Mapping outcomes in quality improvement and system design activities: the outcome identification loop and system impact model

Abstract

BackgroundWhether 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 approachCentral 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 toolsThe 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 conclusionsThe 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.

Multiple outcome interactions in healthcare systems: a participatory outcome mapping approach

“…These findings support the suggestion that outcomes need to be understood as interrelated elements to inform better and adapt systems (Flemming et al 2019;Holden et al 2013;Petticrew et al 2019). Furthermore, these findings align with additional implications about how a multi-outcome approach may reconcile knowledge about how interventions influence outcomes (Akinluyi, Ison, and Clarkson 2019) and how outcomes could play a role with other systems elements. Nevertheless, integrating multiple outcomes increases the risk of attributing false effectiveness to an intervention (Heneghan, Goldacre, and Mahtani 2017).…”

“…Still, it remains unclear how Outcome Evidencing can be implemented to inform the development of new complex interventions. This proactive application of outcomes is rarely used, but it could provide meaningful insights for system design (Akinluyi, Ison, and Clarkson 2019).…”

“…This study illustrated how different stakeholders prioritise outcomes differently, as demonstrated widely in literature (Baldeh et al 2020;Guyatt et al 2011;Woolf et al 2012). This study aims to offer a new practical approach to understand, communicate, and integrate outcomesa need that other studies (Akinluyi, Ison, and Clarkson 2019;Holden et al 2013) have called for. This approach is supported by literature about the limitation of forecasting outcomes and recognises that outcomes in complex systems are unpredictable and unstable (Braithwaite et al 2018).…”

“…However, there is still a need to provide a more straightforward understanding of outcome interactions and how other healthcare systems elements vary in different contexts (Holden et al 2013;Paz-Ybarnegaray and Douthwaite 2017;Petticrew et al 2019). Furthermore, limited practical approaches exist for gathering, discussing, understanding, and communicating outcomes as interrelated systems (Akinluyi, Ison, and Clarkson 2019;Holden et al 2013).…”

Healthcare Systems Design: A Sandbox of Current Research Themes Presented at an International Meeting

“…The importance of technology was, for example, embodied by one of the ignite talks introducing the role of a Clinical Engineer within the NHS, a professional group embedded within hospitals with a broad remit. The main objective of this position is to maximise value delivered by medical technology (Akinluyi et al, 2019). This links to the relevance of data science and the awareness of our community of the importance of harnessing data both in the context of research endeavours but also to support the design of products, interventions, and organisations for better health and care.…”