Objective: To develop a rule-based algorithm that detects temporal information of clinical events during pregnancy for women with COVID-19 by inferring gestational weeks and delivery dates from Electronic Health Records (EHR) from the National COVID Cohort Collaborate (N3C). Materials and Methods: The EHR are normalized by the Observational Medical Outcomes Partnership (OMOP) Clinical Data Model (CDM). EHR phenotyping resulted in 270,897 pregnant women (2018-06-01 to 2021-05-31). We developed a rule-based algorithm and performed a multi-level evaluation to test content validity and clinical validity of the algorithm; and extreme value analysis for individuals with <150 or >300 days of gestation. Results: The algorithm identified 296,194 pregnancies (16,659 COVID-19 174 and 744 without COVID-19 peri-pandemic) in 270,897 pregnant women. For inferring gestational age, 95% cases (n=40) have moderate-high accuracy (Cohen Kappa = 0.62); 100% cases (n=40) have moderate-high granularity of temporal information (Cohen Kappa = 1). For inferring delivery dates, the accuracy is 100% (Cohen Kappa = 1). Accuracy of gestational age detection for extreme length of gestation is 93.3% (Cohen Kappa = 1). Mothers with COVID-19 showed higher prevalence in obesity (35.1% vs. 29.5%), diabetes (17.8% vs. 17.0%), chronic obstructive pulmonary disease (COPD) (0.2% vs. 0.1%), respiratory distress syndrome (ARDS) (1.8% vs. 0.2%). Discussion: We explored the characteristics of pregnant women by different timing of COVID-19 with our algorithm: the first to infer temporal information from complete antenatal care and detect the timing of SARS-CoV-2 infection for pregnant women using N3C. Conclusion: The algorithm shows excellent validity in inferring gestational age and delivery dates, which supports national EHR cohorts on N3C studying the impact of COVID-19 on pregnancy.
翻译:目标:开发一种基于规则的算法,通过从国家COVID Cohort合作公司(N3C)的电子健康记录(EHR)中推断孕期周和分娩日期,检测孕期临床事件的时间信息(2018-06-01至2021-05-31)。我们开发了基于规则的算法,测试孕期临床事件的时间信息(N3C),从国家COVID Cohort合作公司(N3C)中推断怀孕周和分娩日期(EHR)。 材料和方法:观察医学结果伙伴关系(OMOPO)临床数据模型(CDM)中将孕期(16 659 COVI-174和744没有COVI-19 临床数据模型(CDM)中将孕期妊娠时间(20-06-01-01至201-05-31-31);我们开发了基于规则的算法算法,并进行了多层次评估:检测内容的有效性(IPA=0.60);对于 < DNA数据(OVA=0.8),100案例(NCOVA 检测日期为10)。