Precision Medicine in Adult Obstructive Sleep Apnea and Home Diagnostic Testing: Caution in Interpretation of Home Studies Without Clinician Input Is Necessary

Sleep testing during the pandemic

BACKGROUND

The COVID-19 pandemic disrupted the U.S. healthcare system, reducing the capacity available for unrelated conditions, such as sleep disordered breathing, and increasing concerns about the safety of in-lab testing. This study characterizes how the pandemic impacted the assessment of sleep disordered breathing and use of associated services.

METHODS

Sleep testing claims occurring between January 2019 and June 2021 were extracted from the database of a national healthcare organization. Utilization was trended. Logistic regressions were run to assess the association between quarter of initial testing, whether testing was followed by treatment, and whether testing was followed by a clinical visit with a diagnosis related to sleep apnea, after controlling for patient-related factors. A Cox proportional hazards model assessed factors influencing time to treatment. Finally, a logistic regression assessed factors influencing the finality of home-based testing.

RESULTS

In Q2 2021, home-based testing utilization was 134% of its initial level, while in-lab and split night testing were both at 61% of initial levels. Patients receiving initial home-based testing did not significantly differ in their likelihood of treatment, but were significantly less likely to have a clinical visit for sleep apnea (P < 0.01). Patients initially tested in 2021 were treated significantly more quickly than those initially tested in Q1 2019. Home-based testing occurring in Q4 2019 or later was significantly more likely to be definitive than home-based testing occurring Q1 2019.

CONCLUSIONS

Home-based sleep testing increased significantly and durably in 2020, and was associated with faster time to treatment than initial in-lab testing.

Environmental Benefits of Sleep Apnoea Detection in the Home Environment

Sleep Apnoea (SA) is a common chronic illness that affects nearly 1 billion people around the world, and the number of patients is rising. SA causes a wide range of psychological and physiological ailments that have detrimental effects on a patient’s wellbeing. The high prevalence and negative health effects make SA a public health problem. Whilst the current gold standard diagnostic procedure, polysomnography (PSG), is reliable, it is resource-expensive and can have a negative impact on sleep quality, as well as the environment. With this study, we focus on the environmental impact that arises from resource utilisation during SA detection, and we propose remote monitoring (RM) as a potential solution that can improve the resource efficiency and reduce travel. By reusing infrastructure technology, such as mobile communication, cloud computing, and artificial intelligence (AI), RM establishes SA detection and diagnosis support services in the home environment. However, there are considerable barriers to a widespread adoption of this technology. To gain a better understanding of the available technology and its associated strength, as well as weaknesses, we reviewed scientific papers that used various strategies for RM-based SA detection. Our review focused on 113 studies that were conducted between 2018 and 2022 and that were listed in Google Scholar. We found that just over 50% of the proposed RM systems incorporated real time signal processing and around 20% of the studies did not report on this important aspect. From an environmental perspective, this is a significant shortcoming, because 30% of the studies were based on measurement devices that must travel whenever the internal buffer is full. The environmental impact of that travel might constitute an additional need for changing from offline to online SA detection in the home environment.