Using discrete choice experiments to understand preferences in health care.

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.

Redistribution through social health insurance: evidence on citizen preferences.

The extent of social health insurance (SHI) and supplementary private insurance is frequently analyzed in public choice. Most of these analyses build on the model developed by Gouveia (1997), who defines the extent of SHI as consequence of a choice by self-interested voters. In this model, an indicator reflecting individuals' relative income position and relative risk of falling ill determines the voting decision. Up to now, no empirical evidence for this key assumption has been available. We test the effect of this indicator on individuals' preferences for the extent of SHI in a setting with mandatory SHI that can be supplemented by private insurance. The data is based on a DCE conducted in the field with a representative sample of 1538 German citizens in 2012. Conditional logit and latent class models are used to analyze preference heterogeneity. Our findings strongly support the assumptions of the models. Individuals likely to benefit from public coverage show a positive marginal willingness to pay (MWTP) for both a shift away from other beneficiary groups toward the sick and an expansion of publicly financed resources, and the expected net payers have a negative MWTP and prefer lower levels of public coverage.

Attitudes of Germans towards distributive issues in the German health system.

Social health care systems are inevitably confronted with the scarcity of resources and the resulting distributional challenges. Since prioritization implies distributional effects, decisions regarding respective rules should take citizens' preferences into account. In this study we concentrate on two distributive issues in the German health system: firstly, we analyze the acceptance of prioritizing decisions concerning the treatment of certain patient groups, in this case patients who all need a heart operation. We focus on the patient criteria smoking behavior, age and whether the patient has or does not have young children. Secondly, we investigate Germans' opinions towards income-dependent health services. The results reveal the strong effects of individuals' attitudes regarding general aspects of the health system on priorities, e.g. that individuals with an unhealthy lifestyle should not be prioritized. In addition, experience of limited access to health services is found to have a strong influence on citizens' attitudes, too. Finally, decisions on different prioritization criteria are found to be not independent.

Mutual altruism: evidence from Alzheimer patients and their spouse caregivers.

PURPOSE: Preferences of both Alzheimer patients and their spouse caregivers are related to a willingness-to-pay (WTP) measure which is used to test for the presence of mutual (rather than conventional unilateral) altruism. METHODOLOGY: Contingent valuation experiments were conducted in 2000-2002, involving 126 Alzheimer patients and their caregiving spouses living in the Zurich metropolitan area (Switzerland). WTP values for three hypothetical treatments of the demented patient were elicited. The treatment Stabilization prevents the worsening of the disease, bringing dementia to a standstill. Cure restores patient health to its original level. In No burden, dementia takes its normal course while caregiver's burden is reduced to its level before the disease. FINDINGS: The three different types of therapies are reflected in different WTP values of both caregivers and patients, suggesting that moderate levels of Alzheimer's disease still permit clear expression of preference. According to the WTP values found, patients do not rank Cure higher than No burden, implying that their preferences are entirely altruistic. Caregiving spouses rank Cure before Burden, reflecting less than perfect altruism which accounts for some 40 percent of their total WTP. Still, this constitutes evidence of mutual altruism. VALUE: The evidence suggests that WTP values reflect individuals' preferences even in Alzheimer patients. The estimates suggest that an economically successful treatment should provide relief to caregivers, with its curative benefits being of secondary importance.

Reporting heterogeneity in self-assessed health among elderly Europeans.

INTRODUCTION: Self-assessed health (SAH) is a frequently used measure of individuals' health status. It is also prone to reporting heterogeneity. To control for reporting heterogeneity objective measures of true health need to be included in an analysis. The topic becomes even more complex for cross-country comparisons, as many key variables tend to vary strongly across countries, influenced by cultural and institutional differences. This study aims at exploring the key drivers for reporting heterogeneity in SAH in an international context. To this end, country specific effects are accounted for and the objective health measure is concretized, distinguishing effects of mental and physical health conditions. METHODS: We use panel data from the SHARE-project which provides a rich dataset on the elderly European population. To obtain distinct indicators for physical and mental health conditions two indices are constructed. Finally, to identify potential reporting heterogeneity in SAH a generalized ordered probit model is estimated. RESULTS: We find evidence that in addition to health behaviour, health care utilization, mental and physical health condition as well as country characteristics affect reporting behaviour. We conclude that observed and unobserved heterogeneity play an important role when analysing SAH and have to be taken into account.

I feel good! Gender differences and reporting heterogeneity in self-assessed health.

For empirical analysis and policy-oriented recommendations, the precise measurement of individual health or well-being is essential. The difficulty is that the answer may depend on individual reporting behaviour. Moreover, if an individual's health perception varies with certain attitudes of the respondent, reporting heterogeneity may lead to index or cut-point shifts of the health distribution, causing estimation problems. An index shift is a parallel shift in the thresholds of the underlying distribution of health categories. In contrast, a cut-point shift means that the relative position of the thresholds changes, implying different response behaviour. Our paper aims to detect how socioeconomic determinants and health experiences influence the individual valuation of health. We analyse the reporting behaviour of individuals on their self-assessed health status, a five-point categorical variable. Using German panel data, we control for observed heterogeneity in the categorical health variable as well as unobserved individual heterogeneity in the panel estimation. In the empirical analysis, we find strong evidence for cut-point shifts. Our estimation results show different impacts of socioeconomic and health-related variables on the five categories of self-assessed health. Moreover, the answering behaviour varies between female and male respondents, pointing to gender-specific perception and assessment of health. Hence, in case of reporting heterogeneity, using self-assessed measures in empirical studies may be misleading and the information needs to be handled with care.