Factors Associated with Adherence to the HEDIS Quality Measure in Medicaid Patients with Schizophrenia.
Notice bibliographique
Résumé
BACKGROUND: Treatment continuity is a major challenge in the long-term management of patients with schizophrenia; poor patient adherence to antipsychotic drugs has been associated with negative clinical outcomes. Long-acting injectable therapies may improve adherence and lessen the risk for psychiatric-related relapse, often leading to rehospitalization and higher healthcare costs. Therefore, understanding the determinants of adherence to antipsychotics is critical in the management of patients with schizophrenia. OBJECTIVE: To assess the impact of baseline patient characteristics on adherence as measured by the Healthcare Effectiveness Data and Information Set (HEDIS) measure of continuity of antipsychotic medications among patients with Medicaid coverage. METHODS: Medicaid healthcare claims data between 2008 and 2011 from 5 states were used to identify patients who were diagnosed with schizophrenia (aged 25-64 years) and received ≥1 antipsychotic prescriptions in baseline year 2010 and in measurement year 2011. The HEDIS continuity of antipsychotic medications (ie, adherence) measure was defined as the proportion of days covered with any antipsychotic medication ≥80% during the measurement year. The 2 cohorts compared paliperidone palmitate with any other antipsychotics, including quetiapine, risperidone, and haloperidol. The baseline-year characteristics were evaluated as potential predictive factors of adherence in the measurement year using multivariate logistic regressions. The regression models incorporated the inverse probability of treatment weights to control for differences in baseline characteristics between the paliperidone palmitate and the other antipsychotics cohort. RESULTS: Among the 12,990 patients who received an antipsychotic during the study period, 48.6% successfully achieved the continuity criteria in the measurement year. After controlling for other covariates, the odds of adherence were improved by adherence at baseline (odds ratio [OR], 9.42; 95% confidence interval [CI], 8.55-10.39). The use of paliperidone palmitate was associated with a 26% increase in the odds of achieving adherence compared with the use of the other antipsychotics studied (OR, 1.26; 95% CI, 1.14-1.39). In addition, female sex (OR, 1.11; 95% CI, 1.01-1.22), age 55 to 64 years (OR, 1.26; 95% CI, 1.09-1.46) versus age 25 to 34 years, Hispanic race (OR, 1.37; 95% CI, 1.05-1.81) versus white race, and an increase of $10,000 in baseline inpatient costs (OR, 1.11; 95% CI, 1.08-1.15) were associated with greater odds of treatment continuity. CONCLUSIONS: In addition to sex, age, and race, the baseline characteristics that were associated with achieving the HEDIS continuity of antipsychotic medication measure included previous-year adherence, inpatient costs, and the use of paliperidone palmitate. These findings offer insight to healthcare plans that cover Medicaid populations on the effects that patient characteristics and treatment types may have on adherence among patients with schizophrenia.
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 | 0,002 | 0,009 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| 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 | 0,000 |
| Science ouverte | 0,000 | 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 ».