ArticlePLOS global public health2025
Perceived accuracy and utilisation of DHIS2 data for health decision making and advocacy in Kenya: A Qualitative Study.
Article in PLOS global public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
4 citing papers in PubMed.
- Lessons from piloting and scaling a real-time DHIS2 based treatment reporting tool for mass drug administration in Nigeria.PLoS neglected tropical diseases · 2025Article
- D2A: a community-led smartphone tool for malnutrition screening in Kenya.Frontiers in public health · 2025Article
- Review
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
24 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Reliable health information systems (HIS) are critical for effective decision-making in the delivery of Primary Health Care and Reproductive, Maternal, Newborn, Child, Adolescent Health and Nutrition (PHC/RMNCAH+N) services. In Kenya, the District Health Information Software 2 (DHIS2) platform serves as the primary HIS for tracking health indicators. This qualitative study explored perceptions of DHIS2 data accuracy and use for decision-making among PHC/RMNCAH+N stakeholders across 15 counties in Kenya. 89 Key Informant Interviews were conducted with PHC/RMNCAH+N stakeholders, to explore experiences, barriers, and facilitators of DHIS2 data use. Thematic network analysis was employed to identify recurrent themes and generate insights into the utility of DHIS2-generated information. Sociotechnical challenges included limited technical capacity among health staff, inadequate analytical skills, and reliance on a small pool of Health Records Information Officers (HRIOs). However, positive practices emerged, such as the use of DHIS2 dashboards and user-friendly outputs, which were valued for supporting evidence-based decision-making and advocacy, particularly at higher levels of health management. In some counties, visual displays of data, including scorecards and performance trends, facilitated budget advocacy and community engagement. Contextual challenges and constraints, such as use of inconsistent data collection tools across counties post-devolution, human resource shortages, and limited integration of private sector data, contributed to incomplete reporting. These challenges underpinned perceived inaccuracy of DHIS2 data, arguably, hindering the complete reliance on DHIS2 data for planning and decision making. The study highlights the need for targeted investments to improve DHIS2 data accuracy and use through stronger stakeholder coordination, enhanced data synthesis skills, and fostering a culture of data ownership among a wide range of stakeholders in health, including political actors.. Addressing these gaps will contribute to improvement in DHIS2 data quality, enhanced ownership and reliance on DHIS2 data by PHC/RMNCAH+N stakeholders for decision making in Kenya.
Identifiers
What Socratic holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.