{'fraction_non_alphanumeric': 0.04151177199504337, 'fraction_numerical': 0.031598513011152414, 'mean_word_length': 5.046816479400749, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Abstract P17: Effect of telemedicine adoption on accessibility and time to treatment in patients with thoracic malignancies during the COVID-19 pandemic

Introduction: To ensure safe delivery of oncologic care in the COVID-19 pandemic, telemedicine has been rapidly adopted. We assessed accessibility and time to treatment initiation for thoracic oncology patients seen via telemedicine or in-person during the initial phase of the COVID-19 pandemic. Methods: We conducted a retrospective cohort study of patients with thoracic malignancies seen within a multidisciplinary team at the University of Pennsylvania Health System (UPHS) during the first surge of COVID-19 cases in Philadelphia (March 1 to June 30, 2020). Patients with an index visit for a new phase of care, defined as a new diagnosis, local recurrence, or newly discovered metastatic disease were included. Patients who did not receive subsequent oncologic care within the UPHS were excluded. Dates of referral, index visit, and treatment initiation were ed from the electronic medical record (EMR). Patients were divided into groups based on index visit type (in-person vs. telemedicine). Comparisons of time to care between groups were evaluated using the Wilcoxon rank-sum test. Results: Between March 1 and June 30, 2020, 241 distinct thoracic oncology patients were seen for a new phase of care and managed with surgery (n=78, 32.4%), radiation (including concurrent chemoradiation) (n=59, 24.5%), or systemic therapy (n=73, 30.3%). The majority of visits were for a diagnosis of a new thoracic cancer (87.1%). 133 patients (55.2%) were seen in-person and 108 (44.8%) were seen via telemedicine. Baseline characteristics of patients seen via telemedicine vs in-person were well balanced. As expected, the proportion of telemedicine to in-person visit types changed with the local phase of the pandemic with an initial increase of telemedicine during the lockdown period and a decrease during the re-opening phase. A higher proportion of visits were conducted via telemedicine when receiving systemic therapy or radiation as compared to surgery. Among patients with new diagnoses (n=210), the median time from referral to initial visit was significantly shorter amongst the patients seen via telemedicine vs. in-person (4.5 vs. 6.0 days, p=0.006), though only 67.1% had referral dates reported in the EMR. Time-to-treatment stratified by treatment modality received did not differ by type of initial visit (median values in-person vs. telemedicine: surgery 16 vs. 22 days, p= 0.48;radiation 26.5 vs. 28 days, p=0.90;systemic therapy 13.5 vs. 14 days, p=0.49). A sensitivity analysis limited to new diagnoses only (210/241) confirmed the same results. Conclusions: Rapid adoption of telemedicine sustained timely delivery of oncologic care during the initial surge of the COVID19 pandemic across a thoracic oncology multi-disciplinary clinic. While the full impact of telemedicine on long term clinical outcomes remains to be determined, faster times from referral to initial visit in the telemedicine group provide preliminary evidence that telemedicine could sustain or improve accessibility to oncologic care, especially during current and future pandemics.