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Care complexity, perceptions of complexity and preferences for interprofessional collaboration: an analysis of relationships and social networks in paediatrics.
BMC Medical Education 2024 March 26
BACKGROUND: In the context of increasingly intricate healthcare systems, professionals are compelled to collaborate within dynamically changing interprofessional teams. Moreover, they must adapt these collaborative processes to effectively and efficiently manage the evolving complexity of care needs. It remains unclear how professionals determine care complexity and relate this complexity to their preferences for interprofessional collaboration (IPC). This study investigated the relationships between care complexity, professionals' perceived complexity and IPC preferences, and examined the variation in individual and team characteristics of IPC-practices across different levels of complexity in paediatric care.
METHODS: In an online questionnaire, 123 healthcare professionals working at an academic tertiary children's hospital scored their perceptions of complexity and preferences for IPC. They also selected family and various professions as members of the interprofessional (IP-) team based on thirteen patient cases. We employed conjoint analysis to systematically model the complexity of case descriptions across the five domains of the International Classification of Functioning, Disability and Health (ICF). Additionally, we applied social network analysis to identify important professions, crucial connectors and influential professions in the IP-team, and to describe the cohesiveness of IP-teams.
RESULTS: Modelled case complexity, professionals' perceived complexity and IPC preferences were positively associated. We found large inter-individual variations in the degree of these associations. Social network analysis revealed that the importance and influence of professions was more equally distributed when case complexity increased. Depending on the context and complexity of the case, different professions (e.g. medical doctors, social professionals, extramural professionals) were considered to be more crucial connectors within the IP-team. Furthermore, team cohesion was positively associated with modelled and perceived care complexity.
CONCLUSIONS: In conclusion, our study contributes to the existing knowledge by integrating task-specific insights and broadening the use of conjoint and social network analysis in the context of IPC. The findings substantiate the contingency theory that relates characteristics of IPC to care complexity, offering quantified insights into how IP-teams adapt to situational needs. This understanding of relationships and variations within IPC holds crucial implications for designing targeted interventions in both clinical and health profession education contexts. Consequently, it contributes to advancements in healthcare systems.
METHODS: In an online questionnaire, 123 healthcare professionals working at an academic tertiary children's hospital scored their perceptions of complexity and preferences for IPC. They also selected family and various professions as members of the interprofessional (IP-) team based on thirteen patient cases. We employed conjoint analysis to systematically model the complexity of case descriptions across the five domains of the International Classification of Functioning, Disability and Health (ICF). Additionally, we applied social network analysis to identify important professions, crucial connectors and influential professions in the IP-team, and to describe the cohesiveness of IP-teams.
RESULTS: Modelled case complexity, professionals' perceived complexity and IPC preferences were positively associated. We found large inter-individual variations in the degree of these associations. Social network analysis revealed that the importance and influence of professions was more equally distributed when case complexity increased. Depending on the context and complexity of the case, different professions (e.g. medical doctors, social professionals, extramural professionals) were considered to be more crucial connectors within the IP-team. Furthermore, team cohesion was positively associated with modelled and perceived care complexity.
CONCLUSIONS: In conclusion, our study contributes to the existing knowledge by integrating task-specific insights and broadening the use of conjoint and social network analysis in the context of IPC. The findings substantiate the contingency theory that relates characteristics of IPC to care complexity, offering quantified insights into how IP-teams adapt to situational needs. This understanding of relationships and variations within IPC holds crucial implications for designing targeted interventions in both clinical and health profession education contexts. Consequently, it contributes to advancements in healthcare systems.
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