Derivation and external validation of risk stratification models for severe maternal morbidity using prenatal encounter diagnosis codes.

Journal: Journal of perinatology : official journal of the California Perinatal Association
Published Date: May 19, 2021

Abstract

OBJECTIVE: We sought to develop a prediction model using prenatal diagnosis codes that could help clinicians objectively stratify a women's risk for delivery-related morbidity.

Authors

  • Mark A Clapp
    Department of Obstetrics and Gynecology, Massachusetts General Hospital, Boston, MA, USA. mark.clapp@mgh.harvard.edu.
  • Thomas H McCoy
    Center for Quantitative Health, Department of Psychiatry and Department of Medicine, Massachusetts General Hospital, Boston, MA. Electronic address: thmccoy@partners.org.
  • Kaitlyn E James
    Department of Obstetrics and Gynecology, Massachusetts General Hospital, Boston, MA, USA.
  • Anjali J Kaimal
    Department of Obstetrics and Gynecology, Massachusetts General Hospital, Boston, MA, USA.
  • Roy H Perlis
    Center for Quantitative Health, Massachusetts General Hospital, Boston, MA, USA.

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