Can agent-based simulation be used as a tool to support polypharmacy prescribing practice?

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. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.