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Enregistrement W4413358662 · doi:10.5334/ijic.nacic24249

The value of service blueprinting and journey mapping to design, develop and implement digitally enabled integrated care.

2025· article· en· W4413358662 sur OpenAlexaboutno aff
Paula Voorheis, Ibukun Abejirinde, Diana Sherifali

Notice bibliographique

RevueInternational Journal of Integrated Care · 2025
Typearticle
Langueen
DomaineMedicine
ThématiqueTelemedicine and Telehealth Implementation
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésBlueprintProcess managementIntegrated careService (business)Value (mathematics)Computer scienceEngineering managementService designKnowledge managementEngineeringSystems engineeringSoftware engineeringHealth careBusinessService delivery framework

Résumé

récupéré en direct d'OpenAlex

Summary: As co-design and co-creation are increasingly used to develop and implement models of integrated health and social care, practitioners will have to choose from an array of potential approaches and methods. This workshop will present and teach delegates about service blueprinting as a tool uniquely well positioned for integrated care. Background:Health systems globally are increasingly adopting co-design and co-creation methods to guide the development and implementation of integrated models of care. This method aims to ensure that the patient, end-user and community voices are centered in decisions on who integrated models serve, and how services are delivered, funded, governed and managed.Often referred to as user-centred design, when incorporated into the development of technologies, this approach includes an array of approaches and tools to ensure meaningful patient/carer/community engagement. Patient journey mapping, particularly when linked to service blueprinting is emerging tool to guide co-design and subsequent implementation of digitally enabled integrated care models. In addition to centering the patient or end user, it facilitates sensemaking across multiple layers of human, systems, contextual, resource and technological interactions. Aims and objectives:During this workshop, we will share with delegates three examples from project where service blueprinting and journey mapping has been used to inform the design and implementation of digitally enabled integrated and person-centred models of care delivery. Delegates will learn from these examples and have the opportunity to apply the method with guidance through their own journey mapping and service blueprinting exercise.Audience:All delegates of the conference could benefit from this session, particularly those seeking to engage in co-designing innovative models of care; digitally enabled or otherwise. We would be particularly keen to see a diverse array of delegates from different disciplines and health system roles, as that is a better representation of diverse teams needed to engage in this work. As such this would be of interest to patients and family caregivers, researchers, frontline providers, managers, system leaders and decision-makers, policy makers, informaticians, and industry partners. Approach:The lead facilitator (C. Steele Gray) will first introduce the concept of service blueprinting and journey mapping and share an example of its use to design a digitally enabled hospital to home transition model (the Digital Bridge Project). Two more examples from an integrated diabetes remission model (P. Voorheis D. Sherifali), and a project that developed integrated service pathways for immigrants and refugees in Ontario (I. Abejirinde) will also be presented. After the presentations, delegates will work in groups to ) create their own journey map using a mock persona; 2) suggest a service blueprint linked to that journey map; which will serve to 3) create a preliminary prototype of a tool or model of care that is responsive to the patients journey.Structure: ) Introduction and Digital Bridge project (8 minutes); 2) Digital Diabetes Care (6 minutes); 3) Immigrant and refugee integrated services (6 minutes) 3) Table Work (30 minutes); 4) Report back (0 minutes) Outcomes:In the final 0 minutes of the session each table will quickly present their journey maps and share one key reflection from their experience that they will take away with them. Delegates will be able to keep the materials used to guide the exercise so that they can replicate for their own organizations and networks. Facilitators will also encourage delegates to build connections in the session so they can continue to share their experiences, tips, and lessons learned in co-designing their models of integrated care. The facilitators of this session currently lead or co-lead collaborative groups in this field and will invite delegates to join as a means to build capacity and networks.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,022
score de la tête « metaresearch » (Gemma)0,026
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: aucune
GenreSignal candidat: Méthodes · Signal consensuel: Méthodes
Score de désaccord entre enseignants0,022
Score d'incertitude au seuil0,117

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0220,026
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0000,001
Bibliométrie0,0020,002
Études des sciences et des technologies0,0050,010
Communication savante0,0090,009
Science ouverte0,0020,014
Intégrité de la recherche0,0020,003
Charge utile insuffisante (le modèle a refusé de juger)0,0100,002

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.

Tête enseignante Opus0,029
Tête enseignante GPT0,343
Écart entre enseignants0,314 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSans objet
Domainenon disponible
GenreMéthodes

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2025
Routes d'admission1
Résumé présentoui

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