What you need to know
- the study: New research published in Mayo Clinic Proceedings: Digital Health Researchers at the Khan Center for Healthcare Delivery Sciences have revealed that wearable data may help predict patient engagement in remote COPD rehabilitation.
- Core issue: Patients with chronic obstructive pulmonary disease (COPD) often drop out of remote 12-week pulmonary rehabilitation programs. Because COPD severely affects sleep, patients often lack the energy to complete prescribed exercise.
Deciphering the “Composite Sleep Health Score”
This study focused on patients with chronic obstructive pulmonary disease (COPD). COPD causes inflammation, narrowing, and mucus buildup in the airways, making it very difficult to breathe and, in turn, sleep very difficult. When these patients are sleep deprived, their energy levels plummet and they are much less likely to participate in the rigorous exercise and education required for a 12-week pulmonary rehabilitation program.
“As a scientist and engineer, I wanted to explore how wearable data could improve withdrawal rates in telepulmonary rehabilitation programs,” said Dr. Stephanie Zawada, a researcher at the Mayo Clinic and lead author of the study.
To test this, Dr. Zawada and her team strapped wrist activity monitors onto patients for a week. before Rehabilitation at home begins. They used this data to generate a “composite sleep health score.”
When the scores from this wearable were combined with traditional clinical data and fed into a machine learning model, the algorithm’s predictive accuracy skyrocketed. The model was able to accurately predict the level of patient engagement over the next three months.
