Innovating for Complexity and Frailty: Moving the Arrow for Targeted Impact in Integrated Care
Notice bibliographique
Résumé
Fragmented care and communication gaps for patients transitioning between acute care hospitals and home with community care support can lead to poorer patient experience and health outcomes. As a result, there is an urgent need to develop models of care that reduce dependence on hospitals and prevent avoidable readmissions for an ageing and multimorbid population. Since 2019, University Health Network in Toronto, Ontario, Canada has been enrolling patients in an integrated care (IC) program which links patients to one care team through a single contact for support by phone, and provides shared communication and coordination between acute care and home and community care. Our study’s primary objective is to refine and evaluate this existing health and social care pathway among patients with multimorbidity and frailty against quintuple aims and Ontario’s quality standards using a mixed methods design. Our secondary objective will be to scale and spread the program outside our institution, starting with Calgary, Alberta, Canada. An interrupted time series analysis will compare two regression lines and their slopes before and after the onset of COVID-19 (April 1 2020) and before, during and after implementation of our program for our multimorbid and frail senior cohorts. We will also apply a multi-level framework set upon a realist approach to analyze responses from interviews with program leads, clinicians, patients and families in our program and controls who did not receive the program. Starting with an initial cohort of 3228 patients enrolled in the program between June 1 2019 and May 30 2023 admitted to thoracic surgery, vascular surgery, cardiovascular surgery, cardiology, liver transplant, orthopedics, and medicine, there are 372 patients with multimorbidity (defined as having either CHF, COPD, or COVID, plus at least one other chronic condition such as hypertension, diabetes, or dementia) and 568 patients aged 65 years and above who required new homecare and community supports. After linking our site-specific data to provincial administrative datasets, our study will evaluate differences in the proportion of top positive responses to seven patient experience questions, healthcare utilization, mortality, and healthcare costs for our multimorbid and frail seniors enrolled in the IC program compared to those not enrolled, allowing us to identify opportunities for targeted program refinement. To date, our team has conducted six semi-structured interviews with IC leads who spoke of their experiences administering the program and caring for enrolled patients. We intend to expand interviews to patients and families, providers and program leads who participated in the program. Additionally, we will be distributing a survey to providers with IC program experience to measure satisfaction and burnout related to program implementation. Our project provides an opportunity to help inform further IC implementation and evaluation across Ontario, elsewhere in Canada and beyond, while also providing opportunities for discussion of complex program evaluation in IC among individuals with multimorbidity and frailty.
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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 | 0,033 | 0,043 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,003 | 0,002 |
| Études des sciences et des technologies | 0,005 | 0,011 |
| Communication savante | 0,012 | 0,011 |
| Science ouverte | 0,003 | 0,022 |
| Intégrité de la recherche | 0,002 | 0,005 |
| 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 ».