Data management practice of health extension workers and associated factors in Central Gondar Zone, northwest Ethiopia

• Main Authors: Mequannent Sharew Melaku (Author), Lamrot Yohannes (Author)
• Format: Book
• Published: Frontiers Media S.A., 2024-11-01T00:00:00Z.
• Subjects: article
• Online Access: Connect to this object online.
• Notes: 2673-253X; 10.3389/fdgth.2024.1479184
• Keywords: data; data management practice; health extension workers; associated factors; Central Gondar Zone; Medicine; R; Public aspects of medicine; RA1-1270; Electronic computers. Computer science; QA75.5-76.95
• Source: Frontiers in Digital Health, Vol 6 (2024)

IntroductionGenerating quality data for decision-making at all levels of a health system is a global imperative. The assessment of the Ethiopian National Health Information System revealed that health information system resources, data management, dissemination, and their use were rated as "not adequate" among the six major components of the health system. Health extension workers are the frontline health workforce where baseline health data are generated in the Ethiopian health system. However, the data collected, compiled, and reported by health extension workers are unreliable and of low quality. Despite huge problems in data management practices, there is a lack of sound evidence on how to overcome these health data management challenges, particularly among health extension workers. Thus, this study aimed to assess data management practices and their associated factors among health extension workers in the Central Gondar Zone.MethodAn institution-based cross-sectional study was conducted among 383 health extension workers. A simple random sampling method was used to select districts, all health extension workers were surveyed in the selected districts, and a structured self-administered questionnaire was used for data collection. The data was entered using EpiData version 4.6 and analyzed using STATA, version 16. Bivariable and multivariable binary logistic regression analyses were executed. An odds ratio with a 95% confidence interval and a p-value of <0.05 was calculated to determine the strength of the association and to evaluate statistical significance, respectively.ResultsOf the 383 health extension workers enrolled, all responded to the questionnaire with a response rate of 100%. Furthermore, 54.7% of the respondents had good data management practices. In the multivariable logistic regression analysis, being a married woman, having good data management knowledge, having a good attitude toward data management, having 1-5 years of working experience, and having a salary ranging from 5,358 to 8,013 Ethiopian Birr were the factors significantly associated with good data management practices among health extension workers. The overall data management practice was poor with only five health extension workers out of ten having good data management practices.