Evidence map›Paper›PMID 39905148›Full record

ArticleScientific reports2025

Quality of routine malaria data captured at primary health facilities in the Hohoe Municipality, Ghana.

Christopher Ayisah, Thywill Worlase Kpenu, Edem Kojo Dzantor, Clement Tetteh Narh

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Review
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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

4 authors.

Christopher AyisahDepartment of Epidemiology and Biostatistics, Fred N. Binka School of Public Health, University of Health and Allied Sciences, Hohoe Campus, Ghana. christopherayisah128@gmail.com.ORCID 0009-0005-0116-719X
Thywill Worlase KpenuDepartment of Epidemiology and Biostatistics, Fred N. Binka School of Public Health, University of Health and Allied Sciences, Hohoe Campus, Ghana.
Edem Kojo DzantorDepartment of Epidemiology and Biostatistics, Fred N. Binka School of Public Health, University of Health and Allied Sciences, Hohoe Campus, Ghana. edzantor21pg@sph.uhas.edu.gh.ORCID 0000-0002-6195-3898
Clement Tetteh NarhDepartment of Epidemiology and Biostatistics, Fred N. Binka School of Public Health, University of Health and Allied Sciences, Hohoe Campus, Ghana.ORCID 0000-0002-4025-5433

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Malaria is a major public health concern and requires quality data management system for effective preventive measures. The District Health Management Information System (DHMIS II) has been used to routinely capture data at health facilities. However, little is known about the quality of routine malaria data captured on the DHIMS II database in Community-Based Health Planning and Service (CHPS) compounds. The study therefore determined the quality of routine malaria data captured on the DHIMS II database in CHPS compounds in the Hohoe Municipality, Ghana. A retrospective cross-sectional analysis of Out Patient Department (OPD) malaria indicators was conducted using data from January 2018 to December 2022 at CHPS compounds in the Hohoe Municipality. Data were collected from three sources: the DHIMS II, monthly morbidity report forms, and consulting room registers. The study assessed three (3) malaria indicators: suspected malaria cases, tested malaria cases, and confirmed OPD malaria cases. A data validation tool was developed to determine the quality of malaria indicators measuring availability, completeness (percentage of missing data), and accuracy. The data was analysed descriptively using Microsoft excel. Out of the four (4) health facilities, 50% (2/4) met the suggested target of (≥ 90%) in 2018 and 2020 whiles all the (4) facilities met the recommended target in 2021 and 2022 for the availability of monthly OPD morbidity reports. For the availability of monthly data returns on anti-malarial, none of the facilities met the recommended target from 2018 to 2022. All 4 facilities met the recommended target in 2021 and 2022. For completeness of source data, 25% of the facility had complete data that met the required target in specific years (2021-2022). For accuracy, 50% of the facilities showed accurate reporting with a Good (± 5%) accuracy level. The remaining 50% underreported data, resulting in a Poor (± 11-20%) accuracy level. The study finds that while half of the facilities had reliable and complete malaria data in their source registers, there are inconsistencies with the DHIMS II database regarding the standards of data quality. Most facilities faced significant issues like unavailability of data, uncompleted data and underreporting of data, making it not-advisable to rely on DHIMS II for critical health decisions. Although, half of the facilities showed evidence of good data quality, there is still a need for improvement in the capturing of routine malaria data.

Indexed as

Data AccuracyHealth FacilitiesMalariaPrimary Health CareCross-Sectional StudiesDatabases, FactualGhanaHumansRetrospective StudiesData AccuracyData availabilityData completenessDHIMS IIMalaria

Identifiers

PMID39905148
PMCPMC11794616

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