Click on each event type below to learn more.

Course Type Information:

October 2026


01
OCT

Shared Decision Making Hour – October 2026

01 October 2026

Shared Decision Making Hour is a monthly open forum hosted by Shared Decision Making SIG for anyone interested in exploring the latest in shared decision making (SDM). We welcome all perspectives and encourage open dialogue!

Shared Decision Making Hour - October 2026
08
OCT

SMDM Webinar: Calibrating Markov Models to Clinical Survival Data

08 October 2026

Building accurate Markov models is challenging because they cannot easily be matched up with clinical survival data. Partitioned Survival models are built directly on survival curves that can be fitted to clinical data through regression analysis. However, Partitioned Survival models are limited to forward progression, and they do not support critical events beyond implicit progression and death. Markov models are instead built on distinct events including, but not limited to, progression and death. However, Markov models cannot be directly fitted to clinical survival data because disease progression results from a combination of event risks applied over time. For Markov models, curve-fitting calibration techniques can refine event probabilities to match multi-cause disease progression to clinical survival data.

SMDM Webinar: Calibrating Markov Models to Clinical Survival Data

November 2026


12
NOV

Understanding Individual Differences in Medical Decision Making

12 November 2026

Individual differences can shape how patients and clinicians process information and make medical decisions. This course will introduce key concepts and methods for studying individual differences, explore how they can be incorporated into research, and identify opportunities for future work.

Understanding Individual Differences in Medical Decision Making
19
NOV

Causal Machine Learning for Health Economics and Decision Making

19 November 2026

This course introduces methods for combining machine learning (ML) and causal inference to improve health economic evaluations and decision-making. Participants will learn how ML can be used for prediction, estimating treatment effects, and designing stratified treatment policies. The course will also demonstrate practical implementation of these methods in R, with accompanying code provided.

Causal Machine Learning for Health Economics and Decision Making

December 2026


09
DEC

Simulation Models in Public Health Decision Making

09 December 2026

This short course will provide a survey of commonly used simulation models for decision making in public health research, including cohort-/population-based simulation, microsimulation, agent-based, and compartmental models.

Simulation Models in Public Health Decision Making