East Toronto Health Partners, working in unison: Integrating care for chronic disease management
Notice bibliographique
Résumé
Background: East Toronto Health Partners (ETHP) is one of 2 Ontario Health Teams selected to advance integrated care in Ontario. In 2024/25 we will be implementing integrated care pathways for three chronic diseases - chronic obstructive pulmonary disease, congestive heart failure, and diabetes (lower limb preservation). Through extensive provider, partner, and community engagement we co-designed a model reflecting our ideal future state. Approach: From November 2023 to May 2024, we completed a rapid planning and co-design process using an iterative, agile approach rooted in deep engagement. Key success factors included:. Meaningful Co-Design and Needs Identification with over 50 people through different methodologies, including: Patient and caregiver (people) partnership in all engagement forums, featuring individuals with relevant lived experience. People journey mapping and needs assessments to obtain consensus on the needs of providers, patients, and caregivers Partner asset mapping (programs and services) Iterative pathway design with diverse representation, including primary care, specialists, community agencies, hospital staff, rehabilitation, home care, patients, and caregivers. Governance through a multi-sectoral advisory committee. Engagement with Community Advisory Councils, Caregiver Groups, and neighbourhood Resident Committees 2. Co-Designing clear objectives and impact statements, anchored in the Quintuple Aim. 3. Co-Creating design principles to guide our decisions and revisiting these principles regularly to resolve emerging tensions. 4. Iterative co-design sessions to build the model of care and pathwaysLevel : What are we doing? (specifying objectives) Level 2: Who does what? (clarifying interactions) Level 3: How? (detailing processes) 5. Leveraging evaluation expertise and implementation science, including embedding evaluation scientists to ground the planning and design process in research and evidence, including performance measurement metrics, rapid cycle improvement and implementation science. 6. Mapping existing programs and services across partner organizations and transforming these assets into a navigational tool using PowerBI. 7. Building the ideal future state, together using extensive engagement and co-design. Emphasizing evidence-based patient-centred care across sectoral, organizational, and professional boundaries while embedding self-management, addressing social determinants of health and health equity. Results: Together we achieved consensus on a future state population-level model of integrated care for chronic disease management. The model is scalable to include different diseases including co-morbidities and includes several key features. Low Barrier Eligibility: No requirement for provincial health insurance or having a primary care provider. Multiple access and referral points: Ensuring no wrong doors. Dispersed neighborhood accessibility: Bringing care closer to communities. Concerted intake and service connection support: Guiding individuals through the care journey. Comprehensive and holistic assessments: Covering clinical, social, mental health, and co-morbidity aspects. Personalized care planning: Tailoring care to individual needs and goals. Evidence-Based clinical guidance: Standardizing care delivery based on evidence and proven practices. Case and care management: Provided by clinically trained resources who coordinate with the care team. Medication management: Clear support for medications to obtain desired outcomes. Ongoing follow-up and monitoring: Ensuring continuity and effectiveness of care. Care team rounding support: Facilitating collaboration and communication within the care team. Embedded self-management and education: At every step of the pathway. Digital enablers: Supporting team-based care planning and service connections through digital tools. Implications: Our learnings emphasize the necessity of broad engagement and input in designing population-level care models to first develop an ideal future state which can be used to align vision, ensure scalability and future-proof our efforts. The management of chronic diseases is complex, and designing isolated pathways without broad participation only further adds to system fragmentation.Moving forward, we will focus on implementing our first pathway. Our objective is to continuously iterate, improve, and scale implementation grounded in rigorous evaluation. Initial outcomes will be shared at the NACIC24 conference.
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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 | 0,010 | 0,009 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,009 | 0,004 |
| Communication savante | 0,006 | 0,003 |
| Science ouverte | 0,001 | 0,007 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,011 | 0,001 |
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 ».