Challenges and Opportunities for At-Home COPD Management

Sridhar Nemala, co-founder and the Head of AI at Curie AI

There are an estimated 16 million Americans who suffer from Chronic Obstructive Pulmonary Disease (COPD). Patients with COPD are frequently prescribed respiratory medication and given at-home treatment strategies designed to improve general wellness and improve airflow. These strategies may include smoking cessation, air quality control, exercise, and stress management. Unfortunately, despite the use of medication and widespread adoption of lifestyle strategies, COPD continues to represent a serious health burden, with symptomatic exacerbations causing substantial hospital readmission with costs ranging from $7,000 to $39,200 per patient.1 Given the challenge and costs presented by this disease, it is important to understand both the limitations and opportunities inherent to the modern management of COPD, as well as consider new ways to reduce care burdens and streamline the path to effective treatment – including the implementation of novel, truly passive remote monitoring systems.  

Barriers to effective care

A primary obstacle for COPD patient is frequency and impact of care. Specialist visits often occur months or years apart. Between visits, a patient’s condition can deteriorate dramatically: often, the treating pulmonologist only becomes aware of the crisis when it reaches advanced stages. This is a particularly acute problem in rural areas, where the number and distribution of pulmonologists leads to underserved and geographically distant patient populations.2  

When patients do manage to visit their pulmonologist, lack of treatment compliance and self-reported case reporting makes it hard to effectively calibrate treatment. Many COPD patients have multiple comorbidities and use polypharmacy to manage conditions, a trait increasingly linked to low adherence worldwide.3 Combined with mechanical challenges (inhaler operation) and a large patient population over 65, it is likely that many COPD patients forget to take their medical at the correct time, impacting efficacy of treatment. 

Considering the impact of intentional or unintentional reporting and noncompliance, pulmonary specialists typically look for objective data before making treatment recommendations. This data is usually provided through traditional monitoring technologies, such as pulse-oximeters, which measure blood oxygen saturation. Many of these technologies, however, fail to provide the full range of biometrics needed to accurately assess a patient’s deteriorating state, forcing a physician to rely on patient reports and increasing time to intervention.

Remote monitoring: role and limitations

Recently, the development of remote monitoring technology has provided new solutions to help pulmonologists and patients bridge the “data gap” and capture more objective measurements for use in clinical management. Wearable monitors, such as Spry Health’s Loop System wristband monitor, provide real-time data about vital signs such as oxygen saturation, heart rate, and respiratory rate. The Spry device alerts the wearer and their physician to any major change in physiological data. 

This represents a marked improvement over previous monitoring methods. However, most traditional remote monitoring solutions still rely on multi-device setups that make patient adherence difficult. In theory, “truly passive” monitoring solutions – those that do not require learning, skill, or the incorporation of new routines into the patient’s life – make adherence easier. Rather than provide the treating physician a “snapshot” of a patient’s condition days, weeks, or months ago, data provided should be current and relevant. These solutions can short time to treatment when implemented correctly. Accordingly, this represents an emerging area of interest for medical innovators and manufacturers. 

Passive monitoring through artificial intelligence

Access to truly passive, real-time monitoring is an emerging factor for overcoming the previously mentioned care barriers. There are multiple challenges, however, associated with making this goal a reality. First, the remote monitoring technology needs to be completely passive: in other words, requiring minimal patient interaction beyond turning the device off and on. Second, given the highly dynamic nature of patient biomarkers and large amount of data generated, the system requires a means to effectively codify, prioritize, and communicate the data to care teams. The recent integration of Artificial Intelligence (AI) and medical monitoring technology, however, holds promise for making truly passive monitoring a reality. Today, AI-based solutions are being leveraged to shrink or close care gaps across a wide variety of medical disciplines, including pulmonology. 

Conclusion

Despite the robust array of pharmaceutical treatments and lifestyle management solutions available for COPD patients today, care barriers continue to impose human and financial burdens. Physician distribution, physical distance, and lack of patient adherence continue to affect treatment results and consistency. To overcome these barriers, new solutions that bridge the distance between patient and provider – as well as minimize patient non-compliance – should be considered. The integration of AI, remote monitoring, and telehealth systems provide an intriguing potential route of exploration, offering an encouraging case study for the management of COPD. 


About Sridhar Nemal
Sridhar Nemala, co-founder and the Head of AI at Curie AI, is a leading expert in artificial intelligence and its application in speech processing systems. Sridhar earned his doctorate at Johns Hopkins University, where he combined neuroscience principles with machine learning to improve real-world performance of automatic speech processing systems. He later served as Director of Voice AI at Knowles Intelligent Audio, inventing audio processing techniques that are now widely in use in hundreds of millions of smartphones and speakers. At Curie AI, his work focuses on developing technologies for monitoring respiratory health, creating actionable insights for clinical teams, and improving outcomes for patients.