Modelling adherence behaviour for the treatment of obstructive sleep apnoea
| Autor: | Paul M. Griffin, Yuncheol Kang, Amy M. Sawyer, Vittaldas V. Prabhu |
|---|---|
| Rok vydání: | 2016 |
| Předmět: |
medicine.medical_specialty
Information Systems and Management General Computer Science medicine.medical_treatment Psychological intervention Management Science and Operations Research Markov model Article Industrial and Manufacturing Engineering 03 medical and health sciences 0302 clinical medicine Medicine Continuous positive airway pressure Intensive care medicine Chronic care Adherence behaviour business.industry Guideline nervous system diseases respiratory tract diseases 030228 respiratory system Modeling and Simulation Sleep (system call) Markov decision process business 030217 neurology & neurosurgery |
| Zdroj: | European Journal of Operational Research. 249:1005-1013 |
| ISSN: | 0377-2217 |
| DOI: | 10.1016/j.ejor.2015.07.038 |
| Popis: | Continuous positive airway pressure therapy (CPAP) is known to be the most efficacious treatment for obstructive sleep apnoea (OSA). Unfortunately, poor adherence behaviour in using CPAP reduces its effectiveness and thereby also limits beneficial outcomes. In this paper, we model the dynamics and patterns of patient adherence behaviour as a basis for designing effective and economical interventions. Specifically, we define patient CPAP usage behaviour as a state and develop Markov models for diverse patient cohorts in order to examine the stochastic dynamics of CPAP usage behaviours. We also examine the impact of behavioural intervention scenarios using a Markov decision process (MDP), and suggest a guideline for designing interventions to improve CPAP adherence behaviour. Behavioural intervention policy that addresses economic aspects of treatment is imperative for translation to clinical practice, particularly in resource-constrained environments that are clinically engaged in the chronic care of OSA. |
| Databáze: | OpenAIRE |
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