洞察马拉维的COVID-19数据收集和管理:探索流程,感知和数据差异
Amelia Taylor1, Thokozani Liwewe2, Jim Todd3
1Malawi University of Business and Applied Sciences, Blantyre, Malawi.
Wellcome open research
|August 8, 2024
概括
马拉维的COVID-19监测数据质量受到表格设计缺陷和流程问题的阻碍. 提高表格的可用性和培训对于准确的疾病监测和公共卫生洞察至关重要.
科学领域:
- 公共卫生 公共卫生
- 流行病学 流行病学
- 医疗信息学 医疗信息学
背景情况:
- 马拉维的COVID-19监测依赖于基于病例的表格,但数据缺口和不一致性影响了可用性.
- 尽管做出了重大努力,但国家数据质量仍然不足于最佳水平.
研究的目的:
- 调查马拉维的COVID-19数据收集和报告流程.
- 探索卫生工作者对数据收集工具和流程的看法.
- 确定有助于监控数据质量问题的因素.
主要方法:
- 与75名医疗保健专业人员进行了重点小组讨论和深入采访.
- 收集了关于监控形式的有效性,数据收集流程和培训需求的观点.
- 使用MAXQDA进行主题和文档分析.
主要成果:
- 与案例定义有关的表格设计问题和挑战占数据质量问题的44%.
- 数据收集过程中的担忧和培训差距占49%的确定的问题.
- 语言,隐私,伦理和文化因素也影响了数据质量.
结论:
- 数据质量与监控表格的设计和使用密切相关.
- 形式格式,字段顺序以及缺乏指南的缺陷导致了错误.
- 审查表格设计对于有效融入监控系统至关重要.
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