News

CHDS faculty Nicolas Menzies and colleagues found that geographic differences across states and municipalities in Brazil played a larger role than patient-level factors in explaining

Target trial emulation is a causal inference framework that can be used to model and estimate clinical trial outcomes, expanding information available for decision-making when budgets, ethics, feasibility

CHDS faculty Ankur Pandya, doctoral student Andrea Luviano, and former student Jihye Han re-analyzed the value assessments underlying the American Heart Association (AHA) guidelines

The Generalized Risk-Adjusted Cost-Effectiveness (GRACE) framework is a new approach to cost-effectiveness analysis (CEA) that addresses issues related to understanding patient priorities and variation in

CHDS’s Jagpreet Chhatwal and colleagues evaluated the effect of multicancer early detection (MCED) tests – commonly known as liquid biopsy — for fourteen solid tumor cancer types and found that adoption

Boshen Jiao, former postdoctoral fellow in the Department of Global Health and Population, CHDS faculty Stéphane Verguet, and colleagues recently published a study in

CHDS faculty Jagpreet Chhatwal and colleagues, on behalf of the ISPOR Working Group on Generative AI, recently published an article in Value in Health that provides foundational

CHDS faculty Nicolas Menzies and colleagues projected how funding cuts from US bilateral health aid and The Global Fund to Fight AIDS, Tuberculosis, and Malaria could lead to increases

CHDS researchers Emily Burger, Stephen Sy, Mary Caroline Regan, and Jane Kim, as well as former postdoctoral fellow Jenny Spencer, collaborated with an international team

Conventional decision analytic models typically use probability distributions to represent parameter uncertainty. Thomas Trikalinos has developed a novel approach for representing uncertainty