Barriers to Hepatitis C Virus Care and How Federally Qualified Health Centers Can Improve Patient Access to Treatment
Notice bibliographique
Résumé
Background: Despite the availability of direct-acting antiviral agents (DAAs) for hepatitis C virus (HCV) treatment, disparities in HCV care and treatment persist for underserved populations due to demographic-based and insurance-based barriers. We aim to examine the effect of barriers on HCV treatment access for a federally qualified health center (FQHC) population. Methods: We retrospectively evaluated medical records of adults diagnosed with chronic HCV at an FQHC clinic from 2016 to 2020 with follow-up through 2021. Univariate and bivariate analyses were used to describe the patient population and significant associations between predictors of linkage to HCV care and treatment access. Adjusted multivariate logistic regression analyses were used to identify predictors of starting HCV treatment. Results: Of 279 total patients with chronic HCV, 162 patients started treatment (58%), 138 patients (50%) completed treatment, and 99 patients (35%) achieved sustained virological response (SVR). Of the total patients, 145 (52%) were seen by their primary care physician (PCP) for their HCV care and treatment, and 134 (48%) were seen by a provider that specializes in management and treatment of HCV (HCV provider). Patients seen by an HCV provider in addition to their PCP were more likely to have had their prior authorization requests for HCV treatment denied by their insurance providers than patients seen only by their PCP for HCV care (30% vs. 14%, P = 0.001). We believe that this discrepancy stems from two issues. One, prior authorizations are reviewed by insurance providers who are not specially trained in HCV management, so the verbiage used perplexes these reviewers, possibly causing them to issue denials. Two, insurance providers often require HCV genotype testing for DAA medication eligibility, and HCV providers order genotype tests for patients only when HCV treatments have failed to cure patients, so this requirement becomes another barrier to DAA medications. Patients who spoke a non-English language, lived in the USA for less than 10 years, and showed inability to pay for treatment had received treatment despite these characteristics being common barriers to HCV treatment. On multivariate regression, factors independently associated with patients starting treatment included prior denial for DAA medication (odds ratio (OR), 8.88; 95% confidence interval (CI), 3.22 - 24.6; P < 0.001) and being seen by an HCV provider (OR, 24.8; 95% CI, 11.7 - 52.5; P < 0.001). However, the most significant barrier to HCV treatment access for the FQHC population was eligibility restrictions from insurance providers. Conclusions: Demographic-based barriers (e.g., age, race, and income) often impede HCV care and treatment, but insurance-based barriers are the greatest challenge currently that affects treatment outcomes in our study population. Removing these restrictions would, in our opinion, help to increase treatment levels to underserved populations.
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 distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,002 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 tête enseignante, 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 ».