Evidence map›Paper›PMID 41253431›Full record

ArticleBMJ global health2025

Organisational factors associated with implementing action plans informed by routine health information system data in Mozambique: longitudinal analyses, 2016-2020.

Nami Kawakyu, Bradley H Wagenaar, Orvalho Augusto, Aneth Dinis, Artur Gremu, Isaías Ramiro, Stélio Tembe, Dorlim Uetela, Firmino Jaqueta, Xavier Alcides Isidor and 5 more

Abstract read
In one paragraph

Article in BMJ global health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

15 authors.

Nami KawakyuDepartment of Global Health, University of Washington, Seattle, Washington, USA nkawakyu@uw.edu.ORCID 0000-0002-6591-2057
Bradley H WagenaarDepartment of Global Health, University of Washington, Seattle, Washington, USA.
Orvalho AugustoDepartment of Global Health, University of Washington, Seattle, Washington, USA.ORCID 0000-0002-0005-3968
Aneth DinisDepartment of Global Health, University of Washington, Seattle, Washington, USA.
Artur GremuComité para Saúde de Moçambique, Chimoio, Mozambique.
Isaías RamiroComité para Saúde de Moçambique, Maputo City, Mozambique.ORCID 0009-0002-9568-6633
Stélio TembeDepartment of Global Health, University of Washington, Seattle, Washington, USA.
Dorlim UetelaDepartment of Global Health, University of Washington, Seattle, Washington, USA.
Firmino JaquetaServiços Provincias de Saúde, Manica, Mozambique, Manica, Mozambique.
Xavier Alcides IsidorServiços Provincias de Saúde, Manica, Mozambique, Manica, Mozambique.
Priscilla FelimoneServiços Provincias de Saúde, Sofala, Mozambique, Sofala, Mozambique.
Muanda PinhoServiços Provincias de Saúde, Sofala, Mozambique, Beira, Mozambique.
Quinhas FernandesDepartment of Global Health, University of Washington, Seattle, Washington, USA.ORCID 0000-0002-1539-0967
Sarah GimbelDepartment of Global Health, University of Washington, Seattle, Washington, USA.
Kenneth SherrDepartment of Global Health, University of Washington, Seattle, Washington, USA.ORCID 0000-0002-2963-0829

Funding

(NIH) National Institutes of Health & Eunice Kennedy Shriver National Institute of Child Health R01-HDHD092449
6 · The paper itself

Abstract

introductionRoutine health information system (RHIS) data use remains limited in many low- and middle-income countries, with little evidence on factors that promote or hinder its use for improving health facility performance. This study examined patterns of translating RHIS data into action and explored organisational factors associated with successful implementation.

methodsData come from a sample of 36 facilities in Mozambique that participated in a data-to-action strategy from 2016 to 2020. The strategy united provincial, district and facility staff at semiannual meetings to analyse and review RHIS data and develop action plans to improve health facility services. Data included the number of planned and implemented actions and facility characteristics such as staff size, management practices and RHIS data completeness. Generalised mixed effects logistic regression was used to identify factors associated with successful implementation of planned actions.

resultsFrom 2016 to 2020, facilities implemented 64% (1567 of 2462) of planned actions. On average, facilities planned nine actions per meeting, with the highest number of actions planned during the first meeting and plateauing to five actions per meeting. The likelihood of implementing an action increased by 2% for each additional action planned (aOR 1.02, CI 1.01 to 1.03). Facilities reporting limited staff or financial resources as top barriers were significantly less likely to implement planned actions (aOR 0.52, CI 0.36 to 0.75; aOR 0.42, CI 0.23 to 0.76, respectively).

conclusionFindings suggest that supporting health facilities to develop RHIS data-informed action plans and strengthening management capacity may promote implementation of actions. Addressing staffing and financial resource constraints remains critical for successfully translating RHIS data into action to improve health facility performance.

Indexed as

Health FacilitiesHealth Information SystemsHumansLongitudinal StudiesMozambiqueDecision MakingGlobal HealthHealth services researchHealth systemsHealth systems evaluation

Identifiers

PMID41253431
PMCPMC12636973

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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 OpenQuestion graph.