WORK PACKAGE 2

Development and application of a tool to combine and use RCT and observational/registry data in economic evaluation

Objectives
  • To produce guidance on extrapolation of Randomised Clinical Trial (RCT) results using Real World Data (RWD), either observational or registry data, to allow cost-effectiveness analysis (CEA) of new health care technologies to be undertaken

  • To develop a new, publicly accessible platform to allow direct modelling of CEA by Health Technology Assessment (HTA) agencies

Methodology
  • Extrapolation of health benefits by using different sets of data

  • Assessment and evaluation of existing ways of extrapolation of treatment costs

  • Creation of platform based on Discretely Integrated Condition Event (DICE) simulation, to model health benefits and treatment costs during CEA modelling

  • Pilot using the DICE model with a published HTA guideline and provision of recommendations for modelling the consequences of guidelines, both in general and when using DICE simulation

Outcomes
  • A review of methods used to extrapolate RCT outcomes using Real World Data

  • Guidance relating to the matching of data from RCTs and Observational or Registry data

  • An analysis of the manner in which such matched data can be used for estimation of long-term outcomes

  • Validation of the DICE modelling technique against existing methods

  • Speeding up execution of the DICE Simulation macro

  • Training modules and manuals for HTA staff, reviewers and modellers

 
Outputs
  • DICE platform based on Discretely Integrated Condition Event simulation to model health benefits and treatment costs during CEA modelling. 

Publications about DICE
  • Validation of a DICE simulation against a Discrete Event Simulation implemented entirely in code (link)

  • Discretely Integrated Condition Event (DICE) simulation for pharmacoeconomics (link)

  • Leveraging DICE (Discretely-Integrated Condition Event) simulation to simplify the design and implementation of hybrid models (link)

  • Adding events to a Markov Model using DICE simulation (link)

  • Cooking up a transparent model following a DICE recipe (link)

  • Economic evaluation of sequences of biological treatments for patients with moderate-to-severe Rheumatoid Arthritis and inadequate response or intolerance to Methotrexate in France (link)

  • Trusting the results of model-based economic analyses: Is there a pragmatic validation solution? (link)

  • Modeling using discrete event simulation: a report of the ISPOR-SMDM Modeling Good Research Practices Task Force–4 (link)

  • Improving transparency in decision models: Current issues and potential solutions (link)

  • Pharmacoeconomic analyses using discrete event simulation (link)

  • Advantages and disadvantages of discrete-event simulation for health economic analyses (link)

  • Discrete event simulation: the preferred technique for health economic evaluations? (link)

  • Caro JJ, Möller J. Chapter 10. DICE Simulation: A Unifying Modeling Approach for Pharmacoeonomics. Pharmacoeconomics From Theory to Practice. Arnold RJ (ed). CRC Press, Oxford, UK and Boca Raton, FL. 2nd edition 2020.

Lead
London School of Economics and Political Science

Principal Investigators

Alistair McGuire

Jaime Caro