Predictive analytics maximize CPAP adherence, study finds
By HME News Staff
Updated 1:53 PM CST, Thu December 17, 2020
AMSTERDAM, the Netherlands – Automatic telemonitoring algorithms like the Philips Adherence Profiler are relevant tools for early prediction of CPAP therapy adherence, according to a recently published study in the journal Sleep and Breathing. They also may make it possible to focus therapeutic follow-up efforts on patients who are at risk of non-adherence, the study says. The study, which involved 457 patients in France, tested the predictive value at day 14 of the Philips Adherence Profiler algorithm for adherence at three months. The algorithm uses CPAP machine data hosted in the Philips EncoreAnywhere database. In a multivariate analysis, researchers found only older age and the Adherence Profiler prediction at day 14 were significant predictors of adherence. Researchers noted that about 40% of patients treated with CPAP are at risk of discontinuation or insufficient use.
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