LAUSR

INTRODUCTION The global pandemic caused by coronavirus (COVID-19) sped up the adoption of telemedicine. We aimed to assess whether factors associated with no-show differed between in-person and telemedicine visits. The focus is on understanding how social economic factors affect patient no-show for the two modalities of visits. METHODS We utilized electronic health records data for outpatient internal medicine visits at a large urban academic medical center, from February 1, 2020 to December 31, 2020. A mixed-effect logistic regression was used. We performed stratified analysis for each modality of visit and a combined analysis with interaction terms between exposure variables and visit modality. RESULTS A total of 111,725 visits for 72,603 patients were identified. Patient demographics (age, gender, race, income, partner), lead days, and primary insurance were significantly different between the two visit modalities. Our multivariable regression analyses showed that the impact of sociodemographic factors, such as Medicaid insurance (OR 1.23, p < 0.01 for in-person; OR 1.03, p = 0.57 for telemedicine; p < 0.01 for interaction), Medicare insurance (OR 1.11, p = 0.04 for in-person; OR 0.95, p = 0.32 for telemedicine; p = 0.03 for interaction) and Black race (OR 1.36, p < 0.01 for in-person; OR 1.20, p < 0.01 for telemedicine; p = 0.03 for interaction), on increased odds of no-show was less for telemedicine visits than for in-person visits. In addition, inclement weather and younger age had less impact on no-show for telemedicine visits. DISCUSSION Our findings indicated that if adopted successfully, telemedicine had the potential to reduce no-show rate for vulnerable patient groups and reduce the disparity between patients from different socioeconomic backgrounds.