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Mapping outcomes in quality improvement and system design activities: the outcome identification loop and system
Emmanuel Adeoluwa Akinluyi1, Keith Ison1, P John Clarkson2
1Medical Physics, Guy's and St Thomas' NHS Foundation Trust, London, UK.
Background:
Whether explicit or implicit, models of value are fundamental in quality improvement (QI) initiatives. They embody the desirability of the impact of interventions-with either foresight or hindsight. Increasingly impact is articulated in terms of outcomes, which are often prescribed and sometimes inappropriate. Currently, there is little methodological guidance for deriving an appropriate set of outcomes for a given QI initiative. This paper describes a structured approach for identifying and mapping outcomes.
Overall Approach:
Central to the approach presented here is the engagement of teams in the exploration of the system that is being designed into. This methodology has emerged from the analysis and abstraction of existing methods that define systems in terms of outcomes, stakeholders and their analogues. It is based on a sequence of questions that underpin these methods.
Outcome Elicitation Tools:
The fundamental questions of outcome elicitation can be concatenated into a structured process, within the Outcome Identification Loop. This system-analysis process stimulates new insights that can be captured within a System Impact Model.The System Impact Model reconciles principles of intended cause/effect, with knowledge of unintended effects more typically emphasised by risk approaches. This system representation may be used to select sets of outcomes that signify the greatest impact on patients, staff and other stakeholders. It may also be used to identify potential QI interventions and to forecast their impact.
Discussion And Conclusions:
The Outcome Identification Loop has proven to be an effective tool for designing workshops and interviews that engage stakeholders, critically in the early stages of QI planning. By applying this process in different ways, existing knowledge is captured in System Impact Models and mobilised towards QI endeavours.
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