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Abstract
Objective We sought to develop a simulation modelling method to help better understand the complex interplay of factors that lead to people with type 2 diabetes and asthma not taking all of their medication as prescribed when faced with multiple medications (polypharmacy).
Research design and methods In collaboration with polypharmacy patients, general practitioners, pharmacists and polypharmacy researchers, we developed a map of factors that directly and indirectly affect somebody’s decision to take their medication as prescribed when faced with multiple type 2 diabetes and asthma medications. We then translated these behavioural influences into logical rules using data from the literature and developed a proof-of-concept agent-based simulation model that captures the medicine-taking behaviours of those with type 2 diabetes and asthma taking multiple medications and which predicts both the clinical effectiveness and rates of adherence for different combinations of medications.
Conclusions The model we have developed could be used as a prescription support tool or a way of estimating medicine-taking behaviour in cost-effectiveness analyses.
- Agent Based Simulation
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Footnotes
Contributors DC led the project, designed and developed the simulation model and led the authorship of the paper. SM assisted with the design of the model and the translation of the research evidence into rules for the model and contributed edits and feedback for the paper. NB initially proposed the study, offered insight into polypharmacy behaviour and practice to inform the model and contributed edits and feedback for the paper. BK, RM and JV offered insight into polypharmacy behaviour and practice to inform the model and contributed edits and feedback for the paper.
Funding This work was supported by the National Institute for Health Research via the national CLAHRC (Collaboration for Leadership in Applied Health Research and Care) programme.
Competing interests None declared.
Provenance and peer review Not commissioned; externally peer reviewed.
Data sharing statement All data from the study is included in the paper. Therefore, no additional data is available.
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