Quality outcomes of implementing a solid oncology hospitalist service at an urban, academic medical center.

71 Background: The use of hospitalists on an oncology service has been shown to improve quality outcomes among hospitalized patients with cancer, though there is limited data on the use of hospitalists to care for patients with solid tumor malignancies. The Solid Oncology Hospitalist Service at the Mount Sinai Hospital was created in efforts to improve overall care and management of primarily acute medicine related patient admissions. In this abstract, we will discuss quality outcomes. Methods: We created a Solid Oncology Hospitalist Service, led by hospitalists and nurse practitioner front line providers. Patients with active oncologic issues, such as side effects from recent chemotherapy or those requiring specialty oncology management, were seen by the solid tumor consult service as well, led by disease specific medical oncologists and oncology fellows/PA. We used descriptive statistics and Chi-square to evaluate a pre-implementation period from 7/1/2022 – 6/30/2023 and compared to a post- implementation period from 7/1/2023-6/30/2024. We also evaluated differences in length of stay (LOS) in the post period for those twho did and did not have a consult. Results: Inpatient metrics are in the table. Average LOS and discharge before noon rates were similar pre and post implementation. Additionally, in the post-implementation period, more medically complex patients who required a solid oncology consult had an average length of stay (LOS), of 11.4 days vs 8.2 days for those patients who did not require a consult. Conclusions: In this first year of our program, we saw stability in inpatient quality metrics. While hoping for improvement, we acknowledge that change takes time, and it highlights that focused medical management of oncologic patients requires expertise of both hospital and oncologic medicine. These findings suggest that this collaborative, multidisciplinary model can be integrated into inpatient oncology workflows without disrupting readmission rates, length of stay, or discharge dispositions and lays the groundwork for future studies to refine patient selection, optimize care pathways, and assess downstream impacts on quality and patient experience. Quality metrics pre and post implementation. Measure Pre (n=426) (n/%) Post (n=429) (n/%) p value Discharge Before Noon 57 (13.4) 58 (13.5) 1.0 Average LOS (days) 10.6 10.8 0.7 Discharge Disposition Home Hospice 255 (60) 7 (1.6) 259 (60) 3 (0.7) 0.2