Hall E S, Marsolo K, Greenberg J M
Perinatal Institute, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA.
Department of Biomedical Informatics, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA.
J Perinatol. 2017 Aug;37(8):969-974. doi: 10.1038/jp.2017.70. Epub 2017 May 11.
To better address barriers arising from missing and unreliable identifiers in neonatal medical records, we evaluated agreement and discordance among traditional and non-traditional linkage fields within a linked neonatal data set.
The retrospective, descriptive analysis represents infants born from 2013 to 2015. We linked children's hospital neonatal physician billing records to newborn medical records originating from an academic delivery hospital and evaluated rates of agreement, discordance and missingness for a set of 12 identifier field pairs used in the linkage algorithm.
We linked 7293 of 7404 physician billing records (98.5%), all of which were deemed valid upon manual review. Linked records contained a mean of 9.1 matching and 1.6 non-matching identifier pairs. Only 4.8% had complete agreement among all 12 identifier pairs.
Our approach to selection of linkage variables and data formatting preparatory to linkage have generalizability, which may inform future neonatal and perinatal record linkage efforts.
为了更好地解决新生儿病历中标识符缺失和不可靠所产生的障碍,我们评估了一个链接新生儿数据集中传统和非传统链接字段之间的一致性和不一致性。
这项回顾性描述性分析涵盖了2013年至2015年出生的婴儿。我们将儿童医院新生儿科医生的计费记录与来自一家学术性分娩医院的新生儿病历相链接,并评估了链接算法中使用的一组12个标识符字段对的一致性、不一致性和缺失率。
我们链接了7404份医生计费记录中的7293份(98.5%),所有记录经人工审核后均被视为有效。链接记录平均包含9.1对匹配的标识符和1.6对不匹配的标识符。在所有12个标识符对中,只有4.8%完全一致。
我们选择链接变量和进行链接前数据格式化的方法具有可推广性,这可能为未来新生儿和围产期记录链接工作提供参考。