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首页> 外文期刊>Reproductive Health >Data quality monitoring and performance metrics of a prospective, population-based observational study of maternal and newborn health in low resource settings
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Data quality monitoring and performance metrics of a prospective, population-based observational study of maternal and newborn health in low resource settings

机译：在资源匮乏地区进行的基于前瞻性，基于人群的孕产妇和新生儿健康观察研究的数据质量监控和性能指标

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Background To describe quantitative data quality monitoring and performance metrics adopted by the Global Network’s (GN) Maternal Newborn Health Registry (MNHR), a maternal and perinatal population-based registry (MPPBR) based in low and middle income countries (LMICs). Methods Ongoing prospective, population-based data on all pregnancy outcomes within defined geographical locations participating in the GN have been collected since 2008. Data quality metrics were defined and are implemented at the cluster, site and the central level to ensure data quality. Quantitative performance metrics are described for data collected between 2010 and 2013. Results Delivery outcome rates over 95% illustrate that all sites are successful in following patients from pregnancy through delivery. Examples of specific performance metric reports illustrate how both the metrics and reporting process are used to identify cluster-level and site-level quality issues and illustrate how those metrics track over time. Other summary reports (e.g. the increasing proportion of measured birth weight compared to estimated and missing birth weight) illustrate how a site has improved quality over time. Conclusion High quality MPPBRs such as the MNHR provide key information on pregnancy outcomes to local and international health officials where civil registration systems are lacking. The MNHR has measures in place to monitor data collection procedures and improve the quality of data collected. Sites have increasingly achieved acceptable values of performance metrics over time, indicating improvements in data quality, but the quality control program must continue to evolve to optimize the use of the MNHR to assess the impact of community interventions in research protocols in pregnancy and perinatal health. Trial registration number NCT01073475
机译：背景技术描述全球网络（GN）的孕产妇新生儿健康注册中心（MNHR）所采用的定量数据质量监测和性能指标，MNHR是基于中低收入国家（LMIC）的孕产妇和围产期人口注册中心（MPPBR）。方法自2008年以来，已收集了有关参与GN的指定地理位置内所有妊娠结局的持续的，基于人群的前瞻性数据。定义了数据质量指标，并在集群，站点和中央级别实施以确保数据质量。描述了2010年至2013年之间收集的数据的定量绩效指标。结果分娩结果率超过95％，表明从怀孕到分娩的所有部位均能成功追踪患者。特定性能指标报告的示例说明了如何使用指标和报告过程来识别集群级别和站点级别的质量问题，并说明这些指标如何随时间推移进行跟踪。其他摘要报告（例如，测得的出生体重与估计的出生体重相比增加的比例和缺失的出生体重）说明了站点如何随着时间的推移提高质量。结论高质量的MPPBR（例如MNHR）可为缺乏民事登记系统的本地和国际卫生官员提供有关妊娠结局的关键信息。 MNHR已采取措施监控数据收集程序并提高收集的数据质量。随着时间的推移，站点越来越多地获得了可接受的性能指标值，表明数据质量有所提高，但是质量控制计划必须继续发展，以优化MNHR的使用，以评估社区干预措施对怀孕和围生期健康研究方案的影响。试用注册号NCT01073475

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