ReviewBMC health services research2022
Maternal and child health data quality in health care facilities at the Cape Coast Metropolis, Ghana.
Review in BMC health services research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
What it found
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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.
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.
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Who cites it
14 citing papers in PubMed.
- Data Collection Methods, Training, and Perceived Health Information Quality Among Professionals in Three Ghanaian Hospitals: A Cross-Sectional Study.Health science reports · 2026Article
- Digital health system integration in Ghana: a scoping review of governance arrangements, interoperability aspirations, and regulatory gaps.BMC health services research · 2026Article
- Evaluating the Effectiveness of Health Information Management Systems in Facilitating Quality Healthcare Service: A Cross-Sectional Study.Health science reports · 2026Article
- Adolescent pregnancy estimates, spatial distribution, and policy implications in the Volta Region, Ghana, 2019-2023.Scientific reports · 2026Article
- Article
- Medical Science Data Value Evaluation Model: Mixed Methods Study.JMIR medical informatics · 2025Article
- Incidence of low birth weight among newborns delivered in health facilities in the Volta Region, 2019-2023.BMC pregnancy and childbirth · 2025Article
- Article
- Competency Level in Generation and Usage of Health Information Within the Landscape of Ghana.BioMed research international · 2025Article
- Context matters: examining factors influencing the implementation of evidence-based family systems care for small and sick newborns across the care continuum.Frontiers in health services · 2025Article
- Article
- The quality of routine data for measuring facility-based maternal mortality in public and private health facilities in Kampala City, Uganda.Population health metrics · 2024Article
- Review
- Pharmacotherapy for Infertility in Ghana: A Prospective Study on Prescription Patterns and Treatment Outcomes among Women undergoing Fertility Treatment.Current therapeutic research, clinical and experimental · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe demand for quality maternal and child health (MCH) data is critical for tracking progress towards attainment of the Sustainable Development Goal 3. However, MCH cannot be adequately monitored where health data are inaccurate, incomplete, untimely, or inconsistent. Thus, this study assessed the level of MCH data quality.
methodA facility-based cross-sectional study design was adopted, including a review of MCH service records. It was a stand-alone study involving 13 healthcare facilities of different levels that provided MCH services in the Cape Coast Metropolis. Data quality was assessed using the dimensions of accuracy, timeliness, completeness, and consistency. Health facilities registers were counted, collated, and compared with data on aggregate monthly forms, and a web-based data collation and reporting system, District Health Information System (DHIS2). The aggregate monthly forms were also compared with data in the DHIS2. Eight MCH variables were selected to assess data accuracy and consistency and two monthly reports were used to assess completeness and timeliness. Percentages and verification factor were estimated in the SPSS version 22 package.
resultsData accuracy were recorded between the data sources: Registers and Forms, 102.1% (95% CI = 97.5%-106.7%); Registers and DHIS2, 102.4% (95% CI = 94.4%-110.4%); and Forms and DHIS2, 100.1% (95% CI = 96.4%-103.9%). Across the eight MCH variables, data were 93.2% (95% CI = 82.9%-103.5%) complete in Registers, 91.0% (95% CI = 79.5%-102.5%) in the Forms, and 94.9% (95% CI = 89.9%-99.9%) in DHIS2 database. On the average, 87.2% (95% CI = 80.5%-93.9%) of the facilities submitted their Monthly Midwife's Returns reports on time, and Monthly Vaccination Report was 94% (95% CI = 89.3%-97.3%). The overall average data consistency was 93% (95% CI = 84%-102%).
conclusionGiven the WHO standard for data quality, the level of MCH data quality in the health care facilities at the Cape Coast Metropolis, available through the DHIS2 is complete, reported on timely manner, consistent, and reflect accurately what exist in facility's source document. Although there is evidence that data quality is good, there is still room for improvement in the quality of the data.
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