BACKGROUND Those older than 65 years represent the fastest growing demographic in the United States. As such, their care has been emphasized by trauma entities such as the American College of Surgeons Committee on Trauma. Unfortunately, much of that focus has been of their care once they reach the hospital with little attention on the access of geriatric trauma patients to trauma centers (TCs). We sought to determine the rate of geriatric undertriage (UT) to TCs within a mature trauma system and hypothesized that there would be variation and clustering of the geriatric undertriage rate (UTR) within a mature trauma system because of the admission of geriatric trauma patient to nontrauma centers (NTCs). METHODS From 2003 to 2015, all geriatric (age >65 years) admissions with an Injury Severity Score of greater than 9 from the Pennsylvania Trauma Systems Foundation (PTSF) registry and those meeting trauma criteria (International Classification of Diseases, Ninth Revision: 800–959) from the Pennsylvania Health Care Cost Containment Council (PHC4) database were included. Undertriage rate was defined as patients not admitted to TCs (n = 27) divided by the total number of patients as from the PHC4 database. The PHC4 contains all inpatient admissions within Pennsylvania (PA), while PTSF reports admissions to PA TCs. The zip code of residence was used to aggregate calculations of UTR as well as other aggregate patient and census demographics, and UTR was categorized into lower, middle box, and upper quartiles. ArcGIS Desktop: Version 10.7, ESRI, Redlands, CA and GeoDa: Version 1.14.0, Open source license were used for geospatial mapping of UT with a spatial empirical Bayesian smoothed UTR, and Stata: Version 16.1, Stata Corp., College Station TX was used for statistical analyses. RESULTS Pennsylvania Trauma Systems Foundation had 58,336 cases, while PHC4 had 111,626 that met the inclusion criteria, resulting in a median (Q1–Q3) smoothed UTR of 50.5% (38.2–60.1%) across PA zip code tabulation areas. Geospatial mapping reveals significant clusters of UT regions with high UTR in some of the rural regions with limited access to a TC. The lowest quartile UTR regions tended to have higher population density relative to the middle or upper quartile UTR regions. At the patient level, the lowest UTR regions had more racial and ethnic diversity, a higher injury severity, and higher rates of treatment at a TC. Undertriage rate regions that were closer to NTCs had a higher odds of being in the upper UTR quartile; 4.48 (2.52–7.99) for NTC with less than 200 beds and 8.53 (4.70–15.47) for NTC with 200 beds or greater compared with zip code tabulation areas with a TC as the closest hospital. CONCLUSION There are significant clusters of geriatric UT within a mature trauma system. Increased emphasis needs to focus prehospital on identifying the severely injured geriatric patient including specific geriatric triage protocols. LEVEL OF EVIDENCE Epidemiological, Level III.