Natural Language Processing Improves Reliable Identification of COVID-19 Compared to Diagnostic Codes Alone.

Observational COVID-19 studies often rely on diagnostic codes, but their accuracy and potential for differential misclassification across patient subgroups are unclear. In this proof of concept study, we examined age, race, and ethnicity as predictors of differential misclassification by comparing the classification accuracy of diagnostic codes to classifiers based on natural language processing (NLP) of clinical notes. We assessed differential misclassification in two primary care-based samples from the American Family Cohort: first, a cohort of 5000 patients with COVID-19 status assessed by physicians based on notes; and second, 21,659 patients (out of 1,560,564) who received COVID-specific antivirals.

Heterogeneity of diagnosis and documentation of post-COVID conditions in primary care: A machine learning analysis.

Background: Post-COVID conditions (PCC) have proven difficult to diagnose. In this retrospective observational study, we aimed to characterize the level of variation in PCC diagnoses observed across clinicians from a number of methodological angles and to determine whether natural language classifiers trained on clinical notes can reconcile differences in diagnostic definitions.

Methods: We used data from 519 primary care clinics around the United States who were in the American Family Cohort registry between October 1, 2021 (when the ICD-10 code for PCC was activated) and November 1, 2023.

Setting the Target: Comparing Family Medicine Among US Allopathic Target Schools.

Background And Objectives: Despite the persistent primary care physician shortage over 2 decades of allopathic medical school expansion, some medical schools are absent a department of family medicine; these schools are designated as "target" schools. These absences are important because evidence has demonstrated the association between structured exposure to family medicine during medical school and the proportion of students who ultimately select a career in family medicine. In this study, we aimed to address part of this gap by defining and characterizing the current landscape of US allopathic target schools.

Unintended pregnancy and contraceptive use among women in the U.S. military: a systematic literature review.

U.S. servicewomen's ability to plan pregnancies is of concern to the military in terms of troop readiness and cost and is an important public health issue.

Pediatric brain natriuretic peptide and N-terminal pro-brain natriuretic peptide reference intervals.

Background: Brain natriuretic peptide (BNP) and N-terminal pro-brain natriuretic peptide (NT-proBNP) have been shown to be useful biomarkers for the diagnosis of heart failure. Pediatric reference intervals for these analytes have been reported in part. Previous studies lack large numbers in each group, have not covered all age ranges and have not compared results for BNP with NT-proBNP in simultaneously drawn samples.