Using Common Random Numbers in Health Care Cost-Effectiveness Simulation Modeling
Article first published online: 13 FEB 2013
© Health Research and Educational Trust
Health Services Research
Volume 48, Issue 4, pages 1508–1525, August 2013
How to Cite
Murphy, D. R., Klein, R. W., Smolen, L. J., Klein, T. M. and Roberts, S. D. (2013), Using Common Random Numbers in Health Care Cost-Effectiveness Simulation Modeling. Health Services Research, 48: 1508–1525. doi: 10.1111/1475-6773.12044
- Issue published online: 4 JUL 2013
- Article first published online: 13 FEB 2013
- Variance reduction;
- common random numbers;
- cost-effectiveness modeling;
To identify the problem of separating statistical noise from treatment effects in health outcomes modeling and analysis. To demonstrate the implementation of one technique, common random numbers (CRNs), and to illustrate the value of CRNs to assess costs and outcomes under uncertainty.
A microsimulation model was designed to evaluate osteoporosis treatment, estimating cost and utility measures for patient cohorts at high risk of osteoporosis-related fractures. Incremental cost-effectiveness ratios (ICERs) were estimated using a full implementation of CRNs, a partial implementation of CRNs, and no CRNs. A modification to traditional probabilistic sensitivity analysis (PSA) was used to determine how variance reduction can impact a decision maker's view of treatment efficacy and costs.
The full use of CRNs provided a 93.6 percent reduction in variance compared to simulations not using the technique. The use of partial CRNs provided a 5.6 percent reduction. The PSA results using full CRNs demonstrated a substantially tighter range of cost-benefit outcomes for teriparatide usage than the cost-benefits generated without the technique.
CRNs provide substantial variance reduction for cost-effectiveness studies. By reducing variability not associated with the treatment being evaluated, CRNs provide a better understanding of treatment effects and risks.