The University of Sydney Northern Clinical School, Women and Babies Research, NSW, Australia; Northern Sydney Local Health District, Kolling Institute, Australia.
Department of Obstetrics and Gynaecology, Royal North Shore Hospital, St Leonards, Australia.
Int J Popul Data Sci. 2021 Feb 22;6(1):1381. doi: 10.23889/ijpds.v6i1.1381.
Hospital datasets are a valuable resource for examining prevalence and outcomes of medical conditions during pregnancy. To enable effective research and health planning, it is important to determine whether variables are reliably captured.
To examine the reliability of reporting of gestational and pre-existing diabetes, hypertension, thyroid conditions, and morbid obesity in coded hospital records that inform the population-level New South Wales Admitted Patient Data Collection.
Coded hospital admission data from two large tertiary hospitals in New South Wales, from 2011 to 2015, were compared with obstetric data, collected by midwives at outpatient pregnancy booking and in hospital after birth, as the reference standard. Records were deterministically linked and sensitivity, specificity, positive predictive values and negative predictive values for the conditions of interest were obtained.
There were 36,051 births included in the analysis. Sensitivity was high for gestational diabetes (83.6%, 95% CI 82.4-84.7%), pre-existing diabetes (88.2%, 95% CI 84.1-91.6%), and gestational hypertension (80.1%, 95% CI 78.2-81.9%), moderate for chronic hypertension (53.5%, 95% CI 47.8-59.1%), and low for thyroid conditions (12.9%, 95% CI 11.7-14.2%) and morbid obesity (9.8%, 95% CI 7.6-12.4%). Specificity was high for all conditions (≥97.8%, 95% CI 97.7-98.0) and positive predictive value ranged from 53.2% for chronic hypertension (95% CI 47.5-58.8%) to 92.7% for gestational diabetes (95% CI 91.8-93.5%).
Our findings suggest that coded hospital data are a reliable source of information for gestational and pre-existing diabetes and gestational hypertension. Chronic hypertension is less consistently reported, which may be remedied by grouping hypertension types. Data on thyroid conditions and morbid obesity should be used with caution, and if possible, other sources of data for those conditions should be sought.
医院数据集是研究妊娠期间医疗状况的患病率和结局的宝贵资源。为了进行有效的研究和健康规划,确定变量是否可靠地捕获非常重要。
检查编码住院记录中报告妊娠和既往糖尿病、高血压、甲状腺疾病和病态肥胖的可靠性,这些记录为人群水平的新南威尔士州入院患者数据收集提供信息。
比较了新南威尔士州两家大型三级医院 2011 年至 2015 年的编码住院数据与由助产士在门诊妊娠预约和产后住院期间收集的产科数据,作为参考标准。记录被确定性地链接,获得了感兴趣的疾病的敏感性、特异性、阳性预测值和阴性预测值。
分析中包括 36051 例分娩。妊娠期糖尿病的敏感性很高(83.6%,95%CI 82.4-84.7%),既往糖尿病(88.2%,95%CI 84.1-91.6%)和妊娠期高血压(80.1%,95%CI 78.2-81.9%),慢性高血压的中度(53.5%,95%CI 47.8-59.1%),甲状腺疾病(12.9%,95%CI 11.7-14.2%)和病态肥胖(9.8%,95%CI 7.6-12.4%)。所有疾病的特异性均很高(≥97.8%,95%CI 97.7-98.0%),阳性预测值范围从慢性高血压(47.5%-58.8%)的 53.2%到妊娠期糖尿病(91.8%-93.5%)的 92.7%。
我们的研究结果表明,编码的住院数据是妊娠和既往糖尿病以及妊娠高血压的可靠信息来源。慢性高血压的报告不太一致,可能通过将高血压类型分组来纠正。应谨慎使用甲状腺疾病和病态肥胖的数据,如果可能,应寻求这些疾病的其他数据源。