Neonatal indicator data in Tanzania District Health Information System: evaluation of availability and quality of selected newborn indicators, 2015-2022

Tanzania's DHIS2 captures many ENAP indicators; however, notable variability in data quality persists, with substantial data gaps related to maternal and newborn outcomes and complications. To address these challenges, it is crucial to strengthen routine data review, implement robust quality checks, enhance validation processes, provide targeted training, deliver constructive feedback, and conduct supportive supervision. Placing greater emphasis on using DHIS2 data to monitor progress will help identify gaps and drive improvements in data quality, ultimately supporting better maternal and newborn health outcomes.

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Publication Details

Journal
BMC Pediatrics
Published
2025-01-23
DOI
https://doi.org/10.1186/s12887-025-05417-x
Citations
3
Primary Topic
Global Maternal and Child Health
Type
article
Field-Weighted Citation Impact
10.48

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article

Neonatal indicator data in Tanzania District Health Information System: evaluation of availability and quality of selected newborn indicators, 2015-2022

Claud Kumalija, Christine A. Bohne, Ahmad Makuwani, Louise T. Day et al.
3 citations
BMC Pediatrics
Global Maternal and Child Health
10.48
article

Neonatal indicator data in Tanzania District Health Information System: evaluation of availability and quality of selected newborn indicators, 2015-2022

Claud Kumalija, Christine A. Bohne, Ahmad Makuwani, Louise T. Day, Joy Elizabeth Lawn, Felix Bundala, Eric O. Ohuma, Josephine Shabani, Habib Ismail, Nahya Salim
article en
3 citations

Abstract

Tanzania's DHIS2 captures many ENAP indicators; however, notable variability in data quality persists, with substantial data gaps related to maternal and newborn outcomes and complications. To address these challenges, it is crucial to strengthen routine data review, implement robust quality checks, enhance validation processes, provide targeted training, deliver constructive feedback, and conduct supportive supervision. Placing greater emphasis on using DHIS2 data to monitor progress will help identify gaps and drive improvements in data quality, ultimately supporting better maternal and newborn health outcomes.

BMC PediatricsVol. 23(S2)
Ifakara Health Institute (TZ), Muhimbili University of Health and Allied Sciences (TZ), London School of Hygiene & Tropical Medicine (GB), Ministry of Health, Community Development, Gender, Elderly and Children (TZ), Rice University (US)
Bill and Melinda Gates Foundation, John D. and Catherine T. MacArthur Foundation, Sall Family Foundation, Rice University, Children's Investment Fund Foundation, Lemelson Foundation, Ting Tsung and Wei Fong Chao Family Foundation, ELMA Foundation
Good health and well-being
Openalex Percentile: Top 3%
Global Maternal and Child Health
10.48
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