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Case management for high-intensity service users: towards a relational approach to care co-ordination


Phil McEvoy
The Angel Healthy Living
1 St Philip's Place
M3 6FA, UK


This study is based on a formative evaluation of a case management service for high-intensity service users in Northern England. The evaluation had three main purposes: (i) to assess the quality of the organisational infrastructure; (ii) to obtain a better understanding of the key influences that played a role in shaping the development of the service; and (iii) to identify potential changes in practice that may help to improve the quality of service provision. The evaluation was informed by Gittell’s relational co-ordination theory, which focuses upon cross-boundary working practices that facilitate task integration. The Assessment of Chronic Illness Care Survey was used to assess the organisational infrastructure and qualitative interviews with front line staff were conducted to explore the key influences that shaped the development of the service. A high level of strategic commitment and political support for integrated working was identified. However, the quality of care co-ordination was variable. The most prominent operational factor that appeared to influence the scope and quality of care co-ordination was the pattern of interaction between the case managers and their co-workers. The co-ordination of patient care was much more effective in integrated co-ordination networks. Key features included clearly defined, task focussed, relational workspaces with interactive forums where case managers could engage with co-workers in discussions about the management of interdependent care activities. In dispersed co-ordination networks with fewer relational workspaces, the case managers struggled to work as effectively. The evaluation concluded that the creation of flexible and efficient task focused relational workspaces that are systemically managed and adequately resourced could help to improve the quality of care co-ordination, particularly in dispersed networks.