Cost-Minimization Analysis of Risk-Stratified Hematuria Evaluation

Authors

Jing Hao, Geisinger Health SystemFollow
Susan R. Synder, Geisinger Health System
Amanda J. Young, Geisinger Health System
H. Lester Kirchner, Geisinger Health System

Publication Date

8-15-2016

Keywords

hematuria evaluation, cost-minimization analysis

Abstract

Background/Aims: Up to 30% of adults have hematuria; however, 5% or fewer have a significant finding such as bladder or kidney cancer. Current guidelines recommend cystoscopy and imaging for all who meet criteria; however, the guidelines acknowledge evidence gaps resulting in substantial unnecessary testing with adverse financial implications for patients and society. Although risk-stratified approaches have the potential to reduce testing, few are available and none have been rigorously evaluated. The objective of this study is to compare the direct health care costs of two hematuria evaluation approaches: American Urological Association (AUA) guideline-based standard of care versus a theoretical risk-stratified algorithm.

Methods: We will apply decision-analysis modeling and simulation to conduct a cost-minimization analysis, a type of cost-effectiveness analysis that compares interventions of similar effectiveness, to compare the two hematuria evaluation approaches. Model inputs including assumptions and parameter values will be obtained from an established Geisinger Health System hematuria patient database. The database includes patient-level clinical information compiled from extensive chart review of 3,000 patients for whom hematuria evaluations were conducted from 2004 to 2014. Costs for services are based on Medicare reimbursement rates. Data from published literature and inputs from a clinical expert panel will supplement the model inputs.

Results: The results to be presented are a decision-analysis model with assumptions, parameters and input values documented from the Geisinger hematuria database, literature review and clinical expert inputs. The analysis of deterministic decision model provides base-case clinical and economic results for the two approaches.

Conclusion: The finalized results of the cost-minimization analysis will enable threshold analysis to identify critical parameter values (e.g. sensitivity, specificity) for the performance of a theoretical risk-stratified approach to match the effectiveness of the current AUA guideline-based standard of care, and compare the direct health care costs of the two hematuria evaluation approaches from payer perspective. These results will provide a foundation of evidence and a model to evaluate risk-stratified approaches.

Recommended Citation

Hao J, Snyder SR, Young AJ, Kirchner HL. Cost-minimization analysis of risk-stratified hematuria evaluation. J Patient Cent Res Rev. 2016;3:208.