Factors associated with data quality in the routine health information system of Benin

被引：39

作者：

Ahanhanzo Y.G. ^{[1
,2
]}

Ouedraogo L.T. ^{[1
]}

Kpozèhouen A. ^{[1
]}

Coppieters Y. ^{[2
]}

Makoutodé M. ^{[3
]}

Wilmet-Dramaix M. ^{[2
]}

机构：

[1] Epidemiology and Biostatistics Department, Public Health Regional Institute, University of Abomey-Calavi, Abomey-Calavi

[2] Center of research in Epidemiology, Biostatistics and Clinical Research, School of Public Health, Université Libre de Bruxelles, Bruxelles

[3] Environment and Health Department, Public Health Regional Institute, University of Abomey-Calavi, Abomey-Calavi

来源：

Archives of Public Health | / 72卷 / 1期

关键词：

Data quality; Health information systems; Related factors;

D O I：

10.1186/2049-3258-72-25

中图分类号：

学科分类号：

摘要：

Background: Routine health information systems (RHIS) are crucial to the acquisition of data for health sector planning. In developing countries, the insufficient quality of the data produced by these systems limits their usefulness in regards to decision-making. The aim of this study was to identify the factors associated with poor data quality in the RHIS in Benin. Methods: This cross-sectional descriptive and analytical study included health workers who were responsible for data collection in public and private health centers. The technique and tools used were an interview with a selfadministered questionnaire. The dependent variable was the quality of the data. The independent variables were socio-demographic and work-related characteristics, personal and work-related resources, and the perception of the technical factors. The quality of the data was assessed using the Lot Quality Assurance Sampling method. We used survival analysis with univariate proportional hazards (PH) Cox models to derive hazards ratios (HR) and their 95% confidence intervals (95% CI). Focus group data were evaluated with a content analysis. Results: A significant link was found between data quality and level of responsibility (p = 0.011), sector of employment (p = 0.007), RHIS training (p = 0.026), level of work engagement (p < 0.001), and the level of perceived self-efficacy (p = 0.03). The focus groups confirmed a positive relationship with organizational factors such as the availability of resources, supervision, and the perceived complexity of the technical factors. Conclusion: This exploratory study identified several factors associated with the quality of the data in the RHIS in Benin. The results could provide strategic decision support in improving the system's performance. © 2014 Glèlè Ahanhanzo et al.

引用

共 23 条

[1]

Le cadre d'assurance de la qualité de Statistique Canada, (2002)

[2]

PRISM

[3]

Boone D., Cloutier S., Lins S., Makulec A., Botswana's Integration Data Quality Assurance into Standards operating procedures: Adaptation of the Routine Data Quality Assessment Tool, (2013)

[4]

Aqil A., Lippeveld T., Hozumi D., PRISM framework: a paradigm shift for designing, strengthening and evaluating routine health information systems, Health Policy Plan, 24, pp. 217-228, (2009)

[5]

Adeya G., Bigirimana A., Cavanaugh K., Miller Franco L., Rapid Assessment of the Health System in Benin, 2006, (2007)

[6]

Health system assessment in Bénin, (2012)

[7]

Rapport d'évaluation du Système National d'Information et de Gestion Sanitaires du Bénin, (2007)

[8]

Jutand M., Salamon R., [Lot quality assurance sampling: methods and applications in public health], Rev Epidemiol Sante Publique, 48, pp. 401-408, (2000)

[9]

Lemeshow S., Taber S., Lot quality assurance sampling: single-and double-sampling plans, World Health Stat Q, 44, pp. 115-132, (1991)

[10]

Rhoda D.A., Fernandez S.A., Fitch D.J., Lemeshow S., LQAS: User Beware, Int J Epidemiol, 39, pp. 60-68, (2010)

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