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He has over 10 years of experience in health related outcome research and quantitative analysis including microsimulation, cost effectiveness analysis, statistical modeling and data mining. He specializes in modeling onset and consequences of various chronic conditions among different target cohorts, and forecasting clinical and economic impact as result of intervention and other measures. He also takes the lead in developing and expanding capability of the proprietary Disease Prevention Microsimulation Model, which is a Markov based simulation model that makes annual projection on disease incidents, mortality, health expenditure and indirect economic outcomes through 100+ prediction equations. Examples of his past and ongoing work include: (1) projection of national and state level clinical and economic burden of chronic diseases; (2) return on investment analysis of a digital intensive behavior counseling program on people at risk for diabetes and cardiovascular disease; (3) budgetary impact of expanding Medicare coverage on obesity treatment; (4) estimation on benefit of improved diabetes treatment to Medicaid beneficiaries; (5) modeling the impact of anti-opioids abuse treatment in the US. Frank has published on multiple peer reviewed journals such as the American Journal of Managed Care, Journal of Medical Economics, Preventing Chronic Disease, PLOS One, International Journal of Cardiology, BMC medical Genetics etc. Frank holds a Ph.D. degree in computational biology and an M.S. degree in Statistics from Rutgers University.