ArticleHealth research policy and systems2023
Systems thinking methods: a worked example of supporting emergency medical services decision-makers to prioritize and contextually analyse potential interventions and their implementation.
Article in Health research policy and systems, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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1 citing paper in PubMed, 4 citations in OpenAlex.
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8 authors at 3 institutions in 4 countries.
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Abstract
backgroundSystems thinking can be used as a participatory data collection and analysis tool to understand complex implementation contexts and their dynamics with interventions, and it can support the selection of tailored and effective implementation actions. A few previous studies have applied systems thinking methods, mainly causal loop diagrams, to prioritize interventions and to illustrate the respective implementation context. The present study aimed to explore how systems thinking methods can help decision-makers (1) understand locally specific causes and effects of a key issue and how they are interlinked, (2) identify the most relevant interventions and best fit in the system, and (3) prioritize potential interventions and contextually analyse the system and potential interventions.
methodsA case study approach was adopted in a regional emergency medical services (EMS) system in Germany. We applied systems thinking methods following three steps: (1) a causal loop diagram (CLD) with causes and effects (variables) of the key issue "rising EMS demand" was developed together with local decision-makers; (2) targeted interventions addressing the key issue were determined, and impacts and delays were used to identify best intervention variables to determine the system's best fit for implementation; (3) based on steps 1 and 2, interventions were prioritized and, based on a pathway analysis related to a sample intervention, contextually analysed.
resultsThirty-seven variables were identified in the CLD. All of them, except for the key issue, relate to one of five interlinked subsystems. Five variables were identified as best fit for implementing three potential interventions. Based on predicted implementation difficulty and effect, as well as delays and best intervention variables, interventions were prioritized. The pathway analysis on the example of implementing a standardized structured triage tool highlighted certain contextual factors (e.g. relevant stakeholders, organizations), delays and related feedback loops (e.g. staff resource finiteness) that help decision-makers to tailor the implementation.
conclusionsSystems thinking methods can be used by local decision-makers to understand their local implementation context and assess its influence and dynamic connections to the implementation of a particular intervention, allowing them to develop tailored implementation and monitoring strategies.
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