Health Care Provision and Patient Mobility

Pfarr C, Schmid A, Schneider U, Christian Pfarr, Andreas Schmid, Udo Schneider, Pfarr, Christian, Schmid, Andreas, Schneider, Udo

Whenever processes are reconfigured or new products are designed the needs and preferences of patients and consumers have to be considered. Although at times neglected, this becomes more and more relevant in health care settings: Which modes of health care delivery will be accepted? What are the patients' priorities and what is the willingness to pay? To which degree are patients mobile and for which kind of services are they willing to travel? Preferences, however, are difficult to measure, as they are latent constructs. This becomes even more difficult, when no past choices can be analyzed either as the service or the product is yet to be developed or as in the past there has not been free choice for patients. In such cases, preferences cannot be surveyed directly. Asking individuals openly for their attitudes towards certain services and products, the results are likely biased as individuals are not confronted with budget constraints and trade-offs. For this reason, discrete choice experiments (DCEs) are frequently used to elicit patient preferences. This approach confronts patients with hypothetical scenarios of which only one can be chosen. Over the past few years, this tool to reveal patients' preferences for health care has become very popular in health economics. This contribution aims at introducing the principles of DCEs, highlighting the underlying theory and giving practical guidance for conducting a discrete choice experiment in health economics. Thereby we focus on three major fields of patient demand: designing health insurance, assessing patient utility of new pharmaceuticals and analyzing provider choice. By having a closer look at selected international studies, we discuss the application of this technique for the analysis of the supply and the demand of health care as well as the implications for assessing patient mobility across different health care systems.