Faculty of Life and Health Sciences, Ulster University, Belfast, Northern Ireland, United Kingdom.
Population Health Research Institute, St George's University of London, London, United Kingdom.
PLoS One. 2023 Aug 30;18(8):e0290711. doi: 10.1371/journal.pone.0290711. eCollection 2023.
Linking routinely collected healthcare administrative data is a valuable method for conducting research on morbidity outcomes, but linkage quality and accuracy needs to be assessed for bias as the data were not collected for research. The aim of this study was to describe the rates of linking data on children with and without congenital anomalies to regional or national hospital discharge databases and to evaluate the quality of the matched data. Eleven population-based EUROCAT registries participated in a EUROlinkCAT study linking data on children with a congenital anomaly and children without congenital anomalies (reference children) born between 1995 and 2014 to administrative databases including hospital discharge records. Odds ratios (OR), adjusted by region, were estimated to assess the association of maternal and child characteristics on the likelihood of being matched. Data on 102,654 children with congenital anomalies were extracted from 11 EUROCAT registries and 2,199,379 reference children from birth registers in seven regions. Overall, 97% of children with congenital anomalies and 95% of reference children were successfully matched to administrative databases. Information on maternal age, multiple birth status, sex, gestational age and birthweight were >95% complete in the linked datasets for most regions. Compared with children born at term, those born at ≤27 weeks and 28-31 weeks were less likely to be matched (adjusted OR 0.23, 95% CI 0.21-0.25 and adjusted OR 0.75, 95% CI 0.70-0.81 respectively). For children born 32-36 weeks, those with congenital anomalies were less likely to be matched (adjusted OR 0.78, 95% CI 0.71-0.85) while reference children were more likely to be matched (adjusted OR 1.28, 95% CI 1.24-1.32). Children born to teenage mothers and mothers ≥35 years were less likely to be matched compared with mothers aged 20-34 years (adjusted ORs 0.92, 95% CI 0.88-0.96; and 0.87, 95% CI 0.86-0.89 respectively). The accuracy of linkage and the quality of the matched data suggest that these data are suitable for researching morbidity outcomes in most regions/countries. However, children born preterm and those born to mothers aged <20 and ≥35 years are less likely to be matched. While linkage to administrative databases enables identification of a reference group and long-term outcomes to be investigated, efforts are needed to improve linkages to population groups that are less likely to be linked.
将常规收集的医疗保健管理数据进行链接是研究发病率结果的一种有价值的方法，但由于数据不是为研究收集的，因此需要评估链接的质量和准确性，以避免偏差。本研究的目的是描述将患有和不患有先天性异常的儿童的数据与区域或国家医院出院数据库进行链接的比率，并评估匹配数据的质量。11 个基于人群的 EUROCAT 登记处参加了 EUROlinkCAT 研究，将 1995 年至 2014 年间出生的患有先天性异常的儿童（先天性异常儿童）和没有先天性异常的儿童（参考儿童）的数据与包括医院出院记录在内的管理数据库进行链接。通过按地区调整比值比（OR）来评估母婴特征对匹配可能性的影响。从 11 个 EUROCAT 登记处提取了 102654 名患有先天性异常的儿童的数据，从 7 个地区的出生登记处提取了 2199379 名参考儿童的数据。总体而言，97%的先天性异常儿童和 95%的参考儿童成功地与管理数据库相匹配。对于大多数地区，与数据库链接的数据集在母亲年龄、多胎状态、性别、胎龄和出生体重方面的信息完整度>95%。与足月出生的儿童相比，出生于≤27 周和 28-31 周的儿童不太可能被匹配（调整后的 OR 分别为 0.23、95%CI 0.21-0.25 和调整后的 OR 0.75、95%CI 0.70-0.81）。对于出生于 32-36 周的儿童，患有先天性异常的儿童不太可能被匹配（调整后的 OR 为 0.78、95%CI 0.71-0.85），而参考儿童更有可能被匹配（调整后的 OR 为 1.28、95%CI 1.24-1.32）。与 20-34 岁的母亲相比，未成年母亲和≥35 岁的母亲所生的儿童不太可能被匹配（调整后的 OR 分别为 0.92、95%CI 0.88-0.96 和 0.87、95%CI 0.86-0.89）。链接的准确性和匹配数据的质量表明，这些数据适用于大多数地区/国家的发病率研究。然而，早产儿和<20 岁及≥35 岁母亲所生的儿童不太可能被匹配。虽然与管理数据库的链接可以确定参考组并研究长期结果，但需要努力改进与不太可能被链接的人群的链接。
