Validation of pregnancy date estimation from outpatient electronic health record data.

Objectives: Electronic health record (EHR) data can enrich investigation of maternal health and pregnancy in large populations. However, many outpatient care settings lack data infrastructure to record pregnancy start and end dates, limiting the reach of EHR-based research. We examined the accuracy of pregnancy dates estimated from outpatient EHR data, compared to linked state birth certificate data. Materials and Methods: We examined 47 515 pregnancies delivered in OR and CA from the PROMISE study. Pregnancy start and end dates were estimated from outpatient encounter data (procedures, diagnoses), pregnancy episode records (delivery date, gestational age at birth), last menstrual period, estimated due date (EDD), and linkage of clinical records for parents and children. We validated these EHR-derived dates against linked state birth certificates. Results: When estimating pregnancy dates from all available EHR fields, start dates differed from birth certificates by an average of 3.7 days and end dates by 0.2 days. Pregnancy episode data and linked child birthdates enabled most estimates; without these sources, only 490 pregnancies were estimable, which had lower accuracy in end dates (>38 days difference). Estimated start dates were most accurate when based on gestational age and EDD (<1 day, <4 days difference, respectively). Estimated end dates were most accurate when based on child birthdates and episode delivery dates (<1 day difference). Conclusion: In outpatient EHR data, pregnancy episode records and linked child birthdates provide the most accurate estimates of pregnancy timing. For research not requiring precise dating, isolated diagnosis and procedure codes may suffice.