Adaptation to extreme weather events in complex health and social care systems: The example of older people’s services in England

Sarah Curtis, Katie Oven, Jonathan Wistow, Christine Dunn and Lena Dominelli

Environment and Planning C, 2018, vol. 36, issue 1, 67-91

Abstract: Our findings contribute to a growing international literature on how conceptual models from complexity theory may be relevant to inform planning in health and social care systems, helping to adapt and improve preparedness and resilience to extreme weather events. We focus on findings from two case studies in England and their relationship to national policy for adaptation. Complexity theory helped to frame strategies for planning for events that are emergent and unpredictable. We find from our case studies that, in spite of the uncertainty involved, some ‘principles’ derived from parts of the literature on complexity theory may provide a helpful framework for the development of more robust preparedness strategies in the health and social care sector. By viewing health and social care as a ‘system of systems’, adaptation planning recognises the interrelationships of built, institutional and social infrastructures. The idea of local systems, with variable, path-dependent attributes, which are partially closed, but permeable to other parts of the wider network, leads to an actionable model of adaptation which emphasises the potential value of local self-organisation, but also underlines the importance of co-evolution across the wider system and the vital role of national initiatives and support for adaptation strategies. The value of sharing experience from local case studies across the national system, as well as among local partners, is very apparent in the experience reported here.

Keywords: Adaptation; local climate action; health and social care; governance implementation; environmental change (search for similar items in EconPapers)
Date: 2018
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Persistent link: https://EconPapers.repec.org/RePEc:sae:envirc:v:36:y:2018:i:1:p:67-91

DOI: 10.1177/2399654417695101

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