Who Said What Now and How? Evaluating Saskatchewan's Patient-Reported Measures in Primary Care
Notice bibliographique
Résumé
Background: A team of patient partners, researchers, and health system collaborators evaluated the pilot implementation of patient reported metrics in primary care health networks in Saskatchewan, Canada with the intent to recommend best practices for provincial scale-up. Approach: The Saskatchewan Health Authority (SHA) is responsible for health services in Saskatchewan, Canada, including the delivery of primary care services across 38 health networks. Health networks are intended to connect teams of healthcare professionals and community partners to meet the needs of the people they serve. To ensure that the health system delivers care that matters to patients, the People Centred Measurement (PCM) working group, an SHA, patient, and health system partner collaboration, was established in 2020. In November 2022, the PCM working group launched an initiative called Integrating Patient Reported Data into Health Networks in Saskatchewan For this pilot project, an online survey was developed and implemented in 4 of 38 health networks to gather patient reports of their primary care experiences. University of Saskatchewan (USask) researchers and three patient partners who were embedded in the PCM working group engaged in a developmental evaluation of the pilot initiative to recommend policy options to scale up the implementation of patient reported data across Saskatchewan health networks. Working alongside the principal knowledge user who was the PCM working group director and a collaborator who led the development and implementation of the survey, one USask researcher attended all health network meetings and offered evaluative feedback in real time. Early in the evaluation, the researchers and patient partners produced an initial report suggesting the need to increase patient partner engagement and the limitations of a survey approach to the collection of patient reported experiences. Given the PCM imperative to implement patient reported measurement using the survey, the research team was encouraged to engage in a new data collection strategy. The research team pivoted to directly gather perspectives of the pilot project participants using semi-structured virtual interviews. Results: Based on 5 interviews with participants, patient partners and researchers presented the following recommendations at an end of project policy forum: a) Ensure resources for onboarding and support of patients and community members to contribute to ongoing People-Centred Measurement, b) Build processes that engage Indigenous communities, newcomers, hard-to-reach and under-served populations in a meaningful way that directly impacts their experience of care c) Foster relationships and collaboration across SHA portfolios to leverage expertise in People-Centred Measurement design and implementation d) Recognize the difference in capacity between remote, rural, and urban healthcare centres and co-design People-Centred Measurement strategies accordingly, and e) Continuously evaluate People-Centred Measurement implementation and adapt to changing social, economic, and environmental contexts. Implications: With the growing need to incorporate PCM into healthcare systems to deliver on the promise of patient-centred care, Saskatchewan is gradually improving its collection, analysis, and dissemination. Driven by patient partner engagement, findings from our evaluation will inform what is required for the successful collection of patient-reported experience and outcome measures to inform policies that will improve the health of SK people.
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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 | 0,038 | 0,039 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,002 | 0,003 |
| Études des sciences et des technologies | 0,008 | 0,002 |
| Communication savante | 0,005 | 0,002 |
| Science ouverte | 0,003 | 0,005 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 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 ».