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Non-adherence to medication is a ‘worldwide problem of striking magnitude’.1 It has consequences for the health of patients and is a great concern for healthcare providers in terms of patient outcomes and healthcare costs. Theoretical research has mainly focused on intentional non-adherence: for example, when people choose not to take their medication. However, unintentional non-adherence also accounts for a significant proportion of the problem: when people mean to take their medication in the right way but do not. This area is under-researched. In this paper, we bring a new perspective to this problem by exploring what contribution ‘resilience’ could make to it. Resilience engineering focuses on a system's ability to maintain performance, avoid error, compensate for poor circumstances and cope with disturbances. So, rather than focus on how things go wrong, we propose to exploit and enhance how things go right.
The National Health Service in England processed 962 million prescriptions in 2011, which had an ingredient cost of £8.8 billion,2 and it is estimated that 30%–50% of prescribed medication are not taken correctly.3 A report prepared for a summit of European health ministers in 2012 estimated that non-adherence contributes approximately 57% of $500 billion total avoidable costs attributed to suboptimal medicine use globally each year.4 Horne et al3 provide a broad and comprehensive review of the research in this area. Their report shows that the problem is complex and multifaceted, and they call for more research to tackle this important issue. They argue that improving the effectiveness of adherence interventions could have a greater impact on public health than improvements in specific medical treatments.3
Haynes et al5 note that current successful interventions for non-adherence are multifaceted, complex, labour intensive and at best have modest effects; they call for innovative approaches to assist …
Contributors NB had the initial idea for the paper. This idea has been explored, developed and written by DF in collaboration with NB. AB, LE and IL have contributed their knowledge and expertise to sharpen and validate ideas in the paper. Further, we have used examples in the paper that originate from a previous study by LE.
Funding This work was supported by the UK Engineering and Physical Sciences Research Council (EP/G059063/1).
Competing interests None.
Provenance and peer review Not commissioned; externally peer reviewed.