Evidence map›Paper›PMID 34187489›Full record

ArticleMalaria journal2021

Effectiveness of in-service training plus the collaborative improvement strategy on the quality of routine malaria surveillance data: results of a pilot study in Kayunga District, Uganda.

Nelli Westercamp, Sarah G Staedke, Catherine Maiteki-Sebuguzi, Alex Ndyabakira, John Michael Okiring, Simon P Kigozi, Grant Dorsey, Edward Broughton, Eleanor Hutchinson, M Rashad Massoud and 1 more

Abstract read
In one paragraph

Article in Malaria journal, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 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

11 authors.

Nelli WestercampMalaria Branch, Division of Parasitic Diseases and Malaria, Centers for Disease Control and Prevention, 1600 Clifton Road, Atlanta, GA, 30333, USA. ydj6@cdc.gov.ORCID http://orcid.org/0000-0003-0136-9750
Sarah G StaedkeDepartment of Clinical Research, London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT, UK.
Catherine Maiteki-SebuguziInfectious Diseases Research Collaboration, 2C Nakasero Hill Road, Kampala, Uganda.
Alex NdyabakiraInfectious Diseases Research Collaboration, 2C Nakasero Hill Road, Kampala, Uganda.
John Michael OkiringInfectious Diseases Research Collaboration, 2C Nakasero Hill Road, Kampala, Uganda.
Simon P KigoziInfectious Diseases Research Collaboration, 2C Nakasero Hill Road, Kampala, Uganda.
Grant DorseyInfectious Diseases Research Collaboration, 2C Nakasero Hill Road, Kampala, Uganda.
Edward BroughtonASSIST Project, University Research Co., LLC, 5404 Wisconsin Avenue, Suite 600, Chevy Chase, MD, 20815, USA.
Eleanor HutchinsonDepartment of Clinical Research, London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT, UK.
M Rashad MassoudASSIST Project, University Research Co., LLC, 5404 Wisconsin Avenue, Suite 600, Chevy Chase, MD, 20815, USA.
Alexander K RoweMalaria Branch, Division of Parasitic Diseases and Malaria, Centers for Disease Control and Prevention, 1600 Clifton Road, Atlanta, GA, 30333, USA.

Funding

CGH CDC HHS U01 GH000076
6 · The paper itself

Abstract

backgroundSurveillance data are essential for malaria control, but quality is often poor. The aim of the study was to evaluate the effectiveness of the novel combination of training plus an innovative quality improvement method-collaborative improvement (CI)-on the quality of malaria surveillance data in Uganda.

methodsThe intervention (training plus CI, or TCI), including brief in-service training and CI, was delivered in 5 health facilities (HFs) in Kayunga District from November 2015 to August 2016. HF teams monitored data quality, conducted plan-do-study-act cycles to test changes, attended periodic learning sessions, and received CI coaching. An independent evaluation was conducted to assess data completeness, accuracy, and timeliness. Using an interrupted time series design without a separate control group, data were abstracted from 156,707 outpatient department (OPD) records, laboratory registers, and aggregated monthly reports (MR) for 4 time periods: baseline-12 months, TCI scale-up-5 months; CI implementation-9 months; post-intervention-4 months. Monthly OPD register completeness was measured as the proportion of patient records with a malaria diagnosis with: (1) all data fields completed, and (2) all clinically-relevant fields completed. Accuracy was the relative difference between: (1) number of monthly malaria patients reported in OPD register versus MR, and (2) proportion of positive malaria tests reported in the laboratory register versus MR. Data were analysed with segmented linear regression modelling.

resultsData completeness increased substantially following TCI. Compared to baseline, all-field completeness increased by 60.1%-points (95% confidence interval [CI]: 46.9-73.2%) at mid-point, and clinically-relevant completeness increased by 61.6%-points (95% CI: 56.6-66.7%). A relative - 57.4%-point (95% confidence interval: - 105.5, - 9.3%) change, indicating an improvement in accuracy of malaria test positivity reporting, but no effect on data accuracy for monthly malaria patients, were observed. Cost per additional malaria patient, for whom complete clinically-relevant data were recorded in the OPD register, was $3.53 (95% confidence interval: $3.03, $4.15).

conclusionsTCI improved malaria surveillance completeness considerably, with limited impact on accuracy. Although these results are promising, the intervention's effectiveness should be evaluated in more HFs, with longer follow-up, ideally in a randomized trial, before recommending CI for wide-scale use.

Indexed as

Case ManagementData AccuracyEpidemiological MonitoringPopulation SurveillanceHealth FacilitiesHumansInterrupted Time Series AnalysisMalariaPilot ProjectsUgandaCollaborative improvementData qualityMalariaQuality improvementSurveillanceUganda

Identifiers

PMID34187489
PMCPMC8243434

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

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.