Using electronic medical records to understand the impact of SARS-CoV-2 lockdown measures on maternal and neonatal outcomes in Kampala, Uganda.
Using electronic medical records to understand the impact of SARS-CoV-2 lockdown measures on maternal and neonatal outcomes in Kampala, Uganda.
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DOI：
10.1371/journal.pgph.0002022
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发表时间：
2023
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Kawempe国家转诊医院是一家三级医院，每年收治21 000多名孕妇或产后妇女。这家位于乌干达坎帕拉的医院使用电子病历（EMR）系统来获取患者数据。自2017年以来，这种随时可用的电子健康记录（EHR）具有为实时临床护理提供信息的优点，特别是在COVID-19等大流行期间。我们研究了使用EHR评估不良妊娠和婴儿结局的风险因素，这些因素可以纳入数据可视化仪表板，以便在流行病期间进行真实的决策。这项研究分析了在COVID-19大流行封锁前、封锁期间和封锁后收集的乌干达EMR数据，以确定其在监测不良妊娠和新生儿结局风险因素中的用途。Logistic回归模型用于确定不良妊娠和孕产妇结局的危险因素，包括早产、产科并发症、死产和新生儿死亡。我们采用皮尔逊卡方检验对疫情不同阶段的结果进行配对比较。数据分析在国际COVID-19数据联盟（ICODA）工作台内的R中进行。基于风险因素开发了可视化仪表板，以支持决策和改善医疗保健服务。封锁前后变量的比较显示早产风险增加（调整的比值比（aOR = 1.67，95%置信区间（CI）1.38-2.01））;产科并发症（aOR = 2.77，95% CI：2.53-3.03）;新生儿即刻死亡（aOR = 3.89，95% CI 2.65-5.72）和剖腹产（aOR = 1.22，95% CI 1.11-1.34）。不良结局的显著危险因素是母亲年龄较小和分娩时胎龄<32周。这项研究表明，使用电子健康记录，以确定和监测在真实的时间获得卫生服务的危险亚群的可行性。这一信息对于在疾病暴发和大流行情况下制定及时和适当的干预措施至关重要。
Kawempe National Referral Hospital (KNRH) is a tertiary facility with over 21,000 pregnant or postpartum women admitted annually. The hospital, located in Kampala, Uganda, uses an Electronic Medical Records (EMR) system to capture patient data. Used since 2017, this readily available electronic health record (EHR) has the benefit of informing real-time clinical care, especially during pandemics such as COVID-19. We investigated the use of EHR to assess risk factors for adverse pregnancy and infant outcomes that can be incorporated into a data visualization dashboard for real time decision making during pandemics. This study analysed data from the UgandaEMR collected at pre-, during- and post-lockdown timepoints of the COVID-19 pandemic to determine its use in monitoring risk factors for adverse pregnancy and neonatal outcomes. Logistic regression models were used to identify the risk factors for adverse pregnancy and maternal outcomes including prematurity, obstetric complications, still births and neonatal deaths. Pearson chi-square test was used for pair-wise comparison of the outcomes at the various stages of the pandemic. Data analysis was performed in R, within the International COVID-19 Data Alliance (ICODA) workbench. A visualisation dashboard was developed based on the risk factors, to support decision making and improved healthcare delivery. Comparison of pre-and post-lockdown variables showed an increased risk of pre-term birth (adjusted Odds Ratio (aOR = 1.67, 95% confidence interval (CI) 1.38–2.01)); obstetric complications (aOR = 2.77, 95% CI: 2.53–3.03); immediate neonatal death (aOR = 3.89, 95% CI 2.65–5.72) and Caesarean section (aOR = 1.22, 95% CI 1.11–1.34). The significant risk factors for adverse outcomes were younger maternal age and gestational age <32weeks at labour. This study demonstrates the feasibility of using EHR to identify and monitor at-risk subpopulation groups accessing health services in real time. This information is critical for the development of timely and appropriate interventions in outbreaks and pandemic situations.