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Telemedicine has long been considered as an attractive alternative methodology in clinical genetics to improve patient access and convenience. Given the importance of the dysmorphology physical examination and anthropometric measurement in clinical genetics, many have wondered if lost information would hamper diagnosis. We previously addressed this question by analyzing thousands of diagnostic encounters in a single practice involving multiple practitioners and found no evidence for a difference in new molecular diagnosis rates. However, our previous study design resulted in variability in providers between in-person and telemedicine evaluation groups. To address this in our present study, we expanded our analysis to 1104 new patient evaluations seen by one highly experienced clinical geneticist across two 10-month periods before and after the start of the COVID-19 pandemic. Comparing patients seen in-person to those seen by telemedicine, we found significant differences in race and ethnicity, preferred language, and home zip code median income. The clinical geneticist intended to send more genetic testing for those patients seen by telemedicine, but due to issues with test authorization and sample collection, there was no difference in ultimate completion rate between groups. We found no significant difference in new molecular diagnosis rate. Overall, we find telemedicine to be an acceptable alternative to in-person evaluation for routine pediatric clinical genetics care.

Objective We sought to develop and evaluate an electronic health record (EHR) genetic testing tracking system to address the barriers and limitations of existing spreadsheet-based workarounds. Materials and Methods We evaluated the spreadsheet-based system using mixed effects logistic regression to identify factors associated with delayed follow up. These factors informed the design of an EHR-integrated genetic testing tracking system. After deployment, we assessed the system in 2 ways. We analyzed EHR access logs and note data to assess patient outcomes and performed semistructured interviews with users to identify impact of the system on work. Results We found that patient-reported race was a significant predictor of documented genetic testing follow up, indicating a possible inequity in care. We implemented a CDS system including a patient data capture form and management dashboard to facilitate important care tasks. The system significantly sped review of results and significantly increased documentation of follow-up recommendations. Interviews with key system users identified a range of sociotechnical factors (ie, tools, tasks, collaboration) that contribute to safer and more efficient care. Discussion Our new tracking system ended decades of workarounds for identifying and communicating test results and improved clinical workflows. Interview participants related that the system decreased cognitive and time burden which allowed them to focus on direct patient interaction. Conclusion By assembling a multidisciplinary team, we designed a novel patient tracking system that improves genetic testing follow up. Similar approaches may be effective in other clinical settings.