Bio
Fernando Alarid-Escudero, Ph.D., is an Assistant Professor of Health Policy at Stanford University School of Medicine. He is a decision scientist specializing in disease simulation, decision-analytic modeling, and cost-effectiveness analysis to inform health policy questions that cannot be readily answered through clinical studies alone. He has also developed novel methods to quantify the value of future research and calibrate simulation models using emulator-based Bayesian methods. Dr. Alarid-Escudero is a member of three cancers (colorectal [CRC], bladder, and gastric) of the Cancer Intervention and Surveillance Modeling Network (CISNET) consortium, a group of investigators sponsored by the National Cancer Institute in the U.S. that uses simulation modeling to evaluate the impact of cancer control interventions (e.g., prevention, screening, and treatment) on population trends in incidence and mortality. Dr. Alarid-Escudero co-founded the Decision Analysis in R for Technologies in Health (DARTH) workgroup (http://darthworkgroup.com) and the Collaborative Network on Value of Information (ConVOI; https://www.convoi-group.org), international and multi-institutional collaborative efforts that develop transparent and open-source solutions to implement decision analysis and quantify the value of potential future investigation for health policy analysis.
