2024 ARRS ANNUAL MEETING - ABSTRACTS

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5258. Utilizing Large Volume CT Data to Uncover Trends in Radiology Resource Utilization and Survival in Socioeconomically Disadvantaged Patients
Authors * Denotes Presenting Author
  1. Matthew Lee *; University of Wisconsin School of Medicine and Public Health
  2. Benjamin Rush; University of Wisconsin School of Medicine and Public Health
  3. John Garrett; University of Wisconsin School of Medicine and Public Health
  4. Perry Pickhardt; University of Wisconsin School of Medicine and Public Health
Objective:
This study aims to assess the relationship between socioeconomic disadvantage, CT utilization, and patient survival using national area deprivation index (ADI) in a large cohort undergoing abdominal CT imaging.

Materials and Methods:
The study includes a retrospective cohort study of patients undergoing an initial abdominal CT at a single academic center. National ADI rank at the census block group level (percentile rank, 1 - 100) was utilized as a measure of socioeconomic disadvantage with 1 being the lowest and 100 being the highest level of “disadvantage.” Age at CT examination setting (inpatient, outpatient, emergency settings; available for 45% of exams), age at death, and time from CT to death (survival time) were documented from the EHR. Pearson correlation analysis was performed to determine the association between national ADI and age at death and survival time. Histograms and density curves were generated for CT utilization and patient survival measures across ADI quintiles.

Results:
A total of 91,434 adult patients (48,530 women, 42,904 men) underwent abdominal CT from January 2001 - November 2021. Mean (SD) ADI was 46 (21). For examination setting, the mean (SD) ADIs were 54 (22), 43 (20), and 41 (19) for inpatient, outpatient, and emergency settings, respectively (<em>p</em> < .001 for all). National ADI was negatively associated with both age at death (<em>r</em> = -0.18, <em>p</em> < .001) and survival time (<em>r</em> = -0.10, <em>p</em> < .001). Patients from more disadvantaged neighborhoods (higher ADI) died younger, with shorter survival time after CT. Negative associations were observed between age at CT and survival time for the least disadvantaged (lowest) quintile (<em>r</em> = -0.41, <em>p</em> < .001) and the most disadvantaged (highest) quintile (<em>r</em> = -0.60, <em>p</em> < .001). Patients from more disadvantaged neighborhoods were older at CT, and had shorter survival following CT compared with patients from more disadvantaged neighborhoods.

Conclusion:
Socioeconomic disadvantage is associated with differences in abdominal CT utilization and patient survival. Patients from more socioeconomically disadvantaged neighborhoods were older at initial CT, younger at death, more likely to have an initial CT in the inpatient setting, and had shorter survival time after CT. Large-volume radiology data sets in conjunction with tools like ADI can provide meaningful insights into health disparities, radiology resource utilization, and patient outcomes, which may be underappreciated.