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Finding Understudied Disorders Potentially Associated with Maternal Morbidity and Mortality
Laritza M Rodriguez1, Dina Demner Fushman1
1Lister Hill National Center for Biomedical Communications, National Library of Medicine, National Institutes of Health, Bethesda, Maryland.
AJP Reports
|March 7, 2019
Summary
Clinical text analysis reveals uncommonly reported conditions in pregnant and postpartum women admitted to intensive care units (ICUs). This highlights knowledge gaps in maternal morbidity and mortality research.
Area of Science:
- Medical Informatics
- Clinical Research
- Obstetrics and Gynecology
Background:
- Maternal morbidity and mortality (MMM) research often overlooks less common causes.
- Intensive care unit (ICU) admissions provide a critical window into severe maternal complications.
Observation:
- Discharge summaries from the MIMIC database were analyzed for pregnant and postpartum women in ICUs.
- Comorbidities were identified using UMLS semantic types and compared to a matched control group.
- 33 disease mentions not typically associated with MMM were discovered.
Findings:
- Significant overlap in diagnoses exists between pregnant and non-pregnant ICU patients.
- A notable percentage of diagnoses were exclusive to the pregnant/postpartum group.
- Clinical notes contain valuable data on underreported maternal health conditions.
Implications:
- Clinical text mining can uncover critical information beyond standard MMM reporting.
- Further research is needed to address identified knowledge gaps in maternal critical care.
- Integrating clinical notes into MMM research can improve understanding and outcomes.
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