Abstract P372: Drivers of Visit Modality in Primary Care Clinics at an Academic Medical Center

Background: Informed by drivers of visit modality in specialty clinics, we sought to identify factors associated with visit modality selection (telemedicine vs. in-person) for new and return visits in primary care clinics at a large academic medical center (AMC). Methods: We used electronic health record data from 3/2020 - 5/2022 from 13 primary care clinics with 98 unique clinicians for new and 131 for return visits (21,031 new & 207,292 return visits), with about 55% telemedicine (telephone and video) use. We used hierarchical logistic regression and cross-validation methods to estimate the variation in visit modality associated with the patient, clinician, and visit factors (measured with Area Under the Curve). Results: For both new and return visits, there was significant variation in telemedicine use among clinicians (ranging from 0 - 100%) for specific clinical diagnoses (Figure 1). Most variation in telemedicine use was attributed to the clinician seen (new visits) and primary visit diagnosis (return visits). Other visit and patient characteristics were less predictive. For new visits, the clinician model had an AUC of 0.79, followed by clinic site 0.69, whereas for return visits, the primary diagnosis was 0.77, followed by the clinician seen at 0.65. Diagnoses most commonly seen via telemedicine include acute respiratory infection and suspected COVID-19 exposure. Diagnoses commonly seen in-person include annual physical and gynecological exams. Conclusions: Our findings show high variability in telemedicine use for the same diagnosis and differential drivers of visit modality between new and return visits in primary care clinics at a large AMC. Provider ID was the most predictive factor of visit modality for new patients, indicating that clinician preference and individual practice patterns influence the modality of care much more than patient preference. Primary care clinics may reduce the variability in visit modality through standardized processes that integrate clinical factors and patient preference.