Mental Health in Medicine: A novel stepped care model in medical psychiatry and the implementation of measurement-based care
Notice bibliographique
Résumé
Introduction Individuals with co-occurring mental and physical health issues have worse health outcomes in both domains. Integration improves outcomes and aligns with patient preference, but health services tend to be siloed. The Mental Health in Medicine Clinic (MHiM) supports patients receiving inpatient or outpatient medical or surgical care at a tertiary academic hospital in Toronto, Canada. The predominantly virtual clinic has an interdisciplinary team offering services via stepped care, matching patient need with service intensity. Measurement-based care (MBC), the systematic evaluation of patient reported outcomes, was not initially used routinely in the clinic, but its implementation may improve treatment decision-making and may be useful in allocating patients within a stepped care model. Objectives 1) To describe the stepped care model, referral patterns, diagnoses, and level of care provided since implementation of stepped care. 2) To conduct a quality improvement initiative to implement MBC in the clinic, with a goal of 50% of patients completing at the time of first assessment and prior to discharge from the clinic. Methods We reviewed the electronic medical record for referral source, diagnoses, and level of stepped care within the clinic. We conducted semi-structured interviews with stakeholders (clinicians, administrative staff, patients) to explore barriers to implementation of MBC. Interviews were analyzed for themes around barriers and facilitators to MBC. Plan, Do, Study, Act cycles were carried out around change concepts informed by stakeholder interviews and relevant literature. Results The MHiM clinic began operations in August 2020. The clinic operated on a physician-only model until March 2022 and then shifted to a stepped care model with an interdisciplinary team. The most frequent referral sources were internal medicine, COVID19 clinics, consultation-liaison psychiatry, red blood cell disorders clinic and cardiology. Since the implementation of stepped care, 250 referrals were assessed. 58% of new referrals were assessed by the psychiatrist, 42% were managed by the NP, and 25% consulted with the social worker. Referrals consisted of trauma and stress-related disorders (32%), depression (21%) or anxiety disorders (20%). Personality, substance use, and psychotic disorders accounted for less than 10% of referrals combined. Some patients did not have any diagnosis (6%). Results from the quality improvement initiative to implement MBC will also be presented. Conclusions The MHiM clinic provides an integrated care pathway addressing comorbid mental and physical health conditions. We describe a novel stepped care model and the implementation of MBC. Future directions include ongoing quality improvement of MBC and its integration within the clinic to assess and re-assess service intensity. Disclosure of Interest None Declared
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 | 0,021 | 0,017 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,002 | 0,002 |
| Études des sciences et des technologies | 0,005 | 0,018 |
| Communication savante | 0,013 | 0,009 |
| Science ouverte | 0,004 | 0,012 |
| Intégrité de la recherche | 0,004 | 0,006 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 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 ».