Engaging Primary Care using participatory evaluation:  Approaches to uncovering end-user needs of an Integrated Medical Record.
Notice bibliographique
Résumé
Given the unique role Primary Care plays in the health journeys of their patients capturing their perspectives on harmonized electronic medical records is critical. In Ontario, Canada, our multi-disciplinary, Primary Care led working group evaluated clinicians’ needs in the context of a “One Person, One Record” health information system. Previous quantitative phases of our work indicated that primary care clinicians had interest in supporting it but concerns that required attention such as data considerations, information exchange, practice support, costs, privacy, governance, and practice efficiency and autonomy. We grouped this feedback into three discovery areas; (1)system features, (2) change management, and (3) test of change. In summary, voices of clinicians pointed to a clear need for robust engagement. The question remained how to accomplish this task. Workshop Component(30 minutes) After introducing the audience to the context, the audience will be guided in a group, case-study, problem-solving exercise. The objective of the exercise is to co-design an evaluation-based, primary-care engagement approach within a specific set of parameters (i.e. timeline, funding/ budget, human resources, partners, health teams.) Discovery Component (15 minutes) The tables (groups) will be asked to briefly share their participatory evaluation approaches. Our Approach and Methods(10 minutes) During this component of the workshop, we will walk the audience through the actual method that we used, while drawing upon connections from their insights. In 2023, we undertook the socialization phase of our work using qualitative methods to foster in-depth dialogues on the central themes. Our working group co-designed our engagement approach using diffusion of innovation theory and a complimentary participatory evaluation approach. Primary Care clinicians and administrative personnel (n=54) were engaged in mini focus groups on these topics in the form of a World Café series. The change management themes (and corresponding subsets of probing questions stemming from them) were grouped in to three distinct breakout discussions framed by the following over-arching research questions. SYSTEM NEEDS What system features would be necessary for clinicians to adopt a new integrated EMR? CHANGE MANAGEMENT What actions and supports are necessary for the successful diffusion and uptake of an integrated EMR? TEST OF CHANGE What are the core elements of a primary care pilot that will lead to spread and scale of an integrated EMR? Findings(10 minutes) This panel will share its, tools, and best practices with audience members on this primary care engagement approach for spread and scale purposes, in addition to the qualitative data representing primary cares’ change management needs. Discussion (15 minutes) Conclusion, Recommendations and Contributions: Recently, the discussion of primary care adopting a Health Information System (HIS) for their practices has been trending across the world. To get there, an in-depth understanding of primary care’s current systems, support and test of change needs is required. Components are not just a one-time assessment; they are ongoing as service levels and requirements mature. This panel will share insights on how to explore key components using a method that has been tested, endorsed, and delivered by primary care.
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 | 0,217 | 0,158 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,003 | 0,002 |
| Études des sciences et des technologies | 0,013 | 0,015 |
| Communication savante | 0,011 | 0,009 |
| Science ouverte | 0,003 | 0,024 |
| Intégrité de la recherche | 0,003 | 0,004 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,008 | 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 ».