Using protocols in ICU practice. Engaging the staff.

Aims/Purpose: Protocols are evidenced-based structured guides for directing care to achieve improvements. But translating that evidence into practice is a major challenge. It is not acceptable to simply introduce the protocol and expect it to be adopted and lead to change in practice. Implementation requires effective leadership and management. This presentation describes a strategy for implementation that should promote successful adoption and lead to practice change.
Presentation description: There are many social and behavioural change models to assist and guide practice change. Choosing a model to guide implementation is important for providing a framework for action. The change process requires careful thought, from the protocol itself to the policies and politics within the ICU. In this presentation, I discuss a useful pragmatic guide called the 6SQUID (6 Steps in QUality Intervention Development). This was initially designed for public health interventions, but the model has wider applicability and has similarities with other change process models. Steps requiring consideration include examining the purpose and the need for change; the staff that will be affected and the impact on their workload; and the evidence base supporting the protocol. Subsequent steps in the process that the ICU manager should consider are the change mechanism (widespread multi-disciplinary consultation; adapting the protocol to the local ICU); and identifying how to deliver the change mechanism (educational workshops and preparing staff for the changes are imperative). Recognising the barriers to implementation and change and addressing these locally is also important. Once the protocol has been implemented, there is generally a learning curve before it becomes embedded in practice. Audit and feedback on adherence are useful strategies to monitor and sustain the changes.
Conclusion: Managing change successfully will promote a positive experience for staff. In turn, this will encourage a culture of enthusiasm for translating evidence into practice.

Advanced Business Simulations-Incorporating business and process execution data

Key Performance Indicators (KPIs) and their predictions are widely used by the enterprises for informed decision making. Nevertheless , a very important factor, which is generally overlooked, is that the top level strategic KPIs are actually driven by the operational level business processes. These two domains are, however, mostly segregated and analysed in silos with different Business Intelligence solutions. In this paper, we are proposing an approach for advanced Business Simulations, which converges the two domains by utilising process execution & business data, and concepts from Business Dynamics (BD) and Business Ontologies, to promote better system understanding and detailed KPI predictions. Our approach incorporates the automated creation of Causal Loop Diagrams, thus empowering the analyst to critically examine the complex dependencies hidden in the massive amounts of available enterprise data. We have further evaluated our proposed approach in the context of a retail use-case that involved verification of the automatically generated causal models by a domain expert.

Process Selection Using Variation and Cost Relations

Variations are inherent in all manufacturing processes and can significantly affect the quality of a final assembly, particularly in multistage assembly systems. Existing research in variation management has primarily focused on incorporating GD&T factors into variation propagation models in order to predict product quality and allocate tolerances. However, process induced variation, which has a key influence on process planning, has not been fully studied. Furthermore, the link between variation and cost has not been well established, in particular the effect that assembly process selection has on the final quality and cost of a product. To overcome these barriers, this paper proposes a novel method utilizing process capabilities to establish the relationship between variation and cost. The methodology is discussed using a real industrial case study. The benefits include determining the optimum configuration of an assembly system and facilitating rapid introduction of novel assembly techniques to achieve a competitive edge.