A Matter of Identity: A Case Study Exploring the Promotion and Influence of Cross-Sector Integrated Care During COVID-19
Notice bibliographique
Résumé
Cross-sector integrated care is increasingly seen as the route to improving health, advancing health equity, and reducing care fragmentation. While considerable literature has examined characteristics of successful integrated care initiatives, less is known about how sectoral, organizational, and professional boundaries may be overcome to support care unification. The field of health services research has much to learn from the rapid collaborative response that ensued during COVID-19. The purpose of this study was to explore and describe the impact of cross-sector integration utilized during COVID-19 at the individual and organizational level, through the Capability, Opportunity, and Motivation to change behaviour model. An exploratory case study was conducted with an inter-sectoral working group who engaged with and provided vaccines to a community of high COVID-19 incidence from April – September 2021 in Toronto, Canada. This study used three sources of data: key informant interviews (n= 10), key stakeholder interviews (n=4), organizational participants (n=2) and a review of relevant documents. Participants included front-line workers, managers, directors and executive directors from hospitals, community health centres, social care, government, and faith organizations. Data were inductively analyzed using Braun and Clark’s (2006) theoretical thematic analysis. Findings suggest that the success of this community centred initiative rested on the remarkable capability and collective efficacy of the inter-sectoral working group. Participants’ professional identity served as a key intrinsic motivator to support the achievement of normative integration during this rapid collaborative response. The fluid interplay of social processes known to facilitate cross-sector collaboration, namely distributive leadership, and informal organizing were central features to this initiative, where community knowledge was considered an essential resource by working group members and system leaders. While participants were proud of their accomplishments, many were disappointed with limited system learnings to advance integrated care, with communities, beyond COVID-19. Recommendations include a call for health system leaders to increasingly draw on opportunities for collective sectoral organizing grounded in complexity thinking, where sentinel focus areas are addressed through population health approaches. Through these collaborative acts, there is opportunity to bridge divides, drawing on internal motivations and collective governance to generate learning inclusive of community, addressing value for the system as a whole.
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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 | 0,012 | 0,017 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,002 | 0,002 |
| Études des sciences et des technologies | 0,028 | 0,013 |
| Communication savante | 0,006 | 0,005 |
| Science ouverte | 0,004 | 0,010 |
| Intégrité de la recherche | 0,005 | 0,007 |
| 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 ».