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Related Experiment Video

Updated: Oct 19, 2025

Microsatellite DNA Genotyping and Flow Cytometry Ploidy Analyses of Formalin-fixed Paraffin-embedded Hydatidiform Molar Tissues
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A comprehensive digital phenotype for postpartum hemorrhage.

Amanda B Zheutlin1, Luciana Vieira2, Ryan A Shewcraft1

  • 1Sema4, Stamford, Connecticut, USA.

Journal of the American Medical Informatics Association : JAMIA
|September 24, 2021
PubMed
Summary
This summary is machine-generated.

A new digital phenotype accurately identifies postpartum hemorrhage (PPH) using electronic health records, improving upon traditional blood loss estimates. This advance aids in tracking PPH outcomes and developing better interventions.

Keywords:
digital phenotypeelectronic medical recordsmaternal morbiditypostpartum hemorrhage

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Area of Science:

  • Obstetrics and Gynecology
  • Digital Health
  • Clinical Informatics

Background:

  • Current postpartum hemorrhage (PPH) guidelines rely on blood loss estimates, which are often inaccurate and biased.
  • Electronic medical records (EMRs) contain valuable data for a more comprehensive PPH phenotype.
  • Incomplete phenotyping hinders PPH outcome tracking, risk assessment, and intervention development.

Purpose of the Study:

  • To establish a comprehensive digital phenotype for postpartum hemorrhage (PPH).
  • To leverage EMR data for more accurate and complete PPH identification.
  • To improve PPH outcome tracking and inform preventative strategies.

Main Methods:

  • A cohort of 71,944 deliveries was analyzed using EMR data.
  • Postpartum blood loss, hematocrit shifts, uterotonics, surgical interventions, and diagnostic codes were combined to identify PPH.
  • A physician-led chart review validated the developed digital phenotype against alternate methods.

Main Results:

  • The digital phenotype identified 6,639 PPH deliveries (9% prevalence), over three times more than blood loss alone.
  • The developed phenotype demonstrated 89% accuracy and an F1-score of 0.92 upon chart review.
  • This digital phenotype outperformed a blood loss-based definition (67% accuracy) and a prior digital phenotype (74% accuracy).

Conclusions:

  • A scalable, accurate, and valid digital phenotype for PPH has been developed.
  • This digital phenotype can significantly aid in tracking PPH outcomes.
  • The phenotype supports ongoing clinical research for improved PPH preventative interventions.