Reasons for over-reporting of routine immunization administrative data in the Democratic Republic of Congo: a mixed cross-sectional study to determine explanatory factors for poor data quality.

IF 3.6 2区 医学 Q1 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH
Dosithée Ngo-Bebe, Fulbert Nappa Kwilu, Joël Nkiama Konde, Daniel Katuashi Ishoso, Félicité Langwana, Cedric Mwanga, Leon Mbulu Kinuani, Christophe Lungayo Luhata, Jean-Crispin Mukendi, Aimé Mwana-Wabene Cikomola, Marcellin Mengouo Nimpa
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Abstract

Background: Differences of more than 30% have been observed between the results of vaccine coverage surveys and routine vaccine coverage data. In the context of the organization and operation of the health system, the study focused on investigating explanatory factors for over-reporting.

Methods: This was a mixed-method, cross-sectional, and analytical study. Over-reporting of routine immunization data was defined as a discrepancy of ≥ 10% points between routine data and survey data or recount data (standards) for the Penta3 vaccine. Data were collected by questionnaire from 117 health centers, 30 health zone offices, and 13 provincial health offices. Bivariable and multivariable analyses (α = 5%) were used to find factors influencing over-reporting. Data from 30 in-depth interviews were collected to complement quantitative data.

Results: The phenomenon of over-reporting of routine immunization data was verified in the health zones (90% or 77%) and health centers (43%) surveyed in 2019 and 2020. At the health zone level, six explanatory factors emerged. The most significant tree variables being the pressure exerted on managers to achieve pre-established annual targets (p = 0.016), the availability of data collection tools (p = 0.010) and bearer message for manual transport of reports (p = 0.031). At the health center level, seven factors were found, and the four most significant were: availability of a cell phone (p = 0.002), existence of table or graph for coverage monitoring (p = 0.003), availability of a computer in the health center (p = 0.007) and designated health data collector (p = 0.015). Qualitative data revealed three over-reporting practices: deliberate inflation of vaccine delivery figures, readjustment of expected target population figures, and occasional errors in data transcription.

Conclusion: Over-reporting is essentially generated by providers. Solving this problem requires lifting the pressure exerted on managers at different levels of the health system, making data management more secure, and qualifying the staff responsible for managing immunization data.

刚果民主共和国过度报告常规免疫管理数据的原因:一项混合横断面研究,以确定数据质量差的解释因素。
背景:疫苗覆盖率调查结果与常规疫苗覆盖率数据之间存在30%以上的差异。在卫生系统的组织和运作的背景下,研究的重点是调查过度报告的解释因素。方法:采用混合方法、横断面和分析研究。常规免疫数据的多报定义为常规数据与Penta3疫苗的调查数据或重新统计数据(标准)之间的差异≥10%。通过问卷调查收集117个卫生中心、30个卫生区办事处和13个省级卫生办事处的数据。采用双变量和多变量分析(α = 5%)寻找影响多报的因素。从30个深度访谈中收集数据,以补充定量数据。结果:2019年和2020年调查的卫生区(90%或77%)和卫生中心(43%)均存在常规免疫数据报漏的现象。在卫生区层面,出现了六个解释因素。最重要的三个变量是对管理人员施加的压力,以实现预先设定的年度目标(p = 0.016),数据收集工具的可用性(p = 0.010)和手工传输报告的承载信息(p = 0.031)。在保健中心一级,发现了七个因素,其中四个最重要的因素是:手机的可用性(p = 0.002),是否存在用于覆盖率监测的表格或图表(p = 0.003),保健中心是否有计算机(p = 0.007)和指定的健康数据收集器(p = 0.015)。定性数据揭示了三种过度报告的做法:故意夸大疫苗交付数字,重新调整预期目标人口数字,以及数据转录中的偶尔错误。结论:过度报告本质上是由提供者产生的。要解决这一问题,需要减轻对卫生系统各级管理人员施加的压力,使数据管理更加安全,并使负责管理免疫数据的工作人员具备资格。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
BMC Public Health
BMC Public Health 医学-公共卫生、环境卫生与职业卫生
CiteScore
6.50
自引率
4.40%
发文量
2108
审稿时长
1 months
期刊介绍: BMC Public Health is an open access, peer-reviewed journal that considers articles on the epidemiology of disease and the understanding of all aspects of public health. The journal has a special focus on the social determinants of health, the environmental, behavioral, and occupational correlates of health and disease, and the impact of health policies, practices and interventions on the community.
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