Systematic evaluation, replication and validation of structural health economic modelling approaches: Lessons learned in the field of obesity

Björn Schwander

Research output: ThesisDoctoral ThesisExternal prepared

181 Downloads (Pure)

Abstract

According to the World Health Organization, overweight and obesity are major risk factors for a number of chronic diseases, including cardiovascular diseases such as heart disease and stroke, which are the leading causes of death worldwide. This dissertation evaluates, replicates and validates the current structural modelling landscape in obesity, with an emphasis on commonly applied obesity-associated event simulation approaches. It aims to increase trust and confidence in the selection and interpretation of results related to specific methodological approaches commonly used as basis for health economic models in obesity. This research was able to identify some important aspects related to the health economic modelling methodology in general, and key aspects specifically related to the field of obesity. Besides highlighting and investigating the aspects related to research integrity of published health economic models, our research formed a basis for evaluating the strengths and weaknesses of different structural event simulation approaches. Furthermore, we defined valuable future areas of research to further enhance trust and confidence in health economic modelling, especially in the field of obesity.
Original languageEnglish
QualificationDoctor of Philosophy
Awarding Institution
  • Maastricht University
Supervisors/Advisors
  • Evers, Silvia, Supervisor
  • Hiligsmann, Mickaël, Supervisor
  • Nuijten, Mark, Co-Supervisor, External person
Award date6 Mar 2023
Place of PublicationMaastricht
Publisher
Print ISBNs9789464196702
DOIs
Publication statusPublished - 2023

Keywords

  • Health economics
  • obesity
  • modelling
  • validation

Fingerprint

Dive into the research topics of 'Systematic evaluation, replication and validation of structural health economic modelling approaches: Lessons learned in the field of obesity'. Together they form a unique fingerprint.

Cite this