Advancing economic evaluation methods for better medical decision making through real-world, longitudinal data

Abstract

Health economic evaluation is a fundamental component in helping inform health care providers and policy makers in making decisions on priorities in health care. This is particularly relevant in today’s tight budgetary climate and in response to continued calls for sustainable health care systems. Economic evaluation evidence has influenced and contributed to many areas of health policy making, at all levels of the health care system – from shaping guidelines that guide clinical care to informing decision for subsidy of pharmaceuticals and medical services. For these evaluations to be useful to decisions makers, they need to provide useful and reliable information and to achieve this, methodological guidelines should be followed, and robust evidence of effectiveness and cost is paramount. With recent advances in information technology, data and statistical methods and implementation of electronic health records, health decision makers are increasingly seeking real-world, generalisable evidences to complement and support policy and clinical decisions.

This thesis aims to demonstrate the usefulness and practicality of applying real-world longitudinal data in health economics research and applications. It features six individual health economics studies which explore longitudinal data and show their value and contribution towards advancing economic evaluation methodologies and better decision making. Each of the studies answer specific research questions and contribute to the research literature through methodological research to improve consistency in extrapolating costs, utility inputs and modelling long-term outcomes, generating robust evidence for resource allocation decisions, promoting a better understanding of real-world heterogeneity and approaches to optimise patient outcomes. Collectively, these studies highlight important variations in the cost and outcomes of health care delivery in real-world settings, provide useful insights into the implications of such variations and demonstration of translating research findings to implementation.