Evidence map›Paper›PMID 31118006›Full record

ArticleBMC health services research2019

Facilitators, best practices and barriers to integrating family planning data in Uganda's health management information system.

Stephen Ojiambo Wandera, Betty Kwagala, Olivia Nankinga, Patricia Ndugga, Allen Kabagenyi, Bridgit Adamou, Benjamin Kachero

Abstract read
In one paragraph

Article in BMC health services research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed, 2 pooled it
–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

18 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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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

7 authors.

Stephen Ojiambo WanderaDepartment of Population Studies, School of Statistics and Planning, College of Business and Management Sciences, Makerere University, Kampala, Uganda. swandera@gmail.com.ORCID http://orcid.org/0000-0002-5617-0274
Betty KwagalaDepartment of Population Studies, School of Statistics and Planning, College of Business and Management Sciences, Makerere University, Kampala, Uganda.
Olivia NankingaDepartment of Population Studies, School of Statistics and Planning, College of Business and Management Sciences, Makerere University, Kampala, Uganda.
Patricia NduggaDepartment of Population Studies, School of Statistics and Planning, College of Business and Management Sciences, Makerere University, Kampala, Uganda.
Allen KabagenyiDepartment of Population Studies, School of Statistics and Planning, College of Business and Management Sciences, Makerere University, Kampala, Uganda.
Bridgit AdamouMEASURE Evaluation, University of North Carolina (UNC), Chapel Hill, USA.
Benjamin KacheroOffice of the Prime Minister, Kampala, Uganda.

Funding

United States Agency for International Development 17630-Makerere-01
6 · The paper itself

Abstract

backgroundHealth management information systems (HMIS) are instrumental in addressing health delivery problems and strengthening health sectors by generating credible evidence about the health status of clients. There is paucity of studies which have explored possibilities for integrating family planning data from the public and private health sectors in Uganda's national HMIS. This study sought to investigate the facilitators, best practices and barriers of integrating family planning data into the district and national HMIS in Uganda.

methodsWe conducted a qualitative study in Kampala, Jinja, and Hoima Districts of Uganda, based on 16 key informant interviews and a multi-stakeholder dialogue workshop with 11 participants. Deductive and inductive thematic methods were used to analyze the data.

resultsThe technical facilitators of integrating family planning data from public and private facilities in the national and district HMIS were user-friendly software; web-based and integrated reporting; and availability of resources, including computers. Organizational facilitators included prioritizing family planning data; training staff; supportive supervision; and quarterly performance review meetings. Key behavioral facilitators were motivation and competence of staff. Collaborative networks with implementing partners were also found to be essential for improving performance and sustainability. Significant technical barriers included limited supply of computers in lower level health facilities, complex forms, double and therefore tedious entry of data, and web-reporting challenges. Organizational barriers included limited human resources; high levels of staff attrition in private facilities; inadequate training in data collection and use; poor culture of information use; and frequent stock outs of paper-based forms. Behavioral barriers were low use of family planning data for planning purposes by district and health facility staff.

conclusionFamily planning data collection and reporting are integrated in Uganda's district and national HMIS. Best practices included integrated reporting and performance review, among others. Limited priority and attention is given to family planning data collection at the facility and national levels. Data are not used by the health facilities that collect them. We recommend reviewing and tailoring data collection forms and ensuring their availability at health facilities. All staff involved in data reporting should be trained and regularly supervised.

Indexed as

Management Information SystemsCross-Sectional StudiesData CollectionDelivery of Health Care, IntegratedFamily Planning ServicesHealth FacilitiesHumansMedical InformaticsPrivate SectorPublic SectorQualitative ResearchUgandaBarriersBest practicesDHISFacilitatorsHealth information systemHMISSub-Saharan AfricaUganda

Identifiers

PMID31118006
PMCPMC6532212

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.