Transitional Care Support for Medicaid-Insured Patients With Serious Mental Illness: Protocol for a Type I Hybrid Effectiveness-Implementation Stepped-Wedge Cluster Randomized Controlled Trial
Notice bibliographique
Résumé
BACKGROUND: People diagnosed with a co-occurring serious mental illness (SMI; ie, major depressive disorder, bipolar disorder, or schizophrenia) but hospitalized for a nonpsychiatric condition experience higher rates of readmissions and other adverse outcomes, in part due to poorly coordinated care transitions. Current hospital-to-home transitional care programs lack a focus on the integrated social, medical, and mental health needs of these patients. The Thrive clinical pathway provides transitional care support for patients insured by Medicaid with multiple chronic conditions by focusing on posthospitalization medical concerns and the social determinants of health. This study seeks to evaluate an adapted version of Thrive that also meets the needs of patients with co-occurring SMI discharged from a nonpsychiatric hospitalization. OBJECTIVE: This study aimed to (1) engage staff and community advisors in participatory implementation processes to adapt the Thrive clinical pathway for all Medicaid-insured patients, including those with SMI; (2) examine utilization outcomes (ie, Thrive referral, readmission, emergency department [ED], primary, and specialty care visits) for Medicaid-insured individuals with and without SMI who receive Thrive compared with usual care; and (3) evaluate the acceptability, appropriateness, feasibility, and cost-benefit of an adapted Thrive clinical pathway that is tailored for Medicaid-insured patients with co-occurring SMI. METHODS: This study will use a prospective, type I hybrid effectiveness-implementation, stepped-wedge, cluster randomized controlled trial design. We will randomize the initiation of Thrive referrals at the unit level. Data collection will occur over 24 months. Inclusion criteria for Thrive referral include individuals who (1) are Medicaid insured, dually enrolled in Medicaid and Medicare, or Medicaid eligible; (2) reside in Philadelphia; (3) are admitted for a medical diagnosis for over 24 hours at the study hospital; (4) are planned for discharge to home; (5) agree to receive home care services; and (6) are aged ≥18 years. Primary analyses will use a mixed-effects negative binomial regression model to evaluate readmission and ED utilization, comparing those with and without SMI who receive Thrive to those with and without SMI who receive usual care. Using a convergent parallel mixed methods design, analyses will be conducted simultaneously for the survey and interview data of patients, clinicians, and health care system leaders. The cost of Thrive will be calculated from budget monitoring data for the research budget, the cost of staff time, and average Medicaid facility fee payments. RESULTS: This research project was funded in October 2023. Data collection will occur from April 2024 through December 2025. Results are anticipated to be published in 2025-2027. CONCLUSIONS: We anticipate that patients with and without co-occurring SMI will benefit from the adapted Thrive clinical pathway. We also anticipate the adapted version of Thrive to be deemed feasible, acceptable, and appropriate by patients, clinicians, and health system leaders. TRIAL REGISTRATION: ClinicalTrials.gov NCT06203509; https://clinicaltrials.gov/ct2/show/NCT06203509. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/64575.
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 | 0,035 | 0,034 |
| Méta-épidémiologie (sens strict) | 0,008 | 0,003 |
| Méta-épidémiologie (sens large) | 0,013 | 0,007 |
| Bibliométrie | 0,003 | 0,004 |
| Études des sciences et des technologies | 0,003 | 0,004 |
| Communication savante | 0,006 | 0,004 |
| Science ouverte | 0,005 | 0,003 |
| Intégrité de la recherche | 0,007 | 0,008 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,065 | 0,009 |
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 ».