Health Economics

Patient-centred care – care that is consistent with the values and preferences of patients – improves the safety, quality, and outcomes of healthcare. Essential to implementing patient-centred care in cancer services is understanding the values and preferences of patients, and the wider community. Economic methods to measure preferences, such as discrete choice experiments, provide a way to quantitatively assess preferences for health and health care services. The team is working on several projects to measure preferences for cancer care, including the use of artificial intelligence in breast cancer screening, using genomic-risk information to tailor cancer screening services, and examining how patients trade off between quality of life and survival when choosing cancer treatments.

When someone stops working because of cancer this can have a big impact on the individual and their family. However, it also represents a loss to the employer and to the broader economy, known as lost productivity. Economic methods to measure and value this loss of productivity provide health care decision makers with an additional perspective on the burden of disease, and can aid priority setting for cancer control activities. The team is working on several projects measuring and valuing the loss of productivity related to cancer, including in Australia, Brazil and Europe.

Economic evaluation is a tool to guide how we allocate resources in the healthcare system. It involves comparing different treatments or services in terms of both their costs and their benefits. There are different types of economic evaluations, including cost effectiveness analyses, cost benefit analysis and cost utility analysis, all of which provide an indication of whether a proposed intervention represents good value for money. The team is working on several economic evaluation projects, including evaluating the cost-effectiveness and cost-utility of supporting clinicians to provide smoking cessation support to pregnant women, a cost-effectiveness analysis of the use of artificial intelligence in breast cancer screening, the cost-effectiveness of the iConquerFear intervention to address fear of cancer recurrence in cancer survivors, and the costs of providing rural health clinics for head and neck cancer patients in NSW.

As well as applying economic methods in projects examining patient preferences, lost productivity and economic evaluation, the team is actively involved in a range of methodological research projects. This includes work to improve equity in how productivity losses are estimated, improving the validity of discrete choice experiments as a way to measure patient preferences, and improving the way carer burden is measured for inclusion in economic evaluations.