Estimating the costs and analysing the precision of several diagnostic and treatment approaches for obstructive sleep apnea patients in the Netherlands, using timed automata modelling

Obstructive Sleep Apnea (OSA) is a (highly) prevalent medical condition, linked to severe negative health consequences. In the Netherlands, diagnosis of OSA presently has long waiting times and both diagnosis and treatment have high costs. This article introduces a so-called timed automata model (UPPAAL tool) for analysing diagnostic and treatment approaches for OSA. This model is used for assessing the Dutch current traditional approach, as well as multiple alternative approaches for OSA diagnosis and treatment. The analysis shows that one alternative approach can lower the costs and waiting lists, while maintaining diagnostic precision. In this manuscript the best alternative approach is a combination of Oxygen Desaturation Index (ODI) measurement obtained by nocturnal pulse oximetry and a questionnaire to diagnose the patient. Of course, it is important that, although timed automata modelling is a reliable tool, these outcomes are meant to start a discussion regarding the above-mentioned problems and are not proven outcomes yet. The healthcare system in the Netherlands is in danger of becoming unaffordable. Therefore, this initial exploration has been carried out to see whether alternatives to the current OSA-care can be devised.

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Publication Details

Journal
Computers in Biology and Medicine
Published
2025-03-02
DOI
https://doi.org/10.1016/j.compbiomed.2025.109910
Primary Topic
Obstructive Sleep Apnea Research
Type
article
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article

Estimating the costs and analysing the precision of several diagnostic and treatment approaches for obstructive sleep apnea patients in the Netherlands, using timed automata modelling

Miranda J.M. Wetselaar‐Glas, Piet-Heijn van Mechelen, Rom Langerak, Peter Wetselaar et al.
Computers in Biology and Medicine
Obstructive Sleep Apnea Research
article

Estimating the costs and analysing the precision of several diagnostic and treatment approaches for obstructive sleep apnea patients in the Netherlands, using timed automata modelling

Miranda J.M. Wetselaar‐Glas, Piet-Heijn van Mechelen, Rom Langerak, Peter Wetselaar, Nander E.F. Voortman
article en

Abstract

Obstructive Sleep Apnea (OSA) is a (highly) prevalent medical condition, linked to severe negative health consequences. In the Netherlands, diagnosis of OSA presently has long waiting times and both diagnosis and treatment have high costs. This article introduces a so-called timed automata model (UPPAAL tool) for analysing diagnostic and treatment approaches for OSA. This model is used for assessing the Dutch current traditional approach, as well as multiple alternative approaches for OSA diagnosis and treatment. The analysis shows that one alternative approach can lower the costs and waiting lists, while maintaining diagnostic precision. In this manuscript the best alternative approach is a combination of Oxygen Desaturation Index (ODI) measurement obtained by nocturnal pulse oximetry and a questionnaire to diagnose the patient. Of course, it is important that, although timed automata modelling is a reliable tool, these outcomes are meant to start a discussion regarding the above-mentioned problems and are not proven outcomes yet. The healthcare system in the Netherlands is in danger of becoming unaffordable. Therefore, this initial exploration has been carried out to see whether alternatives to the current OSA-care can be devised.

Computers in Biology and MedicineVol. 189
Leiden University Medical Center (NL), Academic Center for Dentistry Amsterdam (NL), The Patients Association (GB), University of Twente (NL)
Good health and well-being
Openalex Percentile: Top 95%
Obstructive Sleep Apnea Research
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Estimating the costs and analysing the precision of several diagnostic and treatment approaches for obstructive sleep apnea patients in the Netherlands, using timed automata modelling — Miranda J.M. Wetselaar‐Glas, Piet-Heijn van Mechelen, et al. · Computers in Biology and Medicine (2025) | TGRS Research Map | TGRS