ArticleJournal of the American Medical Informatics Association : JAMIA2011
Detecting pregnancy use of non-hormonal category X medications in electronic medical records.
Article in Journal of the American Medical Informatics Association : JAMIA, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
10 citing papers in PubMed.
- Identifying pregnancies in routinely collected health data: a scoping review of methods.BMC medical informatics and decision making · 2026Article
- Validation and Improvement of a Convolutional Neural Network to Predict the Involved Pathology in a Head and Neck Surgery Cohort.International journal of environmental research and public health · 2022Article
- Ontology to identify pregnant women in electronic health records: primary care sentinel network database study.BMJ health & care informatics · 2019Article
- Development of A Machine Learning Algorithm to Classify Drugs Of Unknown Fetal Effect.Scientific reports · 2017Article
- Text Mining of the Electronic Health Record: An Information Extraction Approach for Automated Identification and Subphenotyping of HFpEF Patients for Clinical Trials.Journal of cardiovascular translational research · 2017Article
- Comparison of two methods for collecting antibiotic use data on small dairy farms.Preventive veterinary medicine · 2014Article
- Development and validation of an electronic phenotyping algorithm for chronic kidney disease.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2014Article
- Electronic health records-driven phenotyping: challenges, recent advances, and perspectives.Journal of the American Medical Informatics Association : JAMIA · 2013Article
- Clinical research informatics: a conceptual perspective.Journal of the American Medical Informatics Association : JAMIA · 2012Article
- A review of approaches to identifying patient phenotype cohorts using electronic health records.Journal of the American Medical Informatics Association : JAMIAReview
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivesTo determine whether a rule-based algorithm applied to an outpatient electronic medical record (EMR) can identify patients who are pregnant and prescribed medications proved to cause birth defects.
designA descriptive study using the University of Pennsylvania Health System outpatient EMR to simulate a prospective algorithm to identify exposures during pregnancy to category X medications, soon enough to intervene and potentially prevent the exposure. A subsequent post-hoc algorithm was also tested, working backwards from pregnancy endpoints, to search for possible exposures that should have been detected. MEASUREMENTS: Category X medications prescribed to pregnant patients.
resultsThe alert simulation identified 2201 pregnancies with 16,969 pregnancy months (excluding abortions and ectopic pregnancies). Of these, 30 appeared to have an order for a non-hormone category X medication during pregnancy. However, none of the 30 'exposed pregnancies' were confirmed as true exposures in medical records review. The post-hoc algorithm identified 5841 pregnancies with 64 exposed pregnancies in 52,569 risk months, only one of which was a confirmed case.
conclusionsCategory X medications may indeed be used in pregnancy, although rarely. However, most patients identified by the algorithm as exposed in pregnancy were not truly exposed. Therefore, implementing an electronic warning without evaluation would have inconvenienced prescribers, possibly hurting some patients (leading to non-use of needed drugs), with no benefit. These data demonstrate that computerized physician order entry interventions should be selected and evaluated carefully even before their use, using alert simulations such as that performed here, rather than just taken off the shelf and accepted as credible without formal evaluation.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.