Racialized inequities in total hip arthroplasty (THA) are attributed to multiple structural and institutional factors. Robust evaluation of time-to-THA would enable data-driven structural and institutional responses to both mitigate any inequities and optimize care accessibility across the US Military Health System (MHS). The objective of this study was to evaluate time-to-THA after hip osteoarthritis diagnosis in the MHS. It was hypothesized that there will be racialized inequities in time-to-THA; and racialized inequities will replicate in sensitivity analyses of patients receiving only care in the direct (military treatment facilities) versus purchased (civilian network) care systems. This retrospective cohort study was provided an exempt determination by the Uniformed Services University Human Protections Office. Medical records from March 1, 2015 to June 21, 2024 were de-identified and extracted from the MHS Information Platform. Records of adult patients were included if they were enrolled in TRICARE Prime, TRICARE Plus, and Direct Care Only plans, received a hip osteoarthritis diagnosis between March 1, 2018 and March 30, 2023, without prior 3-year diagnosis, and received at least one additional visit 1 week to 3 years post-index. Patient records were excluded if they lacked documented race and ethnicity in their administrative records. The primary outcome was time-to-THA within 3 years of index. To evaluate potential racialized inequities, the primary covariate was patient race and ethnicity. Additional fixed and time-dependent covariates included patient-level (e.g., sex assigned in the medical record, age, beneficiary category) and-care-level information (e.g., cumulative days of therapeutic visits, opioid prescriptions, days of orthopedic surgeon visits, and days of imaging visits). A Cox proportional hazards model was used to assess the proportionality of covariate levels. Any covariate that did not meet the proportionality assumption was included as time-varying covariates in a piecewise exponential additive model. A piecewise exponential additive model is a Poisson generalized additive model used to evaluate time-to-event outcomes and accounts for time-dependent and time-varying covariates, in addition to non-linear relationships between covariates and the outcome. Sensitivity models repeated the primary model, but included patients who received all hip osteoarthritis care in the direct versus purchased care systems. Of the 33979 patients diagnosed with hip osteoarthritis, 28% of patients received a THA within 3 years of index diagnosis. Approximately half (52%) of the sample received all hip osteoarthritis care (e.g., index diagnosis and follow-up care) in the purchased care system only; 20% received only direct system care for hip osteoarthritis; the remaining 28% received hip osteoarthritis care across both systems. The primary model indicated time-to-THA (incidence rate ratios (IRR), 95% CI) was longer for Asian and Pacific Islander (0.78, 0.67-0.90) and Latine (0.84, 0.73-0.96) patients relative to white patients. There were significant fixed (IRR 0.76, 0.71-0.81) and time-varying effects for Black patients compared to white patients, such that cumulative hazard differences had the steepest reductions in the first year. Inequities experienced by Black patients replicated across sensitivity models of patients receiving all hip osteoarthritis care in military versus civilian facilities. Overall, this study identified racialized THA inequities. Previous US Government Accountability Office and Department of Defense Inspector General reports have consistently identified the delays in specialty care receipt for MHS beneficiaries. Taken together, a robust, data-driven approach to personnel allocation, surgical center resourcing, and TRICARE reimbursement models should account for practice locations of orthopedic surgeons in the direct and purchased healthcare systems, including those not participating in TRICARE, care accessibility considering local population care requirements (e.g., population density relative to orthopedic surgeon density), structural determinants of health impacting health and healthcare access for TRICARE beneficiaries, and evidence-based models of care.