70 Using human-centred design to better support primary careobesity management: 5as team at home
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Notice bibliographique
Résumé
<h3>Objectives</h3> The WHO has issued a call to implement <i>people-centred</i> strategies to health services. This makes personalised care a priority. Obesity management in primary care is often embedded in other clinical presentations, like diabetes or osteoarthritis. Achieving collaborative encounters in primary care obesity management is difficult. <i>The challenge is how to support constructive engagement to address the unique needs of each individual.</i> To overcome this, it is indispensable to apply a human-centred approach to meet patients’ needs and values. The objective of this project was to collaboratively identify patients’ needs and expectations about tools for obesity management. Also, to co-design with patients and care teams 4 tools to support patient-physician collaborative engagement to identify health goals and create personalised care plans to manage obesity using a human-centred design approach. Human-centred design puts people at the centre. <h3>Method</h3> We developed three co-design workshops: we used personas, role playing, dialogue prompters, and prototypes to foster collaboration and good communication between patients, health professionals and researchers. Five patients participated in the first workshop to identify their needs and expectations about tools to achieve meaningful obesity conversations. This workshop helped develop a list of goals the tools needed to fulfil and create a first prototype. Ten patients and ten healthcare providers participated in the other two co-creation workshops to tailor the tools to the needs of patients and health professionals. Eight videos of obesity encounters helped develop 3 personas. The personas were used to help participants situate themselves in the story of a ‘constructed’ patient. The personas help patients and health professionals to role play a weight management conversation while using the first prototypes. Dialogue prompters were used to collect participants ideas about what worked, why and how to change it. <h3>Results</h3> Diverse communication needs emerged between patients and healthcare professionals. Patients found the first prototype too medical and technical not helping to address their overall health. Health professionals needed the tool to cover more mental health and functional aspects. The co-creation clarified that we needed to differentiate between what the tool should do from what the health professional should do. For example, the tool should <i>support the identification</i> of patients’ strengths, but it is the <i>health professional who should identify</i> patients’ strengths (such as overcoming depression or emotional easting) throughout the patients’ story. This requires professional training. We learned that the steps to guide patients to plan action needed to be simple and straightforward to avoid overwhelming them. If the tool to plan action was overwhelming, it affected the patients’ capacity and confidence to plan and implement future actions. Overall the tool promoted conversation, but it needed clear instructions. <h3>Conclusions</h3> This study shows the value of human-centred design to achieve collaboration and partnership between patients, health professionals and researchers. Co-creating not only helps investigate how to achieve a deeper understanding of one another’s needs, values and perspectives, but also to get ideas none of these 3 stakeholders: researchers, patients and health professionals would ever conceive alone. This collective aspect of design, is starting to be seeing as an asset. The adoption of human-centred design can help patients and physicians to collaboratively design better healthcare approaches, re-configure the patient-physician relationship, and help provide more suitable weight management conversations.
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Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 découle