Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Brief Communication
  • Published:

Severe maternal morbidity rates in a US-based electronic health record database, 2018–2022

Journal of Perinatology volume 43, pages 1316–1318 (2023)Cite this article

Subjects

Severe maternal morbidity (SMM) result in short and long-term health consequences and increased costs, representing a major public health problem. More insight into the risk factors and health disparities that contribute to SMM would inform potential strategies to reduce SMM. Our objective was to determine contemporary rates of delivery-related SMM and provide evidence to enhance understanding of risk factors associated with delivery-related SMM in a large diverse US population using electronic health record (EHR) data.

This retrospective cross sectional study utilizes Epic Systems Corporation’s (Epic) Cosmos research platform, a newly available US-based EHR database which provides anonymized patient-level data [1]. Epic provides services to one-third of US hospitals. To date, approximately 200 health systems (>1000 hospitals) contribute data to Cosmos, containing data from >190 million patients. Individuals with an inpatient delivery hospitalization encounter or billing and diagnostic codes for childbirth from 01/01/2018 to 12/31/2022 were included. There were no exclusion criteria. For individuals with >1 delivery during the study period, we randomly selected 1 delivery for inclusion. SMM cases were identified using the US Centers for Disease Control and Prevention (CDC)’s algorithm based on 21 SMM indicators and corresponding ICD-10 codes [2]. We calculated rates of overall SMM with and without blood transfusion during the delivery hospitalization. Additionally, rates of SMM were calculated based on patient sociodemographic factors such as age, race and ethnicity, insurance type, and social vulnerability index (SVI) [3], medical comorbidities, and delivery mode. Deaths during the childbirth encounter were identified by an “expired” discharge disposition. This study of deidentified data was deemed exempt from review by the Nemours Children’s Hospital Institutional Review Board.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

References

  1. Tarabichi YFA, Honeywell S, Huang C, Naidech AM, Moore JH, Kaelber DC. The cosmos collaborative: a vendor-facilitated electronic health record data aggregation platform. ACI Open. 2021;05:e36–46.

    Article  Google Scholar 

  2. https://www.cdc.gov/reproductivehealth/maternalinfanthealth/smm/severe-morbidity-ICD.htm Appendix 2. Severe morbidity indicators and corresponding ICD-9-CM/ICD-10-CM/PCS codes during delivery hospitalizations. Accessed 25 Jul 2022.

  3. https://www.atsdr.cdc.gov/placeandhealth/svi/index.html Centers for disease control and prevention social vulnerability index. Accessed 25 Jul 2022.

  4. Fink DA, Kilday D, Cao Z, Larson K, Smith A, Lipkin C, et al. Trends in maternal mortality and severe maternal morbidity during delivery-related hospitalizations in the United States, 2008 to 2021. JAMA Network Open. 2023;6:e2317641.

    Article  PubMed  PubMed Central  Google Scholar 

  5. Son M, Gallagher K, Lo JY, Lindgren E, Burris HH, Dysart K, et al. Coronavirus disease 2019 (COVID-19) pandemic and pregnancy outcomes in a U.S. population. Obstet Gynecol. 2021;138:542–51.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Obstetrics, Gynecology, and Reproductive Sciences, Yale School of Medicine, New Haven, CT, USA

    Moeun Son & Jennifer F. Culhane

  2. Department of Obstetrics and Gynecology, University of South Florida, Tampa, FL, USA

    Judette M. Louis

  3. Division of Neonatology, The Children’s Hospital of Philadelphia, Philadelphia, PA, USA

    Sara C. Handley & Heather H. Burris

  4. Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA

    Sara C. Handley & Heather H. Burris

  5. Leonard Davis Institute of Health Economics, Philadelphia, PA, USA

    Sara C. Handley & Heather H. Burris

  6. Division of Neonatology, Nemours Children’s Hospital, Wilmington, DE, USA

    Jay Greenspan & Kevin Dysart

  7. Sidney Kimmel Medical College, Thomas Jefferson University, Philadelphia, PA, USA

    Jay Greenspan & Kevin Dysart

  8. Department of Obstetrics and Gynecology, University of Colorado School of Medicine, Aurora, CO, USA

    Kathryn M. McKenney

Authors
  1. Moeun Son
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Jennifer F. Culhane
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Judette M. Louis
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Sara C. Handley
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Heather H. Burris
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Jay Greenspan
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Kathryn M. McKenney
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Kevin Dysart
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

MS made substantial contribution to the conception and design of the work, interpretation of the data, drafted the work, and agrees to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. JFC, JML, SCH, HHB, JG and KMM made substantial contributions to the conception and design of the work, reviewed the work critically for important intellectual content, give final approval of the version to be published, and agree to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. KD made substantial contributions to the conception and design of the work, acquired, analyzed, and interpreted the data for the work, reviewed the work critically for important intellectual content, gives final approval of the version to be published, and agrees to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

Corresponding author

Correspondence to Moeun Son.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Son, M., Culhane, J.F., Louis, J.M. et al. Severe maternal morbidity rates in a US-based electronic health record database, 2018–2022. J Perinatol 43, 1316–1318 (2023). https://doi.org/10.1038/s41372-023-01765-7

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41372-023-01765-7

Search

Advanced search

Quick links