Patient and provider perception of appropriateness, acceptability, and feasibility of behavioral health home (BHH) core components based on program implementation in an urban, safety-net health system
Notice bibliographique
Résumé
Background: This manuscript evaluates patient and provider perspectives on the core components of a Behavioral Health Home (BHH) implemented in an urban, safety-net health system. The BHH integrated primary care and wellness services (e.g., on-site Nurse Practitioner and Care Manager, wellness groups and tools, population health management) into an existing outpatient clinic for people with serious mental illness (SMI). Methods: As the qualitative component of a Hybrid Type I effectiveness-implementation study, semi-structured interviews were conducted with providers and patients 6 months after program implementation, and responses were analyzed using thematic analysis. Valence coding (i.e., positive vs. negative acceptability) was also used to rate interviewees' transcriptions with respect to their feedback of the appropriateness, acceptability, and feasibility/sustainability of 9 well-described and desirable Integrated Behavioral Health Core components (seven from prior literature and two additional components developed for this intervention). Themes from the thematic analysis were then mapped and organized by each of the 9 components and the degree to which these themes explain valence ratings by component. Results: Responses about the team-based approach and universal screening for health conditions had the most positive valence across appropriateness, acceptability, and feasibility/sustainability by both providers and patients. Areas of especially high mismatch between perceived provider appropriateness and measures of acceptability and feasibility/sustainability included population health management and use of evidence-based clinical models to improve physical wellness where patient engagement in specific activities and tools varied. Social and peer support was highly valued by patients while incorporating patient voice was also found to be challenging. Conclusions: Findings reveal component-specific challenges regarding the acceptability, feasibility, and sustainability of specific components. These findings may partly explain mixed results from BHH models studied thus far in the peer-reviewed literature and may help provide concrete data for providers to improve BHH program implementation in clinical settings. Plain language abstract: Many people with serious mental illness also have medical problems, which are made worse by lack of access to primary care. The Behavioral Health Home (BHH) model seeks to address this by adding primary care access into existing interdisciplinary mental health clinics. As these models are implemented with increasing frequency nationwide and a growing body of research continues to assess their health impacts, it is crucial to examine patient and provider experiences of BHH implementation to understand how implementation factors may contribute to clinical effectiveness. This study examines provider and patient perspectives of acceptability, appropriateness, and feasibility/sustainability of BHH model components at 6-7 months after program implementation at an urban, safety-net health system. The team-based approach of the BHH was perceived to be highly acceptable and appropriate. Although providers found certain BHH components to be highly appropriate in theory (e.g., population-level health management), their acceptability of these approaches as implemented in practice was not as high, and their feedback provides suggestions for model improvements at this and other health systems. Similarly, social and peer support was found to be highly appropriate by both providers and patients, but in practice, at months 6-7, the BHH studied had not yet developed a process of engaging patients in ongoing program operations that was highly acceptable by providers and patients alike. We provide these data on each specific BHH model component, which will be useful to improving implementation in clinical settings of BHH programs that share some or all of these program components.
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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 | 0,005 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| 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 ».