A summary of research published in ERJ Open Research
Many people with Obstructive Sleep Apnoea (OSA) are treated with CPAP (continuous positive airway pressure), a treatment that uses gentle air pressure during sleep to keep the airway open. For most, this improves symptoms such as snoring and daytime sleepiness.
However, some people continue to feel very sleepy during the day, even when they are using CPAP correctly. This is called residual excessive daytime sleepiness (rEDS). Persistent sleepiness can affect daily life, increase the risk of accidents and may sometimes be linked to other health or lifestyle factors, such as medicines, pain or other sleep problems.
Sleep clinics are advised to check whether people with OSA still have daytime sleepiness after starting treatment. However, busy clinics can find it difficult to review every patient in a consistent way. Researchers in the UK tested whether a digital system could help improve this process.
Researchers developed a digital pathway that helps healthcare staff follow clear steps when reviewing patients. This is a type of computer programme known as a clinical decision support system (CDSS).
The pathway was used to review people with OSA who had been using CPAP treatment for at least six months.
The digital pathway worked in several steps:
Between May and September 2024, 472 patients were reviewed using this pathway. 46 patients were found to have rEDS.
People with rEDS were more likely to report other health or lifestyle challenges, including:
Following a team discussion and a consultant review, the researchers found:
Importantly, before this pathway was used, none of these patients had been reviewed for, or found to have, rEDS.
This study shows that structured digital pathways can help sleep services find and support patients who continue to feel sleepy despite treatment.
The pathway helps healthcare teams:
For patients, this approach may help improve safety, day-to-day living and quality of life by making sure ongoing sleepiness is properly investigated.
Future developments could include more advanced digital tools, including artificial intelligence (AI), to help predict which patients may benefit from specific treatments.