"无声损失-无声数据":在低收入和中等收入国家使用数据质量维度审查死产数据质量
Anuj Kumar Pandey1,2, Sutapa Bandyopadhyay Neogi1, Diksha Gautam1,3
1Department of Health Systems and Implementation Research, International Institute of Health Management Research- New Delhi, Delhi, India.
概括
提高死胎数据质量对于有效的政策制定至关重要. 解决低收入和中等收入国家 (LMICs) 的数据缺口和加强报告可以帮助防止未来的悲剧.
科学领域:
- 公共卫生 公共卫生
- 医疗保健政策 医疗保健政策
- 数据科学数据科学数据科学
背景情况:
- 准确的死胎数据对于政策决策至关重要,影响医疗保健管理和研究.
- 死亡出生代表了深刻的损失,需要从仅仅将其视为出生结果的转变,承认它是一种失去了生命.
- 目前在低收入和中等收入国家 (LMICs) 收集的数据往往忽视了社会和情感层面,阻碍了有效的政策制定.
研究的目的:
- 汇编关于LMIC中死产报告和记录的关键问题,重点关注数据质量.
- 提出改善死胎数据质量的策略,包括定义协调和增强数据采集.
- 倡导增加对死胎研究和改进数据系统的资金.
主要方法:
- 文献综述和综合目前在LMIC中死产数据收集和报告的实践.
- 分析数据质量挑战,包括定义不一致和系统碎片化.
- 开发可操作的数据质量改善策略.
主要成果:
- 在LMICs中确定了死亡出生数据质量的重大挑战,影响了政策和干预的有效性.
- 强调需要协调死产的定义,以确保统一的数据解释.
- 提出了增强数据采集和不同健康信息系统之间的联系的实际解决方案.
结论:
- 提高死胎数据质量对于制定有针对性的政策和干预措施来降低死胎率至关重要.
- 需要采用多方面的方法,包括改进定义,数据链接和增加研究资金.
- 承认死胎是一种生命损失,并得到强有力的数据支持,对于政策和同情护理都至关重要.
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