Understanding and Managing Fragmented Transitions in Care: Learning from and Guided by Patient, Family, Health Care Provider and System-Level Experiences Before, During and Follow-up to COVID-19
Notice bibliographique
Résumé
One ongoing challenge in health care is ensuring patients/families and also health care providers have clear direction and implementation guidance around transitions in care across all care and community settings that includes integration, continuity and coordination. Clearly understanding patient, family, care provider and system-level experiences including what works and where improvements are needed with care transitions across acute and community settings has been an ongoing challenge for most health care systems before and during COVID-19. However, although efforts to identify and use experience measures were complicated and impacted during COVID-19 because of rapidly enforced restrictions and emergent safety protocols, learning to adapt to change was also essential. Our study explored the experiences of patients/clients, families, care providers and system leaders regarding their care transitions between acute and community-based care settings prior to and during COVID-19, along with changes in care outcomes, practices, policies and services became the focus of a two-year pilot study in one Canadian provincial health system. We co-designed relevant acute to community care transition process and outcome/impact experience indicators/measures with patients/clients, families and care providers; and explored the feasibility for transferring measures and lessons learned for practice, policy and service changes as part of follow-up and post COVID new ‘norm’ transformation of care transitions. The study involved the Provincial Seniors and Continuing Care Advisory Council, Continuing Care Quality Committee, Transition Services, primary care and eight pilot care settings involving patients/clients transitioning from acute to community settings. Each care setting involved patient/family advisors co-designing and implementing the initiative with care providers and transition leaders. This included survey development, and gathering, analyzing and interpreting client/patient and care provider experiences. Findings in each and across settings included identifying common core patient/family and care provider experience indicators/measures regarding acute to community care transitions, before and during COVID. System-level factors and experiences were also gathered. Themes for what makes transitions in care successful before, during and follow-up to COVID were also confirmed – e.g. clear communication, navigation and information/direction for all stakeholders. The aggregated findings targeted health outcomes and guided changes in transition practices from across acute points of care as well as Emergency, to various community-based care settings including Home Care, Long-term or other interim programs utilized while patients waited for final transition decisions – e.g. CHOICE programs. Essential learnings include having a clear understanding of the experiences of patients/clients, families, care providers and system-level regarding care transitions, and how well integrated, coordinated and continuity-aligned this care is. This includes understanding what works well and where there are gaps in the system. Managing the gaps helps mitigate failed or unsatisfactory patient transitions across care settings. Such findings also guide or inform quality and safety improvement. Identified transition core measures continue to be studied beyond the pilots for transferability across acute, emergency, primary and community care settings. As well, COVID-19 impacts on practice, policy and service changes involving coordinated and integrated transitions need to be monitored for how well care settings adapt to “new norms” and meet patient/client needs. This work continues.
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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 | 0,024 | 0,038 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,016 | 0,010 |
| Communication savante | 0,009 | 0,007 |
| Science ouverte | 0,005 | 0,019 |
| Intégrité de la recherche | 0,002 | 0,009 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 ».