Statnikov Yevgeniy, Ibrahim Buthaina, Modi Neena
Neonatal Data Analysis Unit, Section of Neonatal Medicine, Department of Medicine, Imperial College London, Chelsea & Westminster Hospital campus, London, UK.
Section of Neonatal Medicine, Department of Medicine, Imperial College London, Chelsea & Westminster Hospital campus, London, UK.
Arch Dis Child Fetal Neonatal Ed. 2017 May;102(3):F270-F276. doi: 10.1136/archdischild-2016-312010. Epub 2017 Jan 13.
High quality information, increasingly captured in clinical databases, is a useful resource for evaluating and improving newborn care. We conducted a systematic review to identify neonatal databases, and define their characteristics.
We followed a preregistered protocol using MesH terms to search MEDLINE, EMBASE, CINAHL, Web of Science and OVID Maternity and Infant Care Databases for articles identifying patient level databases covering more than one neonatal unit. Full-text articles were reviewed and information extracted on geographical coverage, criteria for inclusion, data source, and maternal and infant characteristics.
We identified 82 databases from 2037 publications. Of the country-specific databases there were 39 regional and 39 national. Sixty databases restricted entries to neonatal unit admissions by birth characteristic or insurance cover; 22 had no restrictions. Data were captured specifically for 53 databases; 21 administrative sources; 8 clinical sources. Two clinical databases hold the largest range of data on patient characteristics, USA's Pediatrix BabySteps Clinical Data Warehouse and UK's National Neonatal Research Database.
A number of neonatal databases exist that have potential to contribute to evaluating neonatal care. The majority is created by entering data specifically for the database, duplicating information likely already captured in other administrative and clinical patient records. This repetitive data entry represents an unnecessary burden in an environment where electronic patient records are increasingly used. Standardisation of data items is necessary to facilitate linkage within and between countries.
临床数据库中越来越多地收集到高质量信息,这是评估和改善新生儿护理的有用资源。我们进行了一项系统综述,以识别新生儿数据库并定义其特征。
我们遵循预先注册的方案,使用医学主题词(MeSH)检索MEDLINE、EMBASE、CINAHL、科学网和OVID母婴护理数据库,查找识别涵盖多个新生儿病房的患者层面数据库的文章。对全文进行评审,并提取有关地理覆盖范围、纳入标准、数据来源以及母婴特征的信息。
我们从2037篇出版物中识别出82个数据库。在特定国家的数据库中,有39个地区性和39个全国性的。60个数据库根据出生特征或保险覆盖范围限制新生儿病房入院记录;22个没有限制。53个数据库专门采集数据;21个来自行政来源;8个来自临床来源。两个临床数据库拥有关于患者特征的最大范围的数据,即美国的Pediatrix BabySteps临床数据仓库和英国的国家新生儿研究数据库。
存在一些有潜力为评估新生儿护理做出贡献的新生儿数据库。大多数数据库是通过专门为数据库输入数据创建的,重复了可能已在其他行政和临床患者记录中采集的信息。在越来越多地使用电子患者记录的环境中,这种重复的数据录入是不必要的负担。数据项的标准化对于促进国内和国际间的链接是必要的。