Examining the development and utilisation of Community-Based Health Information Systems (CBHIS) in Africa: A Scoping Review

Introduction The community-based health information system (CBHIS) is a vital component of the community health system, as it assesses community-level healthcare service delivery and generates data for community health programme planning, monitoring, and evaluation. CBHIS promotes data-driven decision-making, by identifying priority interventions and programs, guiding resource allocation, and contributing to evidence-based policy development. Objective This scoping review aims to comprehensively examine the use of CBHIS in African countries, focusing on data generation, pathways, utilization of CBHIS data, community accessibility to the data and use of the data to empower communities. Methods We utilised Arksey and O'Malley's scoping review methodology. We searched eight databases: PubMed, EMBASE, HINARI, Cochrane Library, Web of Science, Scopus, Google Scholar, and grey literature databases (Open Grey and OAIster). We synthesized findings using a thematic approach. Results Our review included 55 articles from 27 African countries, primarily in Eastern and Southern Africa, followed by West Africa. Most of the studies were either quantitative (42%) or qualitative (33%). Paper-based systems are primarily used for data collection in most countries, but some have adopted electronic/mobile-based systems or both. The data flow for CBHIS varies by country and the tools used for data collection. CBHIS data informs policies, resource allocation, staffing, community health dialogues, and commodity supplies for community health programmes. Community dialogue is the most common approach for community engagement, empowerment, and sharing of CBHIS data with communities. Community empowerment tends towards health promotion activities and health provider-led approaches. Conclusion CBHIS utilizes both paper-based and electronic-based systems to collect and process data. Nevertheless, most countries rely on paper-based systems. Most of the CBHIS investments have focused on its digitization and enhancing data collection, process, and quality. However, there is a need to shift the emphasis towards enabling data utilisation at the community level and community empowerment.

databases (Open Grey and OAIster).We synthesized findings using a thematic approach.

Results
Our review included 55 articles from 27 African countries, primarily in Eastern and Southern Africa, followed by West Africa.Most of the studies were either quantitative (42%) or qualitative (33%).Paperbased systems are primarily used for data collection in most countries, but some have adopted electronic/mobile-based systems or both.The data flow for CBHIS varies by country and the tools used for data collection.CBHIS data informs policies, resource allocation, staffing, community health dialogues, and commodity supplies for community health programmes.Community dialogue is the most common approach for community engagement, empowerment, and sharing of CBHIS data with communities.Community empowerment tends towards health promotion activities and health provider-led approaches.

Conclusion
CBHIS utilizes both paper-based and electronic-based systems to collect and process data.Nevertheless, most countries rely on paperbased systems.Most of the CBHIS investments have focused on its digitization and enhancing data collection, process, and quality.However, there is a need to shift the emphasis towards enabling data utilisation at the community level and community empowerment.

Plain Language Summary
For community health services and systems to work well, health managers and other data users, including policy and decision-makers, need a community-based health information system (CBHIS) that produces reliable and timely information on how well these services are working and that supports the use of CBHIS data to improve community health service delivery.This scoping review aimed to explore the use of CBHIS in African countries.It focused on data generation, pathways, use of CBHIS data, community data access, and use of CBHIS data to empower communities.The review authors collected and analysed all relevant studies to answer this question and found 55 articles from 27 African countries.The review found that most countries use paper-based information systems for data collection, while some have adopted electronic and digital systems.CBHIS also collects information on human resources, medicines, and supply systems.CBHIS data are used to guide policy development, allocate resources, track commodities supplies, staff for community health programmes and organise community health dialogues.Community dialogue is the most common approach for engaging, empowering, and sharing CBHIS data with communities.Community empowerment involves activities that promote health and health provider-led approaches.There is a need to focus on enabling the use

Introduction
Community Health Systems (CHS), defined as the interface between community systems and the formal health system, is the most accessible, equitable, cost-effective, and efficient approach to improving access and coverage of health services in a continuum of the primary health care (PHC) system 1 .A strong CHS is critical for delivering accessible, quality, cost-effective preventive and treatment services, including emergency care 2 .
The Astana Declaration on PHC in 2018 fostered a renewed global interest in strengthening CHS in the context of the Universal Health Coverage (UHC) and other Sustainable Development Goals (SDGs).Integrating community health approaches in health systems is now considered paramount 3 , as CHS can help monitor population-level health system performance, track key indicators related to UHC and other healthrelated SDGs, and enhance the quality of health information 4 .The success of the CHS in handling global crises, such as the Ebola epidemic in West Africa and the COVID-19 pandemic, further emphasizes its importance in providing essential health services at the community level and supporting public health emergency preparedness and response 2 .CHS is thus seen as a crucial aspect of PHC, and its strengthening is essential for achieving UHC and other health-related SDGs 5 .
A community-based health information system (CBHIS) is a vital system that encompasses information about the collection and flow of data, assessment and enhancement of data quality, and utilization of community health data.It is essential for ensuring accurate data collection to support governance and management of CHS and decision-making at local, sub-national, and national levels 4,6,7 .CBHIS data also enable advocacy for vulnerable populations 6 , serve as an early warning alert and response (EWAR) tool, support case management and community health units/posts, enable health trend analyses, and reinforce the communication of health challenges to diverse groups 8 .
The four fundamental functions of CBHISs are data generation, data compilation, analysis and synthesis, and communication and use 8 .CBHISs gather health and other relevant data, ensure its quality, relevance, and timeliness, and transform it into useful information for health-related decision-making.However, the CBHIS requires critical health system inputs, including human resources (community health workers), budgetary allocation, and day-to-day operational management, to function efficiently 4,5,8,9 .Many low-and middle-income countries (LMICs) face challenges in establishing and maintaining CBHIS due to insufficient government funding 4 , leading to significant gaps in community-level health data quality 5,6,10 , and thus limiting the demand and utilisation of CBHIS in decision-making processes 11 .This underutilization of CBHIS data in decision-making processes can be attributed to fragmented community-based reporting systems 10 , lack of coordination between data producers and users 12,13 , multiple parallel information subsystems 13 , and variations in the decentralization of community health decisions 14 .Furthermore, limited integration of CBHIS with the formal Health Management Information System (HMIS), insufficient funding for the CHS 2,4,6,15 , and contextual factors beyond technical aspects of data processes and organizational aspects impact the use of evidence in the CHS 13,14 .
Although several African countries have embraced digital platforms, most countries (71 %) continue to rely on paper-based systems to collect CBHIS data 1,2 .Several infrastructural constraints, including limited access to cell phones, stable electrical power supplies, and mobile networks, impede the adoption of digital systems 10,13,[16][17][18] .However, some countries, such as Malawi, Zambia, Ghana, and Kenya, have successfully adopted simple feature phones with simple SMS-based reporting systems, enabling real-time data transmission to all healthcare systems 4,19 .
Several African countries have recently invested in enhancing their CHS and strengthening their CBHIS systems 20 .These efforts have included the digitisation of existing CBHIS systems to improve community health programs and work towards providing universal access to PHC services 21 .However, most CBHIS systems in these countries are partner-driven, program-specific, and heavily reliant on donors' and partners' financial and technical support, as evidenced in the Democratic Republic of Congo (DRC), Egypt, Namibia, and Kenya 1,10,17 .As a result, the landscape of CBHIS data is disjointed and fragmented, failing to integrate with the national HMIS 10 .
There are limited reviews on CBHIS in Africa.A review by Mekonnen et al. 4 examined the current status and implementation challenges of CBHIS in LMICs-Africa but did not focus on CBHIS data processes, utilisation of CBHIS data on health system decision-making, or community access to CBHIS data and community empowerment.Our review focuses on these aspects of the CBHIS.We aim to address the gap in these aspects and inform efforts to enhance the CHS, ultimately contributing to improved community health service coverage and tracking progress towards UHC and other health-related SDGs.

Methods
This scoping review adopted the Arksey and O'Malley's Framework 22 to comprehensively examine the development, implementation, and utilization of CBHIS in Africa.This framework guided the methodological processes for our review.We adhered to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) reporting guidelines 23 .Our review was registered in the Open Science Framework 24 .

Eligibility criteria
We selected eligible studies using the Population, Concept, and Context (PCC) framework recommended for scoping reviews.

Amendments from Version 1
We have revised the manuscript based on the reviewer's feedback, corrected the typo, and added missing in-text citations.No major changes were made to the manuscript.

Information sources and search
We developed the search strategy in consultation with a health research librarian.An initial search was conducted in July 2023, and an updated search in November 2023.Seven databases were searched: PubMed, Embase, HINARI, Cochrane Library, Web of Science, Scopus, and Google Scholar.We also searched grey literature on open grey databases and handsearched the references of included studies to identify additional literature.We limited our search to articles published in English between 2000 and 2023.The PubMed search strategy is presented in Additional File 1 (see Extended data, 25 ).

Study selection
We exported references to the EndNoteX7 database, and duplicates were removed.Two independent reviewers performed study selection over two stages: title and abstract review and full-text review against the predefined eligible criteria, using Covidence.All disagreements were resolved by discussion or consulting with authorship team members for a consensus.Studies that met the inclusion criteria were selected for data extraction and charting.

Data items and charting
A data extraction and charting form was developed and pilot-tested jointly with the research team to determine which variables to extract (Additional File 2) (see Extended data, 25 ).We extracted data on the following aspects: general study characteristics; sources of CBHIS data; data generation; pathways through which data is processed; utilisation of CBHIS data; and community accessibility to CBHIS data and empowerment.Data was extracted and exported from Covidence into Microsoft Excel software.One reviewer extracted data, and reviewers independently conducted quality checks of the extracted data.We resolved discrepancies by discussion between authors or consulting senior reviewers for a consensus.

Synthesis of results
We synthesized the findings using a thematic approach commonly used in scoping reviews.We followed the PRISMA-ScR reporting guideline to present our findings.

Selection of sources of evidence
Our search strategy yielded 7,101 records, of which 362 duplicates were excluded.We screened 6,762 titles and abstracts and excluded 6,498 articles.We screened 264 articles and included 55 articles in this review.The PRISMA flow diagram of the selection process and summary of the search results is provided in Extended data, 25 .

Characteristics of sources of evidence
We synthesized 55 studies from 27 African countries, primarily Eastern and Southern Africa, followed by the West African region.Of these, 52 were research studies, and only three were project/programme reports.Most studies were quantitative (42%), followed by qualitative studies (33%).Table 1 presents the characteristics of the studies, including country, study design, and topical focus.A summary of all key findings is provided in Extended data, 25 .

CBHIS data generation.
CHWs are crucial for collecting CBHIS data.Included studies used various titles to describe CHWs based on their cadres and country of origin, including health extension workers (HEWs), community health volunteers (CHVs), community health extension workers (CHEWs), village pioneers, Health Surveillance Assistants (HSAs), community-based health workers (CBHWs), and village health teams (VHTs) (Table 2).This paper uses CHWs as an allencompassing term to cover all these designations for ease of reading and clarity.Table 2 summarises the CBHIS data collectors, standard data collection tools, and type of data collected.

CBHIS data pathways.
CHWs primarily use paper-based tools for data collection 38,42,45 ; however, some countries have adopted electronic-based systems (eCBHIS), such as mobile phone applications and mHealth tools [41][42][43][44][45][46][47][48][49][50][51][52][53] ).In some instances, CHWs must use both manual and eCBHIS methods, as observed in Ethiopia 47,54 and Ghana 42 .Additionally, mobile technology has been utilized to collect community health data, such as in Kenya, where the mHealth application has been used to collect non-communicable diseases, particularly diabetes and hypertension 55 , and a simple short message service (SMS) -based reporting to support the supply chain management 50 .A mobile-based eCBHIS was implemented in Zambia to monitor commodities stock levels 52 .
In paper-based systems, CHWs record household visits and activities in standardized Federal/National Ministry of Health (MoH) service delivery registers, which are then collated to complete monthly report forms.These report forms their respective catchment areas are then submitted to the supervisors, who aggregate the data in paper-based standardized MoH forms that are in turn submitted to the subnational office (sub-county, county, district, or regional) for digital entry into the web-based national health information systems, the District Health Information System (DHIS2) 26,[56][57][58][59][60][61][62] .Notably, digital entry of the paper-based systems into the DHIS2 database happens at the sub-national level 1,11,32 .However, the lack of harmonization of CHW data collection tools and HMIS forms has been identified as a barrier to data capture in HMIS during data submission 33,63,64 .
In electronic-based systems, data on household visits or program-specific indicators are entered electronically by CHWs into electronic forms on the applications installed on their tablets or mobile phones and submitted electronically to the organization's database or sub-national or national HMIS, DHIS2 27,37,41,51,52 .The electronically aggregated data in the HMIS are made visible and accessible to CHWs supervisors, health managers, and data managers, who review data, trace data errors in data capture, track and analyse data, as well as send electronic feedback notes to CHWs 41,51,52 .Some applications have built-in data validation to ensure the completeness of data 41,51 .However, in other instances, CBHIS data are directly conveyed to the department of funders, bypassing health facilities for electronic database recording 60 .
CBHIS data review/use meetings are intended to also create effective feedback mechanisms across healthcare service levels 1 .However, the implementation of these mechanisms was often limited to human resource constraints, as observed in Namibia, whereas in DRC, feedback mechanisms were reported to function better in areas with partner support, and in Uganda, feedback was reliant upon the provision of supportive supervision 1 .
The data flow for the CBHIS and feedback mechanisms varied depending on the country and tools used for data collection, whether paper-based or electronic-based.
Utilisation of CBHIS data.At the national/federal level, the division/department responsible for health information systems receives community health data from sub-national levels, which is then transmitted to the division responsible for community health services within the Ministry of Health (MoH) 1 .The division of community health services utilizes the data to track the progress of community health programs, create annual health sector performance reports, formulate policies, and provide feedback to decentralized levels.Ideally, all levels of the health system, including community, sub-national, and national, should review and utilise CBHIS data 1 .However, data producers and users often lack the core competencies of data analysis, interpretation, and synthesis, which, in turn, limit the demand and use of data in decision-making processes 1,11,65 .
CBHIS data is reportedly utilized by various stakeholders, including government entities, NGOs, CBOs, funders, health facilities, community health committees, and healthcare professionals at different levels, to guide decision-making, policy decisions, staffing, commodities supplies, and resource allocation for community health programmes 26,29,52,57,64 .In Ethiopia and Malawi, CBHIS data is used to support health extension services 30,54,61,66,67 , whereas, in South Africa, CHWs use it for community activities and referrals to service providers 46 .In Namibia, the MoH uses it to inform future community health programmes 1 , while health managers in Ethiopia use it to monitor and evaluate community health services 54,61 .In Kenya, CBHIS programme data is used to assess interventions 68 and design new ones, and in South Africa, regional coordinators use it for programme tracing and planning 60 .CBHIS data also supports collective activities such as community dialogue in Kenya, South Africa, Malawi, and Ethiopia to address the prevalent challenges in catchment areas/community units 12,36,56,58 .
Moreover, CBHIS data is utilized in various ways by CHWs and healthcare providers in Ethiopia, Kenya, South Africa, Malawi, and Zambia, such as tracking defaulters for health services and scheduling house visits 12,33,37,46,68 , assessing the utilization and coverage of maternal and newborn care services 69 , institutional delivery of immunization 59,[69][70][71] , monitoring trends in health service delivery and disease prevalence, and implementing mitigation strategies for disease outbreaks 12,63 .CHWs also use this data to monitor community health supplies and commodity stock levels 33,50,52 and plan health resources at the sub-national and national levels 28,38,41 .While CBHIS data is crucial for improving community health programs and outcomes, challenges remain in effectively using data at the community level other than for reporting purposes 12,26 .

Accessibility of CBHIS data and community empowerment.
Community dialogue is the most widely used strategy for community engagement, empowerment, and access to CBHIS data.Studies conducted in Ethiopia, Kenya, Malawi, and South Africa have reported that community dialogue brings together community members, leaders, representatives, community health committees, CHWs, and health providers to share CBHIS data for priority setting, planning, implementation, evaluation of health interventions/programmes, and consensus in addressing specific community health issues 36,46,[56][57][58]68,69,72 .
CHWs collaborate with community health-level committees to initiate community dialogues.In addition to community dialogue, community members can access CBHIS data through wall charts/chalkboards displayed in community units, health centers, and clinics 26,32,33 .However, a multi-country study across 17 West and Central African countries revealed the lack of CBHIS data accessibility to community members beyond the CHWs, impeding community participation in data utilization 73 .The included studies have attributed improved health indicators, health service utilization, and health practices, including improved sanitation and hygiene practices, drug adherence, reduced stigma, increased family planning methods, immunization, and maternal delivery to community dialogues 12,36,68 .Nonetheless, evidence directly linking community dialogue to improving specific health indicators, health status, and health practices is limited.Community empowerment in community dialogues tends towards health promotion activities 36,[56][57][58] .

Discussion
CHS is a crucial aspect of PHC and a vehicle for achieving UHC and other global health SDG priorities.To effectively deliver community health services, a functional and practical CBHIS is essential for countries to track their progress toward PHC and UHC.This scoping review aimed to synthesise evidence on the current practices of CBHIS data generation, data pathways across different health system levels, utilisation of CBHIS data, and accessibility of CBHIS data to communities to empower communities in African countries.The majority of articles reported on CBHIS data generation and use.Most CBHIS utilize paper-based systems, although some countries have adopted electronic/digital systems (eCBHIS) to record and transmit data to sub-national and national HMIS; data pathways vary by country.Multiple stakeholders utilize CBHIS data for decision-making, including policymaking, resource allocation, staffing, programme evaluations, and informing community health programmes and dialogues.Community dialogue is the most common strategy for community engagement, sharing CBHIS data, and empowering communities.
CHWs are crucial in generating data for the CBHIS.Different cadres of CHWs have distinct roles and include data collection, management, and dissemination.Although most countries rely on paper-based systems for data collection, some use electronic-based systems 1,37,[45][46][47] , or a combination of both 47,54 .However, reported challenges included a lack of standardized data collection and compilation tools 1,11 , inadequate personnel competencies 37,51,52 , and duplicate data entries in paper-based and electronic forms 1 , can lead to limited data collection and loss, negatively impacting data quality.As countries transition to digitized systems, it is crucial to provide regular technical and supportive supervision to CHWs to tackle user-related and system-related challenges they face with eCBHIS.Continued training for CHWs on basic Information Communication Technology (ICT) skills, digital tools, and data analysis and use, is still vital to ensure timely, accurate, and complete data entry into eCBHIS 4,47,65,74,75 .
The contextual adoption of mobile technology can help with the transition e.g., simple feature phones with simple SMS-based reporting systems have been successfully adopted in Ghana, Kenya, Malawi, and Zambia 4,19 .Our review revealed an absence of policy guidance concerning data security and privacy aspects for both paper-and electronicbased CBHIS systems 11,41 .For instance, CHWs were obliged to store paper-based data in their homes owing to insufficient storage, leading to lost data forms and the potential breach of confidentiality 11 .To enhance the security and privacy of CBHIS data in the healthcare sector, countries transitioning to digital systems should develop or update their eCBHIS policy frameworks.These frameworks should address the gaps in data security and privacy, safeguard community data and guide the implementation of data protection principles in eCBHIS 1,76 .
CBHIS generates large amounts of data on healthcare services and population health, presenting opportunities for data-driven decision-making in the CHS.While efforts to enhance CBHIS have primarily focused on digitalization and improving data collection and quality, particularly at the community level, there is a disproportionate emphasis on the technical aspects of enabling data use 74,77 .The ultimate goal of CBHIS is to translate data into action, address health challenges, and improve the access and quality of community health services 77 .We indicate that CBHIS data can be utilized in health system and service outcomes, health resource allocation, and administrative decisions 45,54,57,59,66,78 ; however, there was limited evidence on the impact of the data-driven decision-making approach in the included studies.Various challenges impede the utilisation of CBHIS data, such as fragmented reporting systems 13 , poor coordination between data producers and users 12,13 , variations in the decentralization of community health decisions 14 , and limited capacity of data producers and users and utilize the data for decision-making 1,11,65 .
To ensure sustainable demand and use of data in decisionmaking, it is essential to develop the capacity of data producers and users in core competencies, such as data analysis, interpretation, and synthesis, at all levels of the health system, including the CHS.Investing in capacity-building for data producers and users on critical competencies can facilitate the functioning of CBHIS 79 .Lippeveld (2017) identified many barriers to data use related to organizational and behavioural factors 77 .The information use culture can act as both a barrier 12,26 and a facilitator 80 in data utilization.Negative organizational behaviour, such as the pressure senior health managers exert on providers to meet unrealistic service delivery targets, has contributed to false reporting and the denial of existing service delivery problems.Conversely, community-led monitoring of health service delivery data has been demonstrated to promote positive organization behaviour by enhancing the culture of information 77,80 .
Community participation in health information generation and dissemination has been shown to increase community engagement and health information sharing and foster health system responsiveness through community activism 20,80-82 .However, community members face barriers to accessing and using health information.A multi-country study across 17 West and Central African nations found that community members lacked access to CBHIS data beyond that of CHWs, which hindered their participation in data utilisation 73 .This limits the involvement of end-users of care in developing interventions that align with local needs and are informed by local knowledge and priorities in a more effective and transformative way that helps empower marginalized and vulnerable population groups.Community data dissemination has shown positive results in various initiatives 80,83,84 .For instance, a randomised field experiment in nine districts in Uganda revealed that granting communities access to data increased their involvement, accountability, and community-led monitoring of PHC services 80 .Consequently, service utilisation and health outcomes improved significantly.This intervention emphasises the magnitude of community participation and a bottom-up approach to enhancing CHS service delivery and health outcomes.Integrating this approach with a structured top-down approach can lead to even better results 80 .
The results of our review carry with them some implications.The CHS require the availability of good-quality data, however, this on its own is insufficient to support the use of data in the CHS and broader health systems management decision-making.Although studies included in our review reported the utilization of CBHIS data, there are deficiencies in comprehending the extent to which it's used or integrated in decision-making processes and policy formulation.The health authorities and practitioners may need to consider implementing interventions that explicitly focus on improving the link between CBHIS data collection and the use of data for decision-making.CHS activities, policies and guidelines may need to focus on capacity building of data producers and users in data management and data use competencies, including analysis, synthesis, interpretation, critical review of data, and data-informed decision making 1,11,65 .In addition, there is a need to focus on organizational culture and practice of monitoring, evaluation, and communication of data use interventions, and that encourages health managers, frontline health providers and users of health services, to take responsibility for using data to inform decision making 7,77,80 .
Our review suggests that there is limited access to CBHIS data beyond community dialogues and wall charts in community health units.Accessibility of CBHIS data to the community is essential to foster community participation in community health activities and accountability.An experimental study on information intervention in Uganda shows that disseminating data to community members can enhance community participation in CHS services, empower them and promote accountability of health providers at the community level 80 .However, there is a gap in studying the impact of community participation and empowerment on health outcomes.
There is a large and diverse body of literature on CBHIS data generation/production (data sources, data management, information products and dissemination) and systems performance (data quality and data use).However, there is a research gap on the links between data collection and data use, and between data use and systems impact, as well as components needed for the design and evaluation of CBHIS, to effectively support health system management decision-making.Implementation research approaches may also help understand data-driven decision-making mechanisms in operational settings 7 .

Strengths and limitations
We conducted a systematic and thorough evaluation of the existing literature.Our approach involved conducting a comprehensive literature search, employing duplicate article screening, and selecting articles by independent reviewers, with senior reviewers verifying and ensuring quality control.However, our review had some limitations.First, we only included published articles and grey literature, which may have led to the exclusion of other relevant documentation on CBHIS.Second, we did not consider non-English studies or grey literature, which could have resulted in the exclusion of articles from non-English-speaking African countries that may have been relevant to our review.

Conclusion
While there is a focus on enhancing data collection, processing, quality, and digitization of CBHIS, there is a need to shift the emphasis towards enabling data utilisation at the community level and community empowerment.Community involvement and empowerment are mainly achieved through community dialogue, but it should move beyond supply-side-driven health promotion activities and enhance demand-driven interventions to foster community accountability and tailor interventions to community needs.Demand-driven initiatives can promote community participation in CBHIS, community empowerment, and health activism.The renewed commitment to PHC presents an opportunity to optimise the functionality of CBHIS and accelerate progress towards UHC and other health-related SDGs.This project includes the following extended data:

Extended data
• Additional File 1 (information search strategy)

• Additional File 2 (data extraction form)
• Additional File 3 (characteristics of included studies).

Title:
The title of the review should be precise and consistent with the problem statement and objectives The title reads: Examining the development and utilization of Community-Based Health Information Systems (CBHIS) in Africa: A Scoping Review.The problem statement and objectives focus on generation and utilization of CBHIS information, leaving out the development of CBHIS, reflected on the title.Authors to consider excluding "development from the title" and thus harmonize the title with problem statement, the objectives, results and discussion.

Scope:
The title states reflects the scope to be the review to be Africa, yet the work reviewed as reflected by results , appear to be Sub Saharan Africa, no single study from North Africa, reflected.

Abstract:
The objective reads "This scoping review aims to comprehensively examine the use of CBHIS in African countries, focusing on data generation, pathways, utilization of CBHIS data, community accessibility to the data and use" The content does not reflect CBHIS pathways.There is need to highlight pathways, or exclude it from the objectives.

Background:
The problem statement is clear, stating why this study was necessary and what it aimed to contribute to the field.The section could end with a very brief statement of what is being reported in the article.

Methods:
The method section has been well written giving sufficient information and elaborating the design of the study including theoretical frameworks applied in data collection analysis.
The inclusion of grey literature is commendable although some reflection on the strength of evidence, given the numerous sources of error involved as compared to scientifically designed works.
Results: Going through the results section, which is well written but the cannot miss to notice the relative over-representation of articles from Kenya, East Africa, and could wonder about some bias in literature access.A statement to demonstrating that articles from the other regions of Africa had equal chance of being included, may be useful.
To help the reader have a glimpse of the achievements and challenges, study type, country where the study was undertaken will be good at the end of the section to have a table or a matrix summarizing the findings based themes or review objectives.Overall, and considering the opening arguments raise the important issue of data infrastructure fragmentation, including through the mixed influence of development partners and donor institutions, it would be useful to understand the extent to which data generated by CBHISs are used (primarily at least) locally and/or domestically and/or regionally/internationally.If this is not reported, then that is also a finding!

Discussion
Secondly, the political nature of data, may be worth considering -issues such as and including how to progress beyond 'naïve rationality' towards fuller views of community data and data use.This is raised explicitly in the paper but deserves more attention.What are the risks, as well as benefits for communities around CBHIS?
Thirdly, there are some powerful statements about data use (and the political nature of data) however it is not clear whether these are findings from the empirical work, this should be clarified (see specific comments, below).Fourth, I was surprised Rwanda does not feature in the findings, considering the expansion of the CHW programme to NCDs.
Finally, the discussion section could be strengthened by 'unpacking' some key concepts (participation, empowerment, accountability etc) and arguments further, please see specific comments.On page 9 for example, the statement 'data pathways vary by country' could be usefully supplemented with additional detail.I would also encourage the authors to balance the 'inward' and 'outward gaze' in the recommendations.The systems and implementation challenges are not just local problems.It follows that it is unlikely that the challenges identified can resolved entirely by front line service providers, particularly CHWs.The Discussion would be usefully balanced with critical reflections on, and recommendations for, national, regional, and international levels.

SPECIFIC COMMENTS Methods
Throughout, minor comment -data is a plural term.1.
A map showing where CBHIS are reported on might be a useful visual representation of the evidence base to consider including.

2.
Page 5 -data items and charting: the data extraction themes are great suggest numbering them to help readers navigate the content.

3.
Page 5: the data extraction theme 'sources of CBHIS data' stated in the methods seems to correspond with 'Characteristics of sources of evidence', although it may correspond with 'general study characteristics'.All other extraction themes are clearly presented and aligned to the methods.The 'sources of CBHIS data' could benefit from being more clearly reported.

Results
Page 5, 'CBHIS data generation' and Table 2: it would be useful to understand whether and how development partner programmes and/or statutory services feature in types of community-based health information.Considering, who are these data (primarily) for. 1.
Page 8: as per the comment, above, the statement 'CBHIS data is reportedly utilized by various stakeholders, including government entities, NGOs, CBOs, funders, health facilities, community health committees, and healthcare professionals at different levels, to guide decision-making, policy decisions, staffing, commodities supplies, and resource allocation for community health programmes' would benefit from more fine-grained detail.

2.
Page 8: while the term 'defaulters' is in popular use especially at front line service delivery level, international consensus is that it is stigmatising and 'people lost to follow up' is the preferred term., Haricharan et al. https://doi.org/10.1017/s1463423621000323 (2)and https://doi.org/10.1017/s146342362100027x (3) Page 9, similarly the statement 'limited.Community empowerment in community dialogues tends towards health promotion activities' needs to be rationalised/evidenced/substantiated a little further.

Discussion
Page 9: the statement 'data pathways vary by country' could be usefully supplemented with additional detail -the analysis provides a granular account of how the generative, processing, utilisation and accessibility pathways vary by several other factors.Similarly, the statement about multiple stakeholders use CBHIS data could provide a little more nuance.These statements, while useful to summarise the findings are very general. 1.
Page 9: the statement on 'continued training for CHWs' is useful but also would benefit from more detail.Who should conduct this training?Statutory services?What are the opportunity costs of this?What is the role of development partners, here?The recommendations are good and grounded in the findings but could be usefully unpacked a little further.

2.
Page 9: the finding on storage of health information in CHWs' residences is powerful, and should be presented in the Results section, and then followed up in the Discussion with a thorough critique.In South Africa, for example, the finding could be considered in terms of the relatively new POPIA legislation on data protection, and in terms of the struggle of CHWs; who are recognised/centralised in PHC policy and strategy but poorly supported and resourced at operational and implementation levels.

3.
Page 9: the discussion point on the 'disproportionate emphasis on technical aspects of enabling data use' is great, and again could be unpacked a little further.There is evidence, again in South Africa, of district health information systems being costly, producing poor 4.

5.
Page 9: the statement 'We indicate that CBHIS data can be utilized in health system and service outcomes, health resource allocation, and administrative decisions' is not quite clear.Does this mean that, in theory, CBHIS can support data-informed decision making, but in practice there are many implementation challenges?The description of these challenges at the end of the passage is great and could usefully be supplemented with the upward accountability (and data) flows in many health systems, together with the fragmentation that can related at least in part to vertical donor and development partner programming.

6.
Page 9: the core recommendations seem to focus 'internally' on improving the capabilities of CHWs for collection, analysis and reporting.This is in part founded and reasonable however, the recommendation could be strengthened by balancing it with an 'outward gaze', considering the national and subnational health systems challenges, as well as the supranational drivers as noted through these comments.How feasible are these recommendations, considering the implementation realities of PHC? 7.
Page 9: the statement 'Negative organizational behaviour, such as the pressure senior health managers exert on providers to meet unrealistic service delivery targets, has contributed to false reporting and the denial of existing service delivery problems' is another powerful statement.However, it is unclear if this is a finding from the data, or from elsewhere.Please reference and relate to a supporting source, and if this is the data set, then present as a finding.Relates to the political nature of data, and may be worth considering issues such as and including how to progress beyond 'naïve rationality' towards a more rounded view of community data and data use, including an appreciation of the political nature of local, routine health data.

8.
Page 10: the discussion on community participation, as above, may usefully refer to evidence on the existence of spaces and processes, but their limited functionality in practice, and consider the implications of this.9.

Ramathebane Maseabata
Department of Pharmacy, National University of Lesotho, Maseru, Lesotho I reviewed this article, and here are my views about it.The article is rewritten, and there is an incorrect full-out of DHIS2, which is supposed to be the District Health Information System, not the Demographic Health Information System.
Apart from this, I am happy with the article, and I recommend it for indexing.
Are the rationale for, and objectives of, the Systematic Review clearly stated?Yes

Are sufficient details of the methods and analysis provided to allow replication by others? Yes
Is the statistical analysis and its interpretation appropriate?Yes

Are the conclusions drawn adequately supported by the results presented in the review? Yes
If this is a Living Systematic Review, is the 'living' method appropriate and is the search schedule clearly defined and justified?('Living Systematic Review' or a variation of this term should be included in the title.)Yes Competing Interests: No competing interests were disclosed.
Reviewer Expertise: Pharmacy Practice I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard.
Havard Dataverse: Replication Data for: Examining the Development and Utilisation of Community-Based Health Information Systems (CBHIS) in Africa: A Scoping Review https://doi.org/10.7910/DVN/ZH5JK8 25

:
Could be structured way, as follows: a) statement of principal findings by objectives; b) strengths and weaknesses of the review; c) contextualizing findings in context of similar reviews hence d) contribution to new knowledge Conclusion: Is well written but could provide a brief summarize of the key findings, potential implications and the way forward.Are the rationale for, and objectives of, the Systematic Review clearly stated?YesAre sufficient details of the methods and analysis provided to allow replication by others?YesIs the statistical analysis and its interpretation appropriate?YesAre the conclusions drawn adequately supported by the results presented in the review?PartlyIf this is a Living Systematic Review, is the 'living' method appropriate and is the search schedule clearly defined and justified?('Living Systematic Review' or a variation of this term should be included in the title.)Yes Competing Interests: No competing interests were disclosed.Reviewer Expertise: Health systems research and development including Community Based Health CareI confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above.D'Ambruoso LuciaMedical Sciences and Nutrition, University of Aberdeen, Aberdeen, UKReviewExamining the development and utilisation of Community-Based Health Information Systems (CBHIS) in Africa: A Scoping ReviewOVERALL COMMENTSThis paper presents a literature review on community-based health information systems in lowand middle-income countries.The analysis provides a granular account of the generative, processing, utilisation and accessibility pathways across a range of African nation states, appraises these findings, and derives recommendations.The paper is important, original and worthy of indexing.The following are some relatively minor comments, which I hope are of use to the authors to further strengthen the piece.N.B.: I am not a professional systematic reviewer and cannot comment on the methodology in anything other than general terms.

Table 2 . Summary of CBHIS data generation processes. Data collectors Data collection tools/templates Type of data collected at the community level Data submission
• Family folder (Ethiopia)• Household registers (Kenya, Egypt, Rwanda, Malawi) • CHWs service Logbook (Kenya) • Simple wall chart templates (Malawi) • Paper registers (Ghana, DRC, Zambia) • Forms/papers (Namibia, South Africa& Ghana) • Surveillance forms (Burkina Faso) Electronic-based tools • Mobile phone applications/technologies/ mHealth tools Other sources of data: • Individual health records (health cards and integrated maternal and childcare (MCH) cards) • Assistant chief registers • Community outreach and meetings • Birth and death register • Village register • Under-five register • Household survey/visit form • Community treatment and tracking register • Referral form

action on Primary Health Care: analyzing bottlenecks and strategies to strengthen community health systems in West and Central Africa
. Glob Health Sci Pract.2021; 9(Suppl 1): S47-S64.PubMed Abstract | Publisher Full Text | Free Full Text 66. Yarinbab TE, Assefa MK: Utilization
Page 9, the theme 'empowerment' would benefit from a little development (space allowing).A notion of what is meant by empowerment together with some grounded consideration of the functionality of existing community dialogue/governance spaces.For instance, in South Africa, while clinic and health committees are well established local governance processes, there is evidence that they have limited functionality.See Hove et al. https://doi.org/10.1080/16549716.2021.2004730

Are the rationale for, and objectives of, the Systematic Review clearly stated? Yes Are sufficient details of the methods and analysis provided to allow replication by others? Yes Is the statistical analysis and its interpretation appropriate? Not applicable Are the conclusions drawn adequately supported by the results presented in the review? Partly If this is a Living Systematic Review, is the 'living' method appropriate and is the search schedule clearly defined and justified? ('Living Systematic Review' or a variation of this term should be included in the title.) Not applicable Competing Interests:
Page 10: the concluding statement needs some unpacking and grounding I, which could be done in the Discussion section -'Community involvement and empowerment are mainly achieved through community dialogue, but it should move beyond supply-side-driven health promotion activities and enhance demand-driven interventions to foster community accountability and tailor interventions to community needs'.As above, it would be useful to outline what is meant by community participation, empowerment and accountability.What community dialogue is and means, how it is done and the challenges it faces in practice and in reality.References 1. Hove J, D'Ambruoso L, Kahn K, Witter S, et al.: Lessons from community participation in primary health care and water resource governance in South Africa: a narrative review.Glob Health Action.The role of community participation in primary health care: practices of South African health committees.Prim Health Care Res Dev.2021; 22: e31 PubMed Abstract | Publisher Full Text 4. Hotchkiss DR, Aqil A, Lippeveld T, Mukooyo E: Evaluation of the Performance of Routine Information System Management (PRISM) framework: evidence from Uganda.BMC Health Serv Res.2010; 10: 188 PubMed Abstract | Publisher Full Text 5. Rouamba T, Samadoulougou S, Kirakoya-Samadoulougou F: Addressing challenges in routine health data reporting in Burkina Faso through Bayesian spatiotemporal prediction of weekly clinical malaria incidence.Sci Rep. 2020; 10 (1): 16568 PubMed Abstract | Publisher Full Text 6. Nshimyiryo A, Health management information system (HMIS) data verification: A case study in four districts in Rwanda.Reference Source No competing interests were disclosed.

have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above.
Reviewer Report 15 September 2024 https://doi.org/10.21956/wellcomeopenres.25084.r95036This is an open access peer review report distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.Karuga LVCT Health, Nairobi, Kenya This is an interesting and timely article.I have a minor comment:This last sentence in the results section seems misplaced and is hanging.Clarify whether it is supported by literature or whether this is the authors' opinion " Community empowerment in community dialogues tends towards health promotion activities." © 2024 Karuga R. ○ Are

the rationale for, and objectives of, the Systematic Review clearly stated? Yes Are sufficient details of the methods and analysis provided to allow replication by others? Yes Is the statistical analysis and its interpretation appropriate? Not applicable Are the conclusions drawn adequately supported by the results presented in the review? Yes If this is a Living Systematic Review, is the 'living' method appropriate and is the search schedule clearly defined and justified? ('Living Systematic Review' or a variation of this term should be included in the title.) Not applicable Competing Interests:
No competing interests were disclosed.

have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard.
This is an open access peer review report distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.