1122 - Implementation of a Department-Wide Automated Electronic Health Record-Based Quality Surveillance Tool Assessing Acute Care Utilization and Mortality after Radiation Therapy

03:55pm - 04:00pm ET

Room 256

Presenter(s)

Mira Patel, MD, BS - UChicago Medicine, Chicago, IL

M. Patel¹, Y. Che², K. M. Yenice³, C. Stepaniak⁴, S. Williams⁴, R. R. Weichselbaum⁵, C. H. Son⁶, A. Juloori⁶, and S. Liauw⁶; ¹UChicago Medicine, Chicago, IL, United States, ²Department of Public Health Sciences, University of Chicago, Chicago, IL, ³Department of Radiation and Cellular Oncology, University of Chicago Medical Center, Chicago, IL, ⁴University of Chicago, Chicago, IL, ⁵Department of Radiation and Cellular Oncology, The University of Chicago Medicine, Chicago, IL, ⁶Department of Radiation and Cellular Oncology, University of Chicago, Chicago, IL

Purpose/Objective(s):

We developed and implemented an automated electronic health record (EHR)–based surveillance tool to longitudinally track 90-day acute care utilization (ACU) and mortality following radiation therapy (RT), with the goal of establishing a reproducible quality improvement framework and identifying patient-level risk factors for adverse outcomes.

Materials/Methods:

A custom program was created to query structured EPIC EHR fields for patients who completed RT at a single academic center. Consecutively treated patients over a rolling 3-year time period were identified and 90-day ACU (oncology rapid assessment clinic (ORAC) visits, ER visits, unplanned hospital admissions), and all-cause mortality were registered. Baseline covariates included age, gender, race, chemotherapy (CHT) use, and year of treatment. Univariate analyses compared event rates across covariates. Multivariable logistic regression models evaluated predictors of ER visits, hospital admissions, and mortality. A secondary single-attending analysis integrating manual chart review evaluated the impact of disease site and treatment intent on outcomes.

Results:

Between 1/2023-9/2025, 3,132 pts received RT by 10 attendings. 49.6% were female, 40.5% were Black, and 44.3% received CHT. Within 90 days of RT completion, 3.0% had an ORAC visit, 8.5% had an ER visit, 12.2% had an unplanned hospital admission, and 6.3% died. On UVA, ACU was higher among pts receiving CHT (ORAC 5% vs 1%, ER 10/7, and admission 16/9, <0.01), females (ORAC 4/2, p=0.009), and Black race (ER 13/5, admissions 17/9, p<0.01). Mortality was higher for females (7/5, p=0.025) and was associated with ER visit (13/6, p<0.01) and hospital admission (21/4, p<0.01) but not ORAC visit (9/6, p=0.38). On MVA including all baseline covariates, CHT and Black race were associated with both ER visit and hospital admissions, while female gender (OR 1.38, CI 1.02-1.86, p=0.04) and hospital admission were associated with mortality (OR 7.1, CI 4.9-10.2, p<0.01). ACU varied by attending and disease site specialization. In a cohort of 502 patients treated by one attending, prostate cancer pts treated with curative intent (77%) had low ER or admission rates (3.1%) and minimal 90-day mortality (0.3%). Curative intent non-prostate pts demonstrated intermediate ER or admission rates (9.5%), while palliative pts experienced substantially higher ER or admission rates (23.5%) and 90-day mortality (14.7%).

Conclusion:

An automated EHR surveillance tool was successfully developed to provide readily available quality metrics after RT. This framework provides insight into identifying adverse populations who may benefit from targeted interventions, including enhanced clinical support during and after RT. Since treatment intent and case mix are critical determinants of mortality, work is underway to incorporate diagnosis, RT dose, and treatment intent by linking a radiation-specific EHR.