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Can electronic health care records be used to monitor and project changes in pregnancy and birth rates after the COVID-19 pandemic societal shutdown?
In this cohort study of pregnancies within a large US university health care system, a model using electronic medical records (used retrospectively from 2017 and modeled prospectively to 2021) projected an initial decline in births associated with the COVID-19 pandemic societal shutdown, predominantly related to fewer conceptions following the societal changes instituted to control COVID-19 spread. This decline was followed by a projected birth volume surge anticipated to occur in summer 2021.
These findings suggest that electronic medical records can be used to model and project birth volume changes and demonstrate that the COVID-19 pandemic societal changes are associated with reproductive choices.
The influence of the COVID-19 pandemic on fertility rates has been suggested in the lay press and anticipated based on documented decreases in fertility and pregnancy rates during previous major societal and economic shifts. Anticipatory planning for birth rates is important for health care systems and government agencies to accurately estimate size of economy and model working and/or aging populations.
To use projection modeling based on electronic health care records in a large US university medical center to estimate changes in pregnancy and birth rates prior to and after the COVID-19 pandemic societal lockdowns.
Design, Setting, and Participants
This cohort study included all pregnancy episodes within a single US academic health care system retrospectively from 2017 and modeled prospectively to 2021. Data were analyzed September 2021.
Pre– and post–COVID-19 pandemic societal shutdown measures.
Main Outcomes and Measures
The primary outcome was number of new pregnancy episodes initiated within the health care system and use of those episodes to project birth volumes. Interrupted time series analysis was used to assess the degree to which COVID-19 societal changes may have factored into pregnancy episode volume. Potential reasons for the changes in volumes were compared with historical pregnancy volumes, including delays in starting prenatal care, interruptions in reproductive endocrinology and infertility services, and preterm birth rates.
This cohort study documented a steadily increasing number of pregnancy episodes over the study period, from 4100 pregnancies in 2017 to 4620 in 2020 (28 284 total pregnancies; median maternal [interquartile range] age, 30 [27-34] years; 18 728 [66.2%] White women, 3794 [13.4%] Black women; 2177 [7.7%] Asian women). A 14% reduction in pregnancy episode initiation was observed after the societal shutdown of the COVID-19 pandemic (risk ratio, 0.86; 95% CI, 0.79-0.92; P < .001). This decrease appeared to be due to a decrease in conceptions that followed the March 15 mandated COVID-19 pandemic societal shutdown. Prospective modeling of pregnancies currently suggests that a birth volume surge can be anticipated in summer 2021.
Conclusions and Relevance
This cohort study using electronic medical record surveillance found an initial decline in births associated with the COVID-19 pandemic societal changes and an anticipated increase in birth volume. Future studies can further explore how pregnancy episode volume changes can be monitored and birth rates projected in real-time during major societal events.
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CME Disclosure Statement: Unless noted, all individuals in control of content reported no relevant financial relationships. If applicable, all relevant financial relationships have been mitigated.
Accepted for Publication: April 1, 2021.
Published: June 3, 2021. doi:10.1001/jamanetworkopen.2021.11621
Open Access: This is an open access article distributed under the terms of the CC-BY License. © 2021 Stout MJ et al. JAMA Network Open.
Corresponding Author: Molly J. Stout, MD, MSCI, Department of Obstetrics and Gynecology, University of Michigan, 1500 E Hospital Center Dr, Von Voigtlander Women’s Hospital 9-019, Ann Arbor, Michigan 48109 (email@example.com).
Author Contributions: Ms Pardo and Mr Garifullin had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.
Concept and design: Stout, Van De Ven, Parekh, Pardo, Garifullin, Fenner, Smith.
Acquisition, analysis, or interpretation of data: Stout, Parekh, Pardo, Garifullin, Xu, Smith.
Drafting of the manuscript: Stout, Pardo, Garifullin.
Critical revision of the manuscript for important intellectual content: Van De Ven, Parekh, Garifullin, Xu, Fenner, Smith.
Statistical analysis: Stout, Pardo, Garifullin.
Administrative, technical, or material support: Stout, Van De Ven, Parekh, Garifullin, Xu, Smith.
Supervision: Van De Ven, Parekh, Fenner, Smith.
Conflict of Interest Disclosures: None reported.
Additional Contributions: We would like to acknowledge Sarah Block, BGS, University of Michigan, who assisted with manuscript preparation and submission. This contribution was uncompensated.
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