The Cassandra Project- Building a Sustainable Workload Activity Model for Future Community and District Nursing Workforce Capacity Planning

Background: When portrayed in terms of supply and demand, nursing work is often represented as a linear series of tasks that are deterministic in nature. These assumptions have led to nursing work being subjected to... [ view full abstract ]

Background:
When portrayed in terms of supply and demand, nursing work is often represented as a linear series of tasks that are deterministic in nature. These assumptions have led to nursing work being subjected to conventional research methods using activity analysis that are simplistic e.g. (i) time and motion studies based on capturing a linear series of tasks, (ii) work on averages like the Safer Nursing Care work (UK), or (iii) diary based making assumptions about what people are doing e.g. Case Allocate. Such tools fail to capture the multidimensional complexity of care particularly in community settings or to accurately present care left undone.

Purpose:
This paper presents work in progress findings from a mixed methods practice development study which:
(i) co-produced and pilot a web based workload activity tool, the Cassandra Matrix with community nurses and community based organisations;
(ii) undertook a utility evaluation through online survey to capture the impact the research had on individual practitioners, teams and organisations;
(iii) developed a shared purpose framework and job descriptors competence framework with community and district nurses mapping a vision for the delivery of a first class holistic service providing care close to or in the home.
Results
Results demonstrate that the tool provides is able to accurately (i) model the multidimensional complexity of care by capturing intervention, context and multiple users, (ii) provide individual and organisational reports as well as modelling negative space and identifying activities that nurses do not have time to do.
Conclusions:
The Cassandra Matrix Tool for community nurses captures what nurses do (interventions), where they happen (contexts), who the work is done for (patients or carers), and what nurses do not have time to do (work left undone). It has enabled aggregation of data to develop a deeper conceptual understanding of community nursing work. Our next phase of work focuses on developing an optimum caseload tool to build a representative “whole system” to represent a realistic picture of what work is being done and how to best develop the future workforce.