The use of pulse oximeters to measure oxygen levels in patients with COVID-19 has been a common practice, with the assumption that it could help detect deteriorating health earlier. However, new research from the Perelman School of Medicine at the University of Pennsylvania suggests that this approach may not offer significant benefits compared to simply asking patients about their symptoms.
The study, published in the New England Journal of Medicine, found that incorporating pulse oximeters into remote monitoring programs did not result in better outcomes for patients with COVID-19. The research, conducted as part of Penn Medicine’s COVID Watch program, compared outcomes between patients who used pulse oximeters and those who did not.
Dr. Anna Morgan, the study’s co-lead author and medical director of the COVID Watch program, noted that pulse oximeters did not save more lives or reduce hospitalizations compared to simple automated check-ins for shortness of breath. The study involved more than 2,000 patients enrolled in the COVID Watch program between November 2020 and February 2021.
Despite the widespread adoption of pulse oximeters early in the pandemic, this study, which is the first randomized trial to test their effectiveness, found no statistical difference in outcomes between patients who used pulse oximeters and those who did not. The average number of days spent alive and out of the hospital in the 30 days after enrollment was similar for both groups.
Dr. Kathleen Lee, another co-lead author of the study, highlighted the intuitive appeal of using pulse oximeters but emphasized the lack of evidence supporting their effectiveness. The study’s principal investigator, Dr. M. Kit Delgado, stressed the importance of evidence-based approaches in healthcare decision-making.
Overall, the findings suggest that a low-tech approach based on symptoms may be just as effective as more expensive methods involving additional devices like pulse oximeters. Automated text messaging, as implemented in the COVID Watch program, was found to be a practical and efficient way to monitor large populations of patients with COVID-19.