Testing for Hepatitis C During Pregnancy Among Persons With Medicaid and Commercial Insurance: Cohort Study
Notice bibliographique
Résumé
BACKGROUND: The reported incidence of acute hepatitis C virus (HCV) infection is increasing among persons of childbearing age in the United States. Infants born to pregnant persons with HCV infection are at risk for perinatal HCV acquisition. In 2020, the United States Preventive Services Task Force and Centers for Disease Control and Prevention recommended that all pregnant persons be screened during each pregnancy for hepatitis C. However, there are limited data on trends in hepatitis C testing during pregnancy. OBJECTIVE: We estimated hepatitis C testing rates in a large cohort of patients with Medicaid and commercial insurance who gave birth during 2015-2019 and described demographic and risk-based factors associated with testing. METHODS: Medicaid and commercial insurance claims for patients aged 15-44 years and who gave birth between 2015 and 2019 were included. Birth claims were identified using procedure and diagnosis codes for vaginal or cesarean delivery. Hepatitis C testing was defined as an insurance claim during the 42 weeks before delivery. Testing rates were calculated among patients who delivered and among the subset of patients who were continuously enrolled for 42 weeks before delivery. We also compared the timing of testing relative to delivery among patients with commercial or Medicaid insurance. Multivariable logistic regression was used to identify factors associated with testing. RESULTS: Among 1,142,770 Medicaid patients and 1,207,132 commercially insured patients, 175,223 (15.3%) and 221,436 (18.3%) were tested for hepatitis C during pregnancy, respectively. Testing rates were 89,730 (21.8%) and 187,819 (21.9%) among continuously enrolled Medicaid and commercially insured patients, respectively. Rates increased from 2015 through 2019 among Medicaid (from 20,758/108,332, 19.2% to 13,971/52,330, 26.8%) and commercially insured patients (from 38,308/211,555, 18.1% to 39,152/139,972, 28%), respectively. Among Medicaid patients, non-Hispanic Black (odds ratio 0.73, 95% CI 0.71-0.74) and Hispanic (odds ratio 0.53, 95% CI 0.51-0.56) race or ethnicity were associated with lower odds of testing. Opioid use disorder, HIV infection, and high-risk pregnancy were associated with higher odds of testing in both Medicaid and commercially insured patients. CONCLUSIONS: Hepatitis C testing during pregnancy increased from 2015 through 2019 among patients with Medicaid and commercial insurance, although tremendous opportunity for improvement remains. Interventions to increase testing among pregnant persons are needed.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,001 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».