Remote Lung Sound Monitoring Feasibility After COPD Exacerbation

Remote lung sound monitoring has emerged as a potential game-changer for managing Chronic Obstructive Pulmonary Disease (COPD), especially after exacerbations. As healthcare systems strive to improve patient outcomes and streamline care, this innovative approach can offer real-time insights into lung health, promising a shift toward more proactive management of this chronic condition.

Why It Matters

Chronic Obstructive Pulmonary Disease (COPD) affects millions worldwide, leading to significant morbidity and mortality.According to the World Health Organization (WHO), COPD is the fourth leading cause of death worldwide, and nearly 90% of COPD deaths in those under 70 years of age occur in low- and middle-income countries (LMIC). When measured by disability-adjusted life years, COPD ranks as the eighth leading cause of poor health worldwide.

Symptoms of COPD include cough, sometimes with phlegm, difficulty breathing, wheezing, and tiredness. COPD is not curable, but symptoms can improve with treatment. However, symptoms of COPD can worsen quickly and develop into flare-ups, also known as exacerbations. Exacerbations typically last for a few days and may require hospitalization and additional medication. In addition to COPD management, patients have a higher risk for other health problems, like

• lung infections, like the flu or pneumonia
• lung cancer
• heart problems
• weak muscles and brittle bones
• depression and anxiety

One crucial aspect of managing COPD is preventing and responding effectively to exacerbations. Traditional methods of monitoring often involve in-person assessments, which can lead to delays in treatment and poorer patient outcomes. Remote lung sound monitoring could provide an immediate way to detect changes in lung function, thereby facilitating prompt intervention.

New Remote Technology

Researchers are beginning a new study to examine whether wearable technology can be used to measure cough and lung sounds to predict exacerbations in people living with COPD. This new technology typically utilizes mobile applications and connected devices to allow patients to record and transmit lung sounds to healthcare providers. Such timely data can lead to quicker diagnostic and treatment decisions, reducing the risk of hospitalization and improving the quality of life for patients.

Enrollment for this study began in January 2026 with a target of up to 20 adults living with COPD. The study is titled “Study on Home Obstructive Respiratory Exacerbations (SHORE)” and will take place at Jefferson Einstein Philadelphia Hospital. The hospitals’ affiliated outpatient pulmonary clinics will also be a part of the study sites. This cohort, prospective study will evaluate whether continuous, passive monitoring of cough and lung sounds using a stethoscope-based wearable device can help extend respiratory assessments into the home with the goal of preventing unnecessary hospital readmissions. The study will follow participants for 90 days after hospital discharge or post-exacerbation outpatient follow-up. The primary objective is to assess the feasibility of remote lung sound monitoring, including patient adherence, compliance, and retention. The secondary objectives will explore associations between data captured by the RESP Biosensor, including cough frequency, wheeze, rhonchi, and respiratory rate, and standard measures of COPD symptom burden.

From a systemic perspective, introducing this monitoring could alleviate some pressure on healthcare facilities, allowing clinicians to manage their caseloads more efficiently while maintaining high standards of care. Furthermore, early detection of exacerbations may lead to a decrease in overall healthcare costs by avoiding emergency room visits and hospital stays.

How does this technology work?

Strados Labs developed the Strados™ Respiratory Care Platform, including the RESP™ Biosensor System, which encompasses a clinically validated wearable, non-invasive, Bluetooth-enabled device capable of remotely collecting respiratory data. Developers designed RESP to extend both the geographical and temporal range of lung sound recordings, which can improve the remote monitoring of high-risk COPD patients.

The RESP Biosensor continuously captures lung sounds and chest wall motions that are wirelessly transmitted through a mobile app to a web application to be analyzed for changes in respiratory health. Throughout the SHORE study, the RESP Biosensor will be used to measure cough and lung sounds during sleep as well as during structured breathing and exertional activities. Data collected from participants will be transferred via a companion mobile phone app to a secure cloud platform for analysis alongside standard measures, including pulmonary function tests and questionnaire results.

Who it affects

The implications of remote lung sound monitoring extend across various groups. Primary care providers and pulmonologists stand to benefit from enhanced diagnostic capabilities, leading to better-informed treatment plans. Patients, particularly those with a history of frequent exacerbations, can gain greater autonomy in managing their condition and may feel more engaged in their care process.

More Data = Better Patient Care?

Healthcare systems could see improved resource allocation, as remote monitoring systems allow for more proactive management of COPD without overwhelming in-person clinic visits. Remote monitoring systems enable the collection of patient health care data using peripheral measurement devices or specific questionnaires about their condition without necessitating an in-person visit to obtain these measurements. This form of monitoring, typically used in the comfort of the patient’s home environment, involves the real-time transfer of data to a dedicated platform where healthcare professionals can receive and access it. The enhanced collection of real-world data (RWD) driven by remote monitoring systems may lead to solutions that have the potential to reduce healthcare costs and increase patient quality of life.

How Do Payers Benefit?

Payers may also find this approach appealing due to potential cost savings linked to reduced hospital admissions. For example, a cardiology practice that was a part of a larger healthcare system implemented a program to evaluate the program costs and financial sustainability of remote patient monitoring for hypertension. The study’s return on investment (ROI) was calculated as the ratio of net return to program costs. Following the analysis, the results showed an average ROI of 22.2% at 55% patient compliance with the program. This ROI ranged from −11.1% to 93.3% per patient. The calculated ROI was most sensitive to changes in data review costs, insurance reimbursement, patient compliance, and device setup. Researchers concluded that the remote monitoring program demonstrated positive ROI, indicating financial sustainability in a large urban healthcare system with improvement in patient compliance with the program and a reduction in human resource costs.

Stakeholders, including policymakers and health advocates, should consider how to incentivize and support such technological advancements in care delivery.

What changes

• Healthcare providers may adopt remote monitoring tools as standard practice following COPD exacerbations, shifting focus from reactive to proactive care. Common practices could include regular follow-ups based on remote data analytics.
• Patients are likely to experience increased empowerment regarding their health management, leading to improved adherence to treatment protocols and lifestyle modifications that can contribute to better patient outcomes.
• Investment in education and training for both healthcare workers and patients will be necessary to maximize the benefits of these technologies and ensure their effective integration into existing healthcare frameworks.

References

1. https://www.who.int/news-room/fact-sheets/detail/chronic-obstructive-pulmonary-disease-(copd)
2. https://clinicaltrials.gov/study/NCT06544928
3. https://pmc.ncbi.nlm.nih.gov/articles/PMC10470466/
4. https://pmc.ncbi.nlm.nih.gov/articles/PMC11838636/