Modelling adherence behaviour for the treatment of obstructive sleep apnoea

Yuncheol Kang, Amy M. Sawyer, Paul M. Griffin, Vittaldas V. Prabhu

Research output: Contribution to journalArticlepeer-review

7 Scopus citations


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.

Original languageEnglish (US)
Pages (from-to)1005-1013
Number of pages9
JournalEuropean Journal of Operational Research
Issue number3
StatePublished - Mar 16 2016

All Science Journal Classification (ASJC) codes

  • General Computer Science
  • Modeling and Simulation
  • Management Science and Operations Research
  • Information Systems and Management


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