Modelling collaboration of primary and secondary care for children with complex care needs: long-term ventilation as an example

• DOI: 10.1007/s00431-019-03367-y
• Publication Date: 2019-04-02T00:02:22Z
• Authors: Daniela Luzi; Fabrizio Pecoraro; Oscar Tamburis; Miriam O’Shea; Philip Larkin; Jay Berry; Maria Brenner
• Keywords: LTV; Child; Child Health Services/organization & administration; Chronic Disease/therapy; Cooperative Behavior; Delivery of Health Care/organization & administration; Europe; Home Care Services/organization & administration; Humans; Respiration, Artificial/methods; Respiration, Artificial/statistics & numerical data; Transitional Care/organization & administration; LTV; Multidisciplinary team; Process modelling; Professional collaboration; UML; Child Health Services; Multidisciplinary team; Transitional Care; Home Care Services; Respiration, Artificial; UML; Europe; 03 medical and health sciences; 0302 clinical medicine; Chronic Disease; Process modelling; Humans; Original Article; Professional collaboration; Cooperative Behavior; Child; Delivery of Health Care

Children dependent on long-term ventilation need the planning, provision and monitoring of complex services generally provided at home by professionals belonging to different care settings. The collaboration among improves efficiency continuity especially when treating children with needs. In this paper, Unified Modelling Language (UML) has been adopted detect variety patterns as well represent compare processes across 30 EU/EEA countries MOCHA project.Conclusion: Half analysed have a multidisciplinary team degrees composition, influencing organisational features such development personalised plan preventive curative services. This approach provides indications in performing organising delivery terms family involvement, interactions availability ICT. What is known: • CCNs require coordination efforts before after discharge continuum level integrated solutions country level. new: •The adoption business process method contributes perform cross-country analysis highlighting variability composition its influence care.