Data quality monitoring and performance metrics of a prospective, population-based observational study of maternal and newborn health in low resource settings.
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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DOI：
10.1186/1742-4755-12-s2-s2
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发表时间：
2015
影响因子：
3.4
通讯作者：
Bose CL
中科院分区：
文献类型：
--
作者：
Goudar SS;Stolka KB;Koso-Thomas M;Honnungar NV;Mastiholi SC;Ramadurg UY;Dhaded SM;Pasha O;Patel A;Esamai F;Chomba E;Garces A;Althabe F;Carlo WA;Goldenberg RL;Hibberd PL;Liechty EA;Krebs NF;Hambidge MK;Moore JL;Wallace DD;Derman RJ;Bhalachandra KS;Bose CL
描述全球网络（GN）孕产妇新生儿健康登记（MNHR）采用的定量数据质量监测和性能指标，MNHR是一个基于低收入和中等收入国家（LMIC）的孕产妇和围产期人口登记（MPPBR）。自2008年以来，已收集了参与GN的定义地理位置内所有妊娠结局的持续前瞻性、基于人群的数据。为确保数据质量，在群组、地点和中央一级确定并实施了数据质量指标。对2010年至2013年期间收集的数据进行了定量业绩指标说明。超过95%的分娩结局率表明，所有研究中心都成功地对患者进行了从妊娠到分娩的随访。特定性能指标报告的示例说明了指标和报告流程如何用于识别群集级和站点级质量问题，并说明了这些指标如何随时间进行跟踪。其他总结报告（例如，与估计和缺失的出生体重相比，测量的出生体重比例增加）说明了研究中心如何随着时间的推移提高质量。高质量的MPPBR，如MNHR，为缺乏民事登记系统的地方和国际卫生官员提供了关于怀孕结果的关键信息。国家人权机构已采取措施监测数据收集程序，并提高所收集数据的质量。随着时间的推移，研究中心越来越多地实现了可接受的性能指标值，这表明数据质量有所改善，但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妊娠和围产期健康研究方案的影响。NCT01073475
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). 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. 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. 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. NCT01073475