Evidence map›Paper›PMID 31263550›Full record

ArticleJournal of global health2019

iCCM data quality: an approach to assessing iCCM reporting systems and data quality in 5 African countries.

Lwendo Moonzwe Davis, Kirsten Zalisk, Samantha Herrera, Debra Prosnitz, Helen Coelho, Jennifer Yourkavitch

Abstract read
In one paragraph

Article in Journal of global health, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

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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

6 authors.

Lwendo Moonzwe DavisICF, Rockville, Maryland, USA.
Kirsten ZaliskICF, Rockville, Maryland, USA.
Samantha HerreraICF, Rockville, Maryland, USA.
Debra ProsnitzICF, Rockville, Maryland, USA.
Helen CoelhoICF, Rockville, Maryland, USA.
Jennifer YourkavitchICF, Rockville, Maryland, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundEnsuring the quality of health service data is critical for data-driven decision-making. Data quality assessments (DQAs) are used to determine if data are of sufficient quality to support their intended use. However, guidance on how to conduct DQAs specifically for community-based interventions, such as integrated community case management (iCCM) programs, is limited. As part of the World Health Organization's (WHO) Rapid Access Expansion (RAcE) Programme, ICF conducted DQAs in a unique effort to characterize the quality of community health worker-generated data and to use DQA findings to strengthen reporting systems and decision-making.

methodsWe present our experience implementing assessments using standardized DQA tools in the six RAcE project sites in the Democratic Republic of Congo, Malawi, Mozambique, Niger, and Nigeria. We describe the process used to create the RAcE DQA tools, adapt the tools to country contexts, and develop the iCCM DQA Toolkit, which enables countries to carry out regular and rapid DQAs. We provide examples of how we used results to generate recommendations.

resultsThe DQA tools were customized for each RAcE project to assess the iCCM data reporting system, trace iCCM indicators through this system, and to ensure that DQAs were efficient and generated useful recommendations. This experience led to creation of an iCCM DQA Toolkit comprised of simplified versions of RAcE DQA tools and a guidance document. It includes system assessment questions that elicit actionable responses and a simplified data tracing tool focused on one treatment indicator for each iCCM focus illness: diarrhea, malaria, and pneumonia. The toolkit is intended for use at the national or sub-national level for periodic data quality checks.

conclusionsThe iCCM DQA Toolkit was designed to be easily tailored to different data reporting system structures because iCCM data reporting tools and data flow vary substantially. The toolkit enables countries to identify points in the reporting system where data quality is compromised and areas of the reporting system that require strengthening, so that countries can make informed adjustments that improve data quality, strengthen reporting systems, and inform decision-making.

Indexed as

Data AccuracyDelivery of Health Care, IntegratedCase ManagementChild, PreschoolCommunity Health ServicesDemocratic Republic of the CongoDiarrheaHealth Services AccessibilityHumansInfantMalariaMalawiMozambiqueNigerNigeriaPneumonia

Identifiers

PMID31263550
PMCPMC6594667

What OpenQuestion holds

Textmetadata
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.