Chalk Daniel, Manzi Sean, Britten Nicky, Kluettgens Bettina, Magura Ratidzai, Valderas Jose
NIHR CLAHRC for the South West Peninsula, St Luke’s Campus, University of Exeter Medical School, Exeter, UK.
Senior Team, South West Academic Health Science Network, Exeter, UK.
BMJ Simul Technol Enhanc Learn. 2017 Jul 6;3(3):94-98. doi: 10.1136/bmjstel-2016-000162. eCollection 2017.
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).
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.
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.
我们试图开发一种模拟建模方法，以帮助更好地理解导致2型糖尿病和哮喘患者在面对多种药物（多重用药）时未按规定服用所有药物的各种因素之间的复杂相互作用。
我们与多重用药患者、全科医生、药剂师和多重用药研究人员合作，绘制了一张因素图，这些因素直接或间接地影响某人在面对多种2型糖尿病和哮喘药物时按规定服药的决定。然后，我们利用文献数据将这些行为影响转化为逻辑规则，并开发了一个基于智能体的概念验证模拟模型，该模型捕捉了服用多种药物的2型糖尿病和哮喘患者的服药行为，并预测了不同药物组合的临床疗效和依从率。
我们开发的模型可作为一种处方支持工具，或在成本效益分析中估计服药行为的一种方法。
