Principles, Pitfalls, and Advanced Applications
228 June 2026, 8:35 AM – 12:00 PM (local time)
Faculty
- Andrew Briggs, DPhil – Professor of Health Economics, London School of Hygiene & Tropical Medicine, United Kingdom
- Elisabeth Fenwick, PhD – Professor of Health Economics, OPEN Health, United Kingdom
- Alex Hill – Senior Methodological Researcher, London School of Hygiene & Tropical Medicine, United Kingdom
- Ziyi Lin – Health Economist, London School of Hygiene & Tropical Medicine, United Kingdom
Course Overview
Survival analysis is central to contemporary health technology assessment (HTA), yet in practice it is frequently applied in a mechanistic way that obscures structural assumptions and weakens decision relevance. This half-day short course provides a rigorous, decision-focused overview of survival analysis for HTA, drawing on an established two-day course but delivered here in an intentionally streamlined format.
The course focuses exclusively on didactic material, emphasizing conceptual clarity rather than hands-on implementation. It bridges statistical survival analysis and decision-analytic modelling, highlighting how alternative survival frameworks influence cost-effectiveness results and policy conclusions. Particular attention is paid to the widespread use (and misuse) of partitioned survival models, with a clear articulation of their potential and their limitations.
Illustrative examples will be presented throughout using both Excel and R to demonstrate implementation choices without requiring participants to complete exercises.
Learning Objectives
Participants will learn how to:
- Explain the fundamental concepts underpinning survival and time-to-event analysis in HTA
- Apply appropriate survival modelling approaches within decision-analytic economic models
- Identify and critically evaluate the limitations of unstructured partitioned survival models
- Extrapolate survival beyond observed data using transparent and defensible principles
- Distinguish between alternative survival and multi-state frameworks and select approaches suited to HTA decision contexts
Course Format
This half-day short course will be delivered through four integrated didactic sessions. The emphasis is on conceptual understanding, modelling structure, and the implications of survival modelling choices for decision making.
Illustrative examples will be presented using both Excel and R to demonstrate key modelling approaches and highlight practical implementation choices.
Participant Requirements
Participants should have prior exposure to decision modelling or economic evaluation (e.g., equivalent to a foundations-level course) and familiarity with basic probability and regression concepts.
No software installation is required. Illustrative examples will be demonstrated using Microsoft Excel and R.