Developing a Patient-Focused Integrated Data Dictionary and Repository
Notice bibliographique
Résumé
Ontario Health Teams (OHTs) are a newer model of intersectoral health care in Ontario, Canada designed to provide integrated care across a variety of sectors and organizations to a large attributed population. With the first cohort of OHTs being approved in 2019 and 4 cohorts being approved thereafter, each existing OHT is in a varying degree of maturity. Under the OHT model, community organizations coordinate with OHTs as a unified team to provide integrated and cohesive care with a focus on population health. This type of coordination invites the challenge of organizing and sharing data across organizational partners in a stream-lined way to deliver timely and evidence-based care. Two OHTs addressed this challenge by developing a data dictionary and repository to better integrate data flow and identify gaps in services to better serve all members of the communities. Based on the collective insights drawn from two OHTs, we present the results of a population health-based data development initiative. This process began with extensive engagement with partner organizations within each OHT and the collective governance teams, including patient and family advisory members. We then developed frameworks to begin asset mapping for data dictionary indicators to develop an understanding of what the current state was in the OHTs. After the indicator mapping was completed, key indicators that were relevant for the current priorities of the OHT as determined in a collective stakeholder process were identified to develop a dynamic and timely data repository within the OHTs. Significant learning has occurred with the development of the data dictionary and repository with the process encountering unexpected needs for education around data literacy and strategies to engage patients and collective governance structures. Because these projects were being engaged simultaneously in two different OHTs that varied by cohort and attributed population demographics, a comparison to identify common and differing enablers and challenges will be undertaken. Next steps once the data dictionary and repositories have been completed will be to evaluate the process and identify educational modules and frameworks that can be developed to promote data development and capacity within the OHTs in order to help them provide evidence-based integrated care to their communities. These resources will enable future collaboration, inform planning and decision-making, and identify existing and potential data gaps within the OHTs. Beyond the OHTs, understanding this process with the resulting frameworks and modules will be applicable across integrated care models of care that desire to build data literacy and capacity and engage in population health.
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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 | 0,087 | 0,127 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,002 |
| Méta-épidémiologie (sens large) | 0,002 | 0,002 |
| Bibliométrie | 0,011 | 0,014 |
| Études des sciences et des technologies | 0,005 | 0,004 |
| Communication savante | 0,017 | 0,028 |
| Science ouverte | 0,008 | 0,017 |
| Intégrité de la recherche | 0,002 | 0,006 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 0,005 |
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 ».