Digitizing Integrated Care – Aligning technology to values
Notice bibliographique
Résumé
Introduction: This workshop will build on an international integrated knowledge translation project that seeks to advance meaningful adoption of digital health services to enable delivery of high-quality and equitable person-centred integrated care. Problem: Digital health solutions and services are recognized as critical to achieve person-centred integrated health and social care. To date work in this area has focused on the development and adoption of these technologies in supporting the (functional) activities of integrated care delivery, but less known is how these technologies can advance, or upend, the (normative) values of the communities, teams, and organizations that underpin their vision for greater integration. With the global rapid uptake of digital health tools in the wake of the COVID-19 pandemic, systems are faced with the opportunity to quickly leverage innovative solutions, and the risk of doing so without a clear view the path this adoption sets us up to follow. Audience: To address the problem this workshop will share findings from the work of the Value Aligned Digital Health Consortium to develop a set of recommendations to inform implementation, evaluation, scale and spread of value-aligned technologies in person-centred integrated care. The Consortium includes researchers, providers, systems leaders, industry representatives as well as a central community partnership ensuring representation of diverse patient, caregiver and community stakeholders. As such, the audience for this workshop will include a similar range of representative groups, bringing in additional international perspectives to discuss how recommendations can be refined and adapted to meet local needs and contexts. Structure and engagement: The Consortium has been running a series of deliberative dialogues with diverse stakeholder groups to arrive at recommendations and guidelines. This workshop would run a modified dialogue session in which delegates will discuss and refine recommendations to account for contextual considerations across different regions. Delegates will work in small groups (5-6 per table), facilitated by our team members, to discuss three topics: values, implementation recommendations, and evaluation recommendations. Facilitators will use a live Google Jamboard to record ideas shared by the group. Workshop structure: 1) Introduction and background of the project (10 minute presentation from project co-leads Carolyn Steele Gray and Jay Shaw); 2) Understanding values of integrated care (10 minute presentation by Nick Zonneveld); 3) patient/community reflection from a patient consortium member (8 minutes) 4) Dialogue methods and activity set up (7 minute presentation by Marissa Bird to describe methods and set up the dialogue activity for delegates); 4) Facilitated small group work on 3 topics, values, implementation, evaluation (45 minutes; 15 minutes per topic); 5) Wrap-up (10 minutes – facilitators present the live Jamboards and elicit any additional feedback from delegates. Summarizing take home messages: This workshop will directly inform the final report to be published on this project. We will additionally be generating info-graphics and short videos to help disseminate learning generated by this workshop and the broader project. All delegates of the workshop will be invited to join the Consortium should they wish to have ongoing engagement.
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 | 0,043 | 0,040 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,003 | 0,005 |
| Études des sciences et des technologies | 0,007 | 0,027 |
| Communication savante | 0,030 | 0,037 |
| Science ouverte | 0,005 | 0,033 |
| Intégrité de la recherche | 0,007 | 0,012 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,016 | 0,003 |
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 ».