Mobile application-based oximetry: a potential toolfor appropriate referral of patients with respiratory symptoms examined via telemedicine

ABSTRACT

Objective

To calculate the positive likelihood ratio to determine whether telemedicine is able to optimize referral to the emergency department.

Methods

Unicenter study with 182 consecutive patients admitted to Hospital Israelita Albert Einstein due to respiratory symptoms. All patients were submitted to oxygen saturation measurement using the standard method Welch Allyn finger device vital sign monitor and a 2-minute evaluation (Binah.ai mobile application). The reproducibility of oxygen saturation measurements made with both methods was investigated using interclass correlation coefficients and analysis of dispersion. Bland-Altman plots were constructed and kappa concordance coefficients used to examine data normality. Accuracy was also estimated.

Results

Oxygen saturation measurement differences between methods were ≤2% in more than 85% of cases. The mean difference (bias) between methods was near zero (0.835; Bland-Altman analysis). Oxygen saturation measurements made using the Binah.ai mobile application had an average ability to detect patients with altered oxygen saturation levels compared to the conventional method (ROC analysis). The positive likelihood ratio of the mobile application was 6.23.

Conclusion

Mobile applications for oxygen saturation measurement are accessible user-friendly tools with moderate impact on clinical telemedicine evaluation of patients with respiratory symptoms, and may optimize referral to the emergency department.

Oximetry; Dyspnea; Signs and symptoms; Respiratory tract diseases; Telemedicine; Referral and consultation; Artificial intelligence