ArticleJMIR medical informatics2022
Identification of Preterm Labor Evaluation Visits and Extraction of Cervical Length Measures from Electronic Health Records Within a Large Integrated Health Care System: Algorithm Development and Validation.
Article in JMIR medical informatics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
5 citing papers in PubMed, 11 citations in OpenAlex.
- Impact of Preterm Birth Subtype on Risk of Diagnosis of Autism Spectrum Disorders in the Offspring.Journal of autism and developmental disorders · 2025Article
- Identifying Hemolytic Disease of the Fetus and Newborn within a Large Integrated Health Care System.American journal of perinatology · 2025Article
- Artificial intelligence in abdominal and pelvic ultrasound imaging: current applications.Abdominal radiology (New York) · 2025Review
- Fine Particulate Matter, Its Constituents, and Spontaneous Preterm Birth.JAMA network open · 2024Article
- Article
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Authors and funding
11 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundPreterm birth (PTB) represents a significant public health problem in the United States and throughout the world. Accurate identification of preterm labor (PTL) evaluation visits is the first step in conducting PTB-related research.
objectiveWe aimed to develop a validated computerized algorithm to identify PTL evaluation visits and extract cervical length (CL) measures from electronic health records (EHRs) within a large integrated health care system.
methodsWe used data extracted from the EHRs at Kaiser Permanente Southern California between 2009 and 2020. First, we identified triage and hospital encounters with fetal fibronectin (fFN) tests, transvaginal ultrasound (TVUS) procedures, PTL medications, or PTL diagnosis codes within 24
resultsA total of 441,673 live birth pregnancies were identified between 2009 and 2020. Of these, 103,139 pregnancies (23.35%) had documented PTL evaluation visits identified by the computerized algorithm. The trend of pregnancies with PTL evaluation visits slightly decreased from 24.41% (2009) to 17.42% (2020). Of the first 103,139 PTL visits, 19,439 (18.85%) and 44,423 (43.97%) had an fFN test and a TVUS, respectively. The percentage of first PTL visits with an fFN test decreased from 18.06% at 24
conclusionsThe developed computerized algorithm effectively identified PTL evaluation visits and extracted the corresponding CL measures from the EHRs. Validation against this algorithm achieved a high level of accuracy. This computerized algorithm can be used for conducting PTL- or PTB-related pharmacoepidemiologic studies and patient care reviews.
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