Predictive power of socio-demographic attributes of healthcare workers on data quality in Tanzanian regional referral hospitals

This study highlights the significant influence of socio-demographic factors, particularly age and sex, on the accuracy and completeness of healthcare data. These findings suggest that the characteristics of patient data collectors can either enhance or hinder data quality. Therefore, it is crucial to implement targeted training programs for healthcare workers, emphasizing their role in maintaining high-quality healthcare data.

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Publication Details

Journal
BMC Health Services Research
Published
2025-12-08
DOI
https://doi.org/10.1186/s12913-025-13219-1
Primary Topic
Global Maternal and Child Health
Type
article
Field-Weighted Citation Impact
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article

Predictive power of socio-demographic attributes of healthcare workers on data quality in Tanzanian regional referral hospitals

Joshua J. Malago, Mikidadi Muhanga, Rogate I. Phinias
BMC Health Services Research
Global Maternal and Child Health
article

Predictive power of socio-demographic attributes of healthcare workers on data quality in Tanzanian regional referral hospitals

Joshua J. Malago, Mikidadi Muhanga, Rogate I. Phinias
article en

Abstract

This study highlights the significant influence of socio-demographic factors, particularly age and sex, on the accuracy and completeness of healthcare data. These findings suggest that the characteristics of patient data collectors can either enhance or hinder data quality. Therefore, it is crucial to implement targeted training programs for healthcare workers, emphasizing their role in maintaining high-quality healthcare data.

BMC Health Services ResearchVol. 25(1)
Mzumbe University (TZ), Sokoine University of Agriculture (TZ)
Openalex Percentile: Top 51%
Global Maternal and Child Health
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