Journal of obstetric, gynecologic, and neonatal nursing : JOGNN
June 9, 2026 · via Europe PMC
Use of a Risk Assessment Tool to Predict Postpartum Hemorrhage in a Community Birth Population.
George EK, Goh AH, Jean-Baptiste MC, Erickson EN.
AI summary — for doctors, generated from the abstract only
The AWHONN postpartum hemorrhage risk assessment tool predicted PPH poorly (AUC 0.53) in US community births, improving only modestly when nulliparity was added.
What was studied
A secondary analysis of 61,246 singleton term vertex home and birth center births (2011-2018) from the MANA Statistics Project database.
Key findings
- PPH occurred in 6.4%
- AWHONN tool AUC 0.53
- Adding nulliparity and cumulative scoring raised AUC to 0.59
Clinical relevance
This suggests the AWHONN tool should not be relied on alone to predict PPH in community birth settings, and preparedness for hemorrhage remains essential.
Who should care
Limitations
Secondary registry data from community births; PPH ascertainment and risk factor recording may vary.
Current PPH risk tools barely beat chance in community births, so be prepared for every birth.
This is an AI-generated summary of the published abstract, not a clinical recommendation. It may not reflect the full text or subsequent updates — verify against the original source before acting on it.
Abstract
Objective
To describe postpartum hemorrhage (PPH) outcomes and evaluate the predictive power of a PPH risk tool in a community birth population.
Design
Secondary data analysis using data from the Midwives Alliance of North America (MANA) Statistics Project 4.0 database.
Setting
United States.
Participants
We analyzed data from the MANA database that pertained to women who had singleton term pregnancies with the fetus in vertex position and gave birth at home or in birth centers from 2011 to 2018 (N = 61,246).
Methods
We calculated descriptive statistics and risk of PPH using the Association of Women's Health, Obstetric and Neonatal Nurses (AWHONN) Postpartum Hemorrhage Risk Assessment Tool. Using logistic regression, we calculated the area under the curve (AUC) three different ways to see how well it predicted actual PPH in our sample. We calculated (a) with the current AWHONN tool, (b) by adding nulliparous women to the medium/high-risk group and multiparous women without additional PPH risk factors to the low-risk group, and (c) by treating the modified AWHONN tool as cumulative PPH risk factors rather than simply as low versus medium/high risk. We performed postestimation tests for goodness of fit, AUC, and correct classification.
Results
In our sample, 6.4% of women (n = 3,899) experienced PPH. The AUC for PPH prediction using the AWHONN tool was 0.53. After adding nulliparity as a PPH risk factor and applying PPH risk scores, the AUC of the tool increased to 0.59.
Conclusion
The AWHONN PPH Risk Assessment Tool was poorly predictive for PPH in this sample. Incorporating additional PPH risk factors may improve accuracy of risk tools.
DOI
10.1016/j.jogn.2026.05.001
PMID
42259458
Research metadata (titles, abstracts, authors, publication dates) is sourced from Europe PMC, which aggregates content from PubMed/MEDLINE, PubMed Central, and other providers under the U.S. National Library of Medicine (NLM/NCBI). NLM does not claim copyright on abstracts; the original journal publishers or authors may hold rights to the full articles. AI-generated summaries are derived only from the abstract, never the full text, and are always labeled as AI-generated.
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