Microsystems culture change: a refined theory for developing person-centred, safe and effective workplaces based on strategies that embed a safety culture
Notice bibliographique
Résumé
Background: Attending to culture is central to developing workplaces that are safe and effective – those that prioritise learning to support continuing quality, person-centred relationships and the wellbeing of providers and recipients of care. Culture at the microsystems level, where care is experienced and provided, directly impacts on staff and patients but is generally given much less attention than organisational cultures at the meso level. This paper presents a refinement of a previously published middle-range theory of culture change derived from a concept analysis of effective workplace culture. It draws on findings from a project that set out to embed a safety culture and grow quality improvement and leadership capability through a regional patient safety initiative in frontline teams across four acute NHS hospital trusts in south-east England. Aims and objectives: To refine theoretical understanding about how to recognise and develop effective workplace cultures at the microsystems level based on practical insights from the Safety Culture Quality Improvement Realist Evaluation (SCQIRE) project. Methods: The evaluation approach for the SCQIRE project combined realist evaluation and practice development methodology. Realist evaluation was selected to answer the question ‘what works for whom and why when embedding a safety culture, improvement capability and leadership in frontline teams?’ Key to this approach is the local development, testing and refinement of ‘CMO’ relationships between: contexts (C); mechanisms, for example triggers and explaining why components work (M); and outcomes (O). Drawing on project data, the enablers, attributes and consequences of an effective workplace culture have been used to critically examine the factors that contributed to frontline teams’ ability to create and sustain a safety culture. Findings: A total of 24 CMO relationships resulted in four emerging programme theories that described what worked, why and for whom in relation to: 1) frontline teams developing their safety culture; 2) facilitators working with frontline teams to embed safety culture, quality improvement and leadership; 3) organisations supporting frontline teams; and 4) the patient safety collaborative initiative. Conclusions: It is concluded that the close relationship between person-centred values, ways of working and continuing effectiveness mean it is not possible to develop a safety culture without also being person-centred in relationships. Other theoretical refinements proposed include greateremphasis on the role of appreciative active learning, person-centredness in everyday relationships and an integrated approach to learning, development and improvement embedded at both micro and meso levels. The theory strengthens individual enablers of safety culture, with particular attention given to quality clinical leadership based on an inclusive, participative, collaborative approach involving all stakeholders, and to facilitation that embraces all the skills required for learning, developing and improving with person-centred values. Organisational enablers emphasise the need for a corporate body of facilitators to support frontline teams, as well as the role of senior organisational leaders in enabling a bottom-up approach to supporting quality and innovation. Implications for practice: • Safety and person-centred values are interdependent with ways of working in relationships and ongoing team effectiveness. None of these can be considered without the others • Investment in quality clinical leadership is essential for the development of high-performing teams, safety culture, achievement of shared meanings and direction, and valuing of engagement of both staff and patients • Facilitators supporting frontline teams require corporate support and a wide range of skills including leadership, the ability to promote engagement in co-creating meaning, and appreciative learning that draws on the workplace as a powerful resource • Senior organisational leaders need to model organisational values in every situation but also be skilled at enabling frontline teams to become empowered through supporting a bottom-up approach to innovation and change
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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 | 0,014 | 0,014 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,003 | 0,001 |
| Études des sciences et des technologies | 0,004 | 0,025 |
| Communication savante | 0,010 | 0,010 |
| Science ouverte | 0,003 | 0,010 |
| Intégrité de la recherche | 0,003 | 0,004 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 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 ».