Observe, Coach, Assist, Report: A personal support practice framework to build Home and Community Care workforce capacity in Ontario, Canada
Notice bibliographique
Résumé
Background: In Canada, most paid home care is provided by an unregulated workforce of personal support (PS) providers. Given their frequent and consistent interactions with clients, PS providers are well-positioned to identify unaddressed client needs; however little infrastructure exists to communicate these observations with the broader home care team. To support deeper integration of PS providers and their contributions into home care teams, the Observe, Coach, Assist and Report (OCAR) Framework was collaboratively developed in 2015 with point-of care clinicians and practice leaders. Following development, the OCAR Framework was adopted to guide PS practice at a large Canadian homecare agency, but little is known about how OCAR is used in care planning and decision-making at micro, meso, and macro levels. Aims: Since development of the OCAR Framework, the Canadian home care landscape has changed substantially, with the COVID-19 pandemic impacting service volumes, the types of services required; and health human resources, making workforce optimization using OCAR a high priority. The aim of this project was to assess the ongoing relevance and current use of the OCAR framework and identify opportunities for enhanced use both within and outside early adopter organizations. Methods: A cross-sectional approach was taken, using a web-based self-report survey of point-of-care leadership, clinical management, and practice and operations support (education, training, advance practice leaders) staff at SE Health. A proportional quota sampling strategy was employed, recruiting ~30% of eligible staff from each perspective. Participants were asked about the relevance of the OCAR Framework for daily practice; how frequently they used it for various care tasks (e.g., communicating client care needs); and to identify and rate importance of potential opportunities to improve its use (e.g., knowledge about PS provider roles) and helpful integration resources. Results: Survey respondents (n=99) overwhelmingly (81-95%) felt the OCAR Framework was often or almost always relevant to daily practice in the PS provider program. Notable findings include 81% of point-of-care staff report using OCAR regularly with client care documentation; 67% of clinical management often or almost always use OCAR when developing care plans; and 47% of practice and operation support staff often or almost always use OCAR when orienting new hires. Participants felt opportunities to improve SE Health’s use of OCAR were important to support consistency in client care across providers, improve role clarity (i.e., with both clients and staff), and ensure relevant, actionable information is available for providers. Learnings: Without regulation guiding practice standards, organizations are left to set education, training, and documentation requirements, in addition to outlining role and task descriptions. Variability in these professional practice requirements can create role confusion and barriers to integrated care. The OCAR Framework is a practical, relevant, and frequently used integration resource for home care providers, managers, and support staff within this homecare organization. Future planned work aims to expand the use of the OCAR Framework in Canada and beyond by co-designing an implementation toolkit to support delivery of integrated care by leveraging clinical contributions, improving communication, and integrating this important workforce into the home care team.
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 | 0,018 | 0,017 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,005 | 0,004 |
| Études des sciences et des technologies | 0,018 | 0,012 |
| Communication savante | 0,010 | 0,004 |
| Science ouverte | 0,006 | 0,012 |
| Intégrité de la recherche | 0,002 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 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 ».