Health Decision Sciences

Principal Investigator: Prof. dr. Pieter H.M. van Baal (vanbaal@eshpm.eur.nl)

Traditionally, threshold levels of cost-effectiveness have been derived from willingness-to-pay studies, indicating the consumption value of health (v-thresholds). However, it has been argued that v-thresholds need to be supplemented by so-called k-thresholds, which are based on the marginal returns to health care. The objectives of thesis written on this theme is to estimate k-thresholds for various disease categories and/or health care providers.

Relevant literature:

van Baal, P., Perry‐Duxbury, M., Bakx, P., Versteegh, M., van Doorslaer, E., & Brouwer, W. (2019). A cost‐effectiveness threshold based on the marginal returns of cardiovascular hospital spending. Health economics, 28(1), 87-100.

Brouwer, W., van Baal, P., van Exel, J., & Versteegh, M. (2019). When is it too expensive? Cost-effectiveness thresholds and health care decision-making.

Principal Investigator: Prof. dr. Pieter H.M. van Baal (vanbaal@eshpm.eur.nl)

In most countries, non-communicable diseases have taken over infectious diseases as the most important causes of death. Many non-communicable diseases which were previously lethal diseases have become chronic, and this has changed the healthcare landscape in terms of treatment and prevention options. Currently, a large part of health care spending is targeted at curing and caring for the elderly, who have multiple chronic diseases. In order to make efficient use of scarce health care resource one ideally needs to compare the cost effectiveness of different interventions aiming to treat and prevent chronic diseases. To assess the cost effectiveness of such interventions, simulation models are used that integrate information from various data sources. At Erasmus School of Health Policy and Management there is room for several research master students who would like to work on modelling the cost-effectiveness of the prevention and treatment of chronic diseases such as cancer, cardiovascular disease, COPD and diabetes.

Relevant literature:

Briggs, Andrew, and Mark Sculpher. “An introduction to Markov modelling for economic evaluation.” Pharmacoeconomics 13.4 (1998): 397-409.

van Baal, P., & Boshuizen, H. (2019). Modeling chronic diseases in relation to risk factors. In Oxford Research Encyclopedia of Economics and Finance.

Prof. dr. Myriam G.M. Hunink

This program focuses on the assessment of medical imaging technology, both diagnostic imaging and minimal invasive (image-guided) therapies. The clinical problems studied are mainly related to cardiovascular disease (CVD) and include imaging for suspected coronary artery disease, imaging of carotid artery disease, imaging and treatment of peripheral arterial disease, and screening of asymptomatic individuals to identify and treat those with high CVD risk.

Other areas of research are identifying the best management strategy in patients with incidental findings on imaging studies (performed clinically or as part of population-based studies) and the choice of image-guided therapy vs surgery vs conservative therapy (for example, for intra-cerebral aneurysms). The studies performed include systematic reviews and meta-analyses, prediction models, decision modeling, randomized controlled trials, and cost-effectiveness analyses. The goal is to assess the added value of imaging, to determine the appropriate indications for specific imaging technologies, to estimate prognosis on the basis of imaging findings and to define the best treatment based on the imaging findings.