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Contemporary Microhematuria Evaluation in Veterans: Cancer Detection and Resource Utilization
Krishay Sridalla1, Joseph D Nicolas2, Lili Zhao3
1Department of Surgery, Northwestern University Feinberg School of Medicine, Chicago, IL.
Urology
|February 22, 2026
Summary
Urologic consultations for microhematuria (MH) are frequent in Veterans, but bladder cancer (BCa) detection is low. Optimizing diagnostic thresholds and imaging strategies can reduce costs and improve resource allocation for MH evaluation.
Area of Science:
- Urology
- Oncology
- Health Economics
Background:
- Microhematuria (MH) evaluation in Veterans Affairs (VA) centers involves urologic consultations, with bladder cancer (BCa) detection rates varying.
- Current diagnostic pathways and risk stratification for MH require examination to optimize resource utilization and patient outcomes.
Purpose of the Study:
- To evaluate the patterns of urologic consultations for MH in Veterans.
- To determine the distribution of BCa detection across different risk strata.
- To estimate the costs associated with current and alternative evaluation strategies for MH.
Main Methods:
- Retrospective study of Veterans with MH at Jesse Brown VA (2021-2024).
- Risk stratification based on MH severity (red blood cells per high-powered field) and age.
- Assessment of urology consultation rates, BCa detection, and procedural costs for different strategies.
Main Results:
- 71.6% of 1,046 Veterans received a urology consult, irrespective of risk stratification.
- BCa was detected in only 7 high-risk patients (0.7%).
- Raising the diagnostic threshold to ≥26 RBC/hpf significantly reduced total costs but increased per-patient costs.
Conclusions:
- Urologic evaluation for MH is common in Veterans, but BCa yield is low, primarily in high-risk individuals.
- Current referral patterns may lead to overuse of resources for low-risk patients.
- Adjusting diagnostic thresholds and imaging modalities (e.g., ultrasound over CT for low-risk patients) could decrease costs, warranting further multi-center validation.
