Register (ETR).

Some participants indicated that they often receive poor-quality data from health facilities. Most data need to be complete and accurate. This makes it difficult for managers to make informed decisions in a timely manner. Some participants indicated a lack of capacity in advanced software operations of DHIS2. One manager lamented the public health sector in Namibia’s dependency on outsourced HIS technical expertise, highlighting its high cost and the lack of sustainability.

Other participants indicated that inadequate human resources hinder the effective use of RHISs. In this instance, the high staff turnover among HIS officers causes delays in submitting data to higher levels and compromises quality. There was also a shortage of skilled workers at the district and national levels:

‘Decision-makers and policymakers do not appear to need data because budgeting is not based on data but on past expenditures, political influence, or resource availability, so the use of information is weak in Namibia.’ (Participant 15; Male; National level)

‘We experience poor internet connectivity in our district. Because DHIS2 is a web-based system, we are unable to capture data when the internet is poor, so data will not be available for the next level.’ (Participant 1; Male; National level)

‘The late reporting of routine health data varies from month to month. Sometimes, reports are late for 3 to 5 days. This is due to staff shortages and a lack of transport to bring monthly summary forms to the DHIS Office, especially peripheral health facilities.’ (Participants 7; Male; Regional level)

‘The health information system in Namibia is fragmented. Programmes such as TB are captured on ETR, HIV patients are captured on EPMIS, and pharmacies have their system, PMIS which is mainly funded by donors based on their goals. All these systems are not interoperable with DHIS2.’ (Participant 13; Female; District level)

‘You must understand that donors fund most of these systems and must design something to address their objectives and programme goals.’ (Participant 15; Male; National level)

‘Sometimes, you will find a huge difference when you compare figures from one month to another, making it difficult to use those data with some variables missing.’ (Participant 1; Male; National level)

‘The health statistics report is shocking. The last one was in 2013, so if you use the information to guide decision-making and resource allocation, how can the Ministry of Health be behind seven years in generating an annual health statistical report? This means the decisions are inaccurate because they are based on old data.’ (Participant 14; Female; Regional level)

‘HIS officers at the district-level have a high workload as they are also engaged with other duties, such as disease surveillance.’ (Participant 5; Female; Regional level)

‘We also have a shortage of skilled technical staff at the national level who can support the district health information system officers; there are fewer than five at the national level.’ (Participant 5; Female; Regional level)

A road map for routine health information systems in Namibia: Some participants mentioned that plans are underway to establish a digital platform for capturing patient data. The Ministry of Health in Namibia has developed an Electronic Health Strategy (e-Health Strategy) to guide the implementation of a digital health platform. According to the plan, they will begin with a billing module that is currently being piloted in two hospitals.

Most of the district and region managers supported the introduction of the Electronic Health Record for capturing data on child health programmes during each visit; however, they were unaware of plans for a digitised platform. They also indicated a need to introduce DHIS2 at the point-of-care to support data entry and analysis at the health facility level.

Some managers suggested various HIS systems should be intergrated into one central HIS system so that DHIS2 users can log in to only one system and generate data. This will reduce the time users spend searching for information from different sources.

System integration is part of MoHSS’s future. Managers at the national level indicated plans to build capacity among healthcare professionals and integrate all HISs into DHIS2, as well as create a data warehouse that will enable data to be accessed from a central point, allowing systems to share information.

On the other hand, a few participants suggested incorporating HISs into the curricula of institutions of higher learning that train health professionals. Participants emphasised the need for a regulatory framework for HISs in Namibia. Therefore, protocols and policies should clarify the roles and functions of different key players:

‘The Ministry of Health is piloting a digital health information platform at two hospitals, Katutura Hospital and Windhoek Central Hospital, which will be paperless.’ (Participant 15; Male; National level)

‘Recently, we developed an e-Health Strategy with a specific focus on guiding the implementation of the E-Health project, a digital platform in the Ministry of Health.’ (Participant 14; Female; Regional level)

‘If systems such as EPMIS and ETR can be integrated into DHIS2 under one system, it will make it easier and reduce the time I spend searching for data from different systems.’ (Participants 7; Male; Regional level)

‘Information systems introduced in Namibia should be interoperable with DHIS2, and data can be viewed and analysed using one platform.’ (Participant 13; Female; District level)

‘Plans are underway to integrate all systems in Namibia, and we are currently engaging a company to explore the possibilities and eventualities of integrating those different systems into DHIS2.’ (Participant 14; Female; Regional level)

‘We have engaged with departmental partners to ensure that we build a local training academy for DHIS2 to build a local capacity for sustainability purposes; we sometimes depend on external institutions.’ (Participant 14; Female; Regional level)

‘The training institutions must include it in their curriculum so that health professionals understand how to generate and use data at the point-of-care.’ (Participant 12; Female; District level)

Measures for improvement of the routine health information system: Participants recommended strengthening regular support supervision for lower-level structures, including providing constructive feedback on the performance of the child healthcare programme. They emphasised the need to enhance data management processes and promote the use of information. In addition, increasing the visibility of leadership was highlighted as a crucial factor in supporting effective data management and utilisation.

Routine data collection tools on child health need to be improved, and additional data elements for services provided in health facilities are required to address the information needs of the DHIS2 users. These data elements include information to capture the zinc supplements and information on the deworming of children under 5 years old:

‘We need information on Zinc and deworming with Albendazole to be captured in routine health data for children under five years old because there are places like northern regions where we have problems with worm infestations. This way, we can know how many children were provided with those supplements.’ (Participant 12; Female; District level)

 Discussion

This study provides critical insights into how healthcare managers in Namibia understand and utilise RHISs for child health programme management. The theoretical framework provided a guide for researchers in examining and discussing key concepts in the study, which included the essential role of foundational inputs – information communication and technology (ICT) infrastructure, skilled personnel, policy frameworks, and standardised data elements – in effective RHIS implementation. These findings align with Tulu, Demie and Teshome (2021), who emphasised that health worker competency, data infrastructure and availability of HMIS guidelines fundamentally determine routine health information utilisation.

A significant finding reveals Namibia’s current reliance on a hybrid system that combines paper-based facility level reporting with DHIS2 for the management of aggregate data at the district, regional and national levels. While this approach enables cross-facility comparisons and standardised reporting, it creates substantial inefficiencies and data quality concerns. The slow implementation of DHIS2 at the point-of-care level represents a critical challenge, with most facilities continuing to rely on paper-based systems that require manual data entry and transfer to the district level.

This hybrid approach reflects broader challenges in low- and middle-income countries transitioning to digital HISs (Kapepo & Yashik 2018). The MoHSS’ plans for a comprehensive digital platform remain partially implemented, highlighting the gap between policy intentions and operational realities. The persistence of paper-based systems suggests that technological solutions alone are insufficient without addressing underlying capacity, resource and workflow integration challenges.

Healthcare managers demonstrated good understanding of RHIS principles, indicating that knowledge gaps are not the only implementation barrier. However, several systemic challenges also impede effective utilisation of child health data, such as poor Internet connectivity and DHIS2 technical glitches, which create fundamental barriers to real-time data access and system reliability. These technical failures undermine managers confidence in the system and limit timely decision-making capabilities.

The lack of integration between various HISs creates data silos that hinder comprehensive oversight of child health programmes. As De Mello et al. (2022) emphasised, without standardised interoperability protocols, HISs remain isolated, limiting their collective value for decision-making. The lack of HIS interoperability is caused by the absence of comprehensive HIS legislative frameworks, which results in ambiguity in system requirements, data standards and integration protocols. This regulatory vacuum allows for inconsistent implementation approaches and limits the effectiveness of accountability mechanisms.

A critical finding reveals that decision-making at strategic levels within the MoHSS remains ‘historical’ and subject to political influences rather than being derived from routine health data. This observation warrants deeper analysis, as it suggests that the improvements to RHISs should be accompanied by capacity-building initiatives, as it may have a limited impact without addressing underlying governance and decision-making cultures.

The influence of political considerations on health budgeting decisions represents a significant barrier to data-driven management. This finding indicates that improving RHIS effectiveness requires not only technical enhancements, but also institutional reforms that prioritise evidence-based decision-making. The study identified concerning gaps in data quality assurance practices, with some healthcare managers failing to conduct regular data quality checks. This finding suggests that while managers understand RHIS importance conceptually, they may lack specific technical skills or institutional support systems necessary for effective data management.

Current capacity-building initiatives appear insufficient for developing practical data management skills. The need for standardised training on data quality assessment procedures, audit protocols and SOPs represents a critical capacity gap. This will ensure that all data generated and entered into DHIS2 are of good quality. Good quality data can contribute to reliable estimates of service delivery coverage, effective clinical management at the health facility level and monitoring and evaluating programmes (Seid et al. 2021).

Inconsistent supervisory support and limited feedback to lower-level facilities create a disconnect between data collection and quality improvement. Effective RHIS implementation requires systematic feedback mechanisms that enable continuous improvement of routine health data.

The study revealed unequal access to DHIS2 among managers, and delays in data availability after entry represent significant operational barriers. These access limitations create information hierarchies that may disadvantage certain management levels and geographic areas, potentially exacerbating existing health system inequities.

The need for real-time data access is particularly critical for child health programmes, where timely interventions can significantly impact outcomes of improved data use by managers for programme monitoring and resource allocation. Current system configurations that create delays between data entry and availability limit managers’ ability to respond quickly to emerging issues or trends.

While managers reported using routine health data for operational decisions such as vaccine ordering and immunisation coverage monitoring, significant gaps exist between stated use and actual evidence-based practices. This finding is consistent with Abdisa et al. (2022) in Ethiopia, who claimed that 65.5% of public health managers reported using a RHIS for evidence-based decision-making.

Factors such as manager experience, position, training and data quality knowledge significantly influence actual utilisation patterns.

The study highlighted significant skill mismatches in HIS personnel, representing a critical structural challenge. Effective RHIS implementation requires strategic deployment of human resources, ensuring that technical skills are aligned with functional demands at various levels of the system. The finding that different healthcare levels have distinct data management functions, yet lack appropriately skilled personnel, underscores this issue. The study therefore recommends comprehensive workforce planning that facilitates optimal deployment based on technical competencies and specific functional requirements.

The study revealed discrepancies between child health services provided and data captured in RHISs, indicating that current systems may not fully address managers’ information needs. Missing data elements and imprecise reporting to higher levels suggest that the design of RHISs may not adequately capture the complexities of child health service delivery.

As Amouzou et al. (2021) emphasised, effective RHISs must be responsive to country-specific information needs and adaptable to evolving child health indicators. This requires ongoing dialogue between system designers, implementers and users to ensure that the information needs of decision-makers are addressed.

Strengths and limitations

The study was limited to assessing the understanding and experiences of healthcare managers on RHISs and the use of information on child healthcare. It was conducted in one context, ||Kharas region, with healthcare managers, but some from the national authority. The limitation could have been reduced if participants were recruited from the different areas in Namibia. However, the study assumes that the findings would be similar in contexts and characteristics.

 Conclusion

This study demonstrates that effective RHIS implementation for child health programmes requires more than technical solutions and demands comprehensive approaches that address infrastructure, capacity, governance and institutional culture simultaneously. Even though Namibian healthcare managers possess the conceptual foundation for RHIS utilisation for child health management, the study revealed a significant disconnect between data availability and utilisation, highlighting the need for sustained commitment to addressing the complex, interdependent challenges identified in this research. The research demonstrates that RHIS effectiveness depends not merely on technical functionality but on the combination of human resources, technological infrastructure, policy frameworks and institutional culture.

The findings highlight how challenges within RHISs compound across levels of the health system. Technical infrastructure limitations (poor connectivity and system glitches) undermine managers’ confidence in data reliability, which in turn reduces utilisation, even when systems function correctly. The absence of comprehensive legislative frameworks creates implementation ambiguity that manifests in inconsistent data quality practices and fragmented system integration. Most critically, the influence of political factors on strategic decision-making suggests that technical improvements alone cannot achieve evidence-based health programme management without addressing underlying governance.

Based on the evidence, three priority areas could be considered for interventions: system reliability and accuracy by addressing technical glitches, and providing equitable access to DHIS2 across all levels. Capacity-building and information use can be enhanced by developing practical data management competencies through revised training approaches, establishing clear standards, implementing effective feedback mechanisms and creating incentive structures.

There is a need to establish comprehensive legislative frameworks that mandate interoperability standards, data quality requirements and evidence-based planning processes. The study also recommends sequential implementation aligned with available resources and institutional capacity. Success will ultimately be measured not by the sophistication of information systems themselves, but by their contribution to improved child health outcomes through enhanced programme effectiveness, better resource allocation and more responsive health service delivery.

In conclusion, to utilise RHISs for child healthcare, there is a need for holistic, multi-dimensional approaches rather than isolated solutions. Hence, success depends on simultaneously addressing infrastructure, human capacity, governance structures and organisational culture.

 Acknowledgements

This article includes content that overlaps with research originally conducted as part of Rauna N. Namukwambi’s doctoral thesis titled ‘Strategies for utilisation of Routine Health Information System (RHIS) for management of child healthcare in Namibia’, submitted to the Department of Health Studies, University of South Africa in 2024. The thesis was supervised by Mokholelana M. Ramukumba. Portions of the data, analysis and/or discussion have been revised, updated and adapted for journal publication. The original thesis is publicly available at: https://uir.unisa.ac.za/items/90ca4015-1b9d-4a82-96d1-bbe8f52ab7d4. The author affirms that this submission complies with ethical standards for secondary publication, and appropriate acknowledgement has been made of the original work.

Competing interests

The author reported that they received funding from the University of South Africa which may be affected by the research reported in the enclosed publication. The author has disclosed those interests fully and has implemented an approved plan for managing any potential conflicts arising from their involvement. The terms of these funding arrangements have been reviewed and approved by the affiliated university in accordance with its policy on objectivity in research.

 CRediT authorship contribution

Rauna N. Namukwambi: Conceptualisation, Formal analysis, Investigation, Methodology, Project administration, Writing – original draft, Writing – review & editing. Mokholelana M. Ramukumba: Supervision, Writing – review & editing. All authors reviewed the article, contributed to the discussion of results, approved the final version for submission and publication, and take responsibility for the integrity of its findings.

 Data availability

The data that support the findings of this study are available from the corresponding author, Rauna N. Namukwambi, upon reasonable request.

 Disclaimer

The views and opinions expressed in this article are those of the authors and are the product of professional research. They do not necessarily reflect the official policy or position of any affiliated institution, funder, agency or that of the publisher. The authors are responsible for this article’s results, findings and content.

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How to cite this article: Namukwambi, R.N. & Ramukumba, M.M., 2026, ‘Managers’ perspectives on using routine health information systems for effective child healthcare programmes in Namibia’, South African Journal of Information Management 28(1), a2060. https://doi.org/10.4102/sajim.v28i1.2060