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Dec 07, 2020

The key to maximizing CPAP adherence: data and predictive analytics

Estimated reading time: 7-9 minutes

Continuous Positive Airway Pressure (CPAP) is the most widely prescribed treatment for Obstructive Sleep Apnea (OSA), though patient adherence to this therapy has long been a challenge for Durable Medical Equipment providers (DMEs). Between 40-60% of patients prescribed CPAP either abandon treatment or do not use it enough to see a benefit to their health. [1] And while untreated OSA has been associated with significant cardiovascular, metabolic, and psychosocial morbidity, non-adherence remains an issue.

 

OSA patient care requires exhaustive coordination and follow-up to meet compliance standards, with DMEs investing a significant amount of time and effort to support patient adherence. In the United States, reimbursement is particularly challenging for DMEs due to Centers for Medicare & Medicaid Services (CMS) policies that require objective proof of adequate adherence, 90-day compliance standards, and the effective management of a large patient population to ensure reimbursement. It has become increasingly important for DMEs and clinicians to take advantage of holistic service offerings that can help to support patient adherence from diagnosis through setup and ongoing treatment to not only help improve patient outcomes, but allow for reimbursement as well. In an evolving healthcare landscape that leans heavily on remote patient management, the use of data and predictive analytics could help DMEs to address these compliance challenges in both a proactive and distanced way. 

 

Tools such as Philips Adherence Profiler – a predictive trending algorithm for Positive Airway Pressure therapy adherence found within Philips cloud based patient management software – can automate the process to identify patients who are at risk of non-adherence to help DMEs and Health Care Providers (HCPs) intervene when necessary in order to keep their patients more compliant. In fact, patients using Philips sleep therapy solutions have logged more than 4 billion compliant (>4h CPAP use) nights. [2]

 

A retrospective study involving 457 patients conducted in France using the Philips Adherence Profiler algorithm concluded that automatic telemonitoring algorithms are relevant tools for early prediction of CPAP therapy adherence and may make it possible to focus therapeutic follow-up efforts on patients who are at risk of non-adherence. By triaging patient care based upon the likelihood of the patient becoming a regular user of CPAP therapy, the study points to a new way DMEs can efficiently maximize adherence across the patient population.

 

Dr. Teofilo Lee-Chiong, MD, Chief Medical Liaison at Philips Sleep and Respiratory Care and Dr. Mark Aloia, PhD, Global Lead for Behavior Change at Philips, discuss the clinical and behavioral issues of CPAP compliance, what needs to change between patient and provider, and how technology and data may be effective in determining adherence and recommending intervention. 

While CPAP is the most commonly prescribed treatment for OSA, why do we continue to see issues with adherence? 

 

Dr. Teofilo Lee-Chiong: "It is estimated that 425 million adults globally have moderate-to-severe obstructive sleep apnea today. Not one of them is exactly alike, yet many are managed as if they are. A one-size-fits-all approach to treating sleep apnea, which disregards each individual’s unique medical condition and life preferences, degrades the experience of care, and contributes to non-adherence to therapy."  

 

Dr. Mark Aloia: "Adherence with CPAP is hard because all adherence is hard. People even have difficulty sticking to their medication regimen, where adherence to taking a prescribed pill is mediocre at best in the scientific literature, and getting worse. We must think of adherence to treatment as a change to one’s health behavior. Perhaps the greatest predictor is a person’s confidence. Confidence involves both the confidence in the treatment conferring benefit to the patient as well as confidence that they can meet the expectations put on them. With sleep, confidence becomes increasingly important as we often ask patients to use CPAP all night, every night. That’s a very high bar to meet when you don’t feel particularly confident."

 

What changes need to be made, from both the DME and healthcare provider side, and the patient side to ensure CPAP adherence is carried through beyond the 90-day period?  

 

Teofilo: "Not ensuring adherence to PAP therapy beyond the currently mandated 90-day period is not due to a lack of science or limitation of technology – there are still challenges that need to be addressed. Currently, we have the tools to monitor PAP use continuously and reliably, but these are underutilized past the first 3 months of initiating PAP treatment for sleep apnea. Since the benefits of PAP therapy are rapidly lost following interruption of its use, the medical community, including patients, health providers, insurance companies and government authorities, should work together to incentivize and support ongoing review of PAP use."        

 

Mark: "We have to spend a bit more time with patients, listening and truly hearing what is important to them. We should listen to their concerns about the therapy and express empathy. But we should also try to elicit the factors that motivate them to engage in their therapy. We must understand that disengagement with treatment occurs when confidence is low and ambivalence is high. As far as 90 days is concerned, I think there are many examples of the value created in allowing successful users to use their experiences to help others. Altruism can be a powerful motivator to maintain change." 

 

What role can data and analytics (i.e. using Adherence Profiler) play in improving CPAP adherence? 

 

Mark: "Data tells us quite a lot and serves as another way for us to “listen”. We listen to trends in the data and flag the early moments when disengagement is likely, but not yet a foregone conclusion. This is critical because early intervention is always best. Analytics are only as good as the interventions to which they lead us, but they can absolutely help improve outcomes as they tell us when to pay special attention."

 

Teofilo: "Data and analytics enable everyone in the healthcare team to better understand how a specific patient uses, and how they feel when using, sleep apnea technologies. Instead of a wait-and-see, or worse, a trial-and-error strategy for addressing difficulties and complications related to PAP use, the Adherence Profiler is designed to use robust methodology to enhance the efficiency and consistency of care, and help empower patients and their health providers to make informed decisions." 

 

What can we learn from this specific use case of data/analytics to improve CPAP adherence that may allow us to enable improved patient therapy engagement and support throughout the entire healthcare industry? 

 

Mark: "Again, it all comes down to recognizing a downward turn in health behaviors and knowing how to engage. Analytics alone do not solve the problem. If I saw that a patient was decreasing their engagement with therapy and I called them to chastise them and push harder, they might easily just give up, feeling like a failure. But, if I recognize this trend early and call with a tone that is supportive, normalizing their struggle and reminding them why they started this in the first place – in their own words, I may be able to save them." 

 

Teofilo: "Collaborative management is key to long-term success of any sleep apnea therapy. Dialogue between patients and healthcare providers often starts at the medical office but should not be allowed to end there. Rather than being episodic and fragmented, care must be continuous and integrated over the long-term."

 

[1] Sabil, A., Le Vaillant, M., Stitt, C. et al. A CPAP data–based algorithm for automatic early prediction of therapy adherence. Sleep Breath (2020). https://doi.org/10.1007/s11325-020-02186-y 

[2] Based on snapshot data from Philips Encore Anywhere database. Total nights of sleep therapy data stored within Encore Anywhere for US companies 4,042,476,461 as of 10/1/2020.  (1 patient for 1 night where usage was greater than 4 hours from the period of 1/1/2007 through 10/1/2020= 1 night of data)

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Meredith Amoroso

Meredith Amoroso

Philips Global Press Office

Tel: +1 724-584-8991