263 Background: No-Shows are pervasive across healthcare systems and are associated with interrupted clinical workflows, increased cost, healthcare utilization, and increased morbidity, and mortality. In palliative care, patients who miss their appointments are more likely to have uncontrolled symptoms, frequent Emergency Room visits, and unplanned hospitalization. There is an ongoing need to reduce no-shows to improve patient outcomes. Methods: The aim of this quality improvement (QI) project, launched in September 2022 at the outpatient supportive care center (SCC) at the University of Texas MD Anderson Cancer Center, was to reduce overall no-shows by process improvement in the targeted areas. We developed a process map and Ishikawa diagram to outline workflow and reasons for no-shows. Based on the results of a previous study from our center, 8% of no-shows were due to hospitalization. We used the Plan Do Study Act (PDSA) tool. We developed an electronic query for the Electronic Health Record (EHR) to identify hospitalized patients with an upcoming appointment at SCC in the next 10 days. We redesigned the clinical workflow to generate a daily list of such appointments which were canceled and replaced by patients on the waitlist. We assessed overall no-show rate and rate specific to hospitalizations for our center monthly for eight months. This QI project was approved by the Quality Improvement Assurance Board at the University of Texas MD Anderson Cancer Center. Results: Overall no-show rate was 12% before intervention (BI) and decreased to 8% after intervention (AI), measured at 8 months. No-show rate due to hospitalizations decreased from 9% BI to 2% AI. Telehealth visits had a lower rate of no-shows (5.9%) than in person visits (10.4%). No-show rates did not differ based on days of the week (median 7.4%, SD 0.3%), and the type of visit - consult vs. follow-up (8% vs. 7%). Conclusions: Clinical workflow redesign using EHR at our SCC decreased no-shows due to hospitalization, thereby reducing overall no-show rate by 33% of the original. However, most no-shows are due to reasons other than hospital stays, and more research is needed to identify these patient and system level factors.