Data from wearables provide more comprehensive view of COPD, researchers say

ROCHESTER, Minn. – Sleep data captured with a wearable device could help clinicians better tailor care by identifying patients with chronic obstructive pulmonary disease (COPD) who may need additional support to participate in pulmonary rehabilitation, according to new research published in Mayo Clinic Proceedings: Digital Health. In the study, researchers found that using baseline sleep data from a wrist activity monitor, combined with machine learning and traditional clinical indicators, improved the prediction of how consistently patients would participate in a 12-week home pulmonary rehabilitation program. "As a scientist and engineer, I wanted to explore how wearable data could improve the drop-out rates of remote pulmonary rehabilitation programs,” said Stephanie Zawada, Ph.D., M.S., a Mayo Clinic research associate and first author of the study. “By better understanding a patient's day-to-day life, we can make more personalized and potentially more effective care plan recommendations.” Researchers made their calculations after collecting sleep measures for one week to generate a Composite Sleep Health Score before the home-based pulmonary rehabilitation began. At the end of the 12-week program, their analysis showed that including the health score improved prediction of patient engagement over the study period. Researchers say this information can help clinicians better tailor rehabilitation programs and identify patients who may benefit from additional support. It also may inform the design of future remote-care programs, they say. "Adding wearable data provides a more comprehensive view of a patient's daily pattern," says Emma Fortune Ngufor, Ph.D., senior author of the study and a Mayo Clinic researcher in the Kern Center for the Science of Health Care Delivery.