Estimating Attribute-Specific Willingness-to-Pay Values from a Health Care Contingent Valuation Study: A Best-Worst Choice Approach.

BACKGROUND: Willingness-to-pay (WTP) studies frequently use a contingent valuation (CV) method to determine the economic value of a good or service. However, a typical CV study is able to estimate the WTP for a good as a whole, but provides no information about the marginal WTP for different attributes of a good. OBJECTIVE: The aim was to estimate marginal WTP for different attributes of a CV scenario. METHODS: By using the data from an additional best-worst choice (BWC) experiment, we disaggregated the holistic WTP values for dental care, estimated using the CV method, into attribute-specific WTP values. The study was conducted at the School of Dental Medicine, University of Zagreb, Croatia. Dental school patients were surveyed from March 2016 to January 2017, and their WTP for dental care was estimated using either a CV survey (n = 242), which also included a BWC task, or a discrete choice experiment (DCE) survey (n = 275). RESULTS: The largest marginal welfare estimate (€13.5) was obtained for the improvement in treatment explanation, followed by the improvements in staff behavior (€8.1) and waiting time in the office (€7.2), and by the changes in dental care provider (€3.4). These estimates were generally highly similar to the traditional marginal WTP estimates obtained with a traditional multi-profile DCE, after adjusting DCE estimates for non-attendance to the cost attribute. CONCLUSION: Our BWC-CV framework may serve as a valuable alternative for estimating marginal WTP values for health care attributes when the choice behavior of respondents raises concerns for the validity of DCE estimates.

Estimating willingness-to-pay for health care: A discrete choice experiment accounting for non-attendance to the cost attribute.

RATIONALE, AIMS, AND OBJECTIVES: The literature suggests that discrete choice experiments (DCEs) are a preferable method for estimating willingness-to-pay (WTP) values, as they may avoid some biases often observed in contingent valuation surveys, such as protest and strategic behaviour. However, the choice studies have demonstrated that attribute non-attendance may be a serious issue that leads to biased WTP estimates. METHOD: A DCE was used to estimate patients' WTP for dental care at the dental school clinic. The endogenous attribute attendance (EAA) model was used to estimate WTP for dental care attributes, while accounting for non-attendance to the cost attribute. RESULTS: The EAA model revealed that almost every second respondent had ignored the cost attribute when making choices, indicating that patients were very sensitive to other characteristics of dental care. Dental care providers should pay particular attention to providing a detailed explanation of treatment to their patients, as this was the most valued attribute of dental care. The welfare estimates from the EAA model, which accounted for non-attendance to the cost attribute, were more than two times lower than welfare estimates from a traditional multinomial logit model and mixed logit model estimated in WTP space. CONCLUSIONS: The findings raise concerns for derived WTP estimates in DCE studies that did not consider non-attendance to the cost attribute during the estimation process. Non-attendance to the cost attribute overestimates WTP values, even if being motivated by the true preferences of respondents.

Valuing the delivery of dental care: Heterogeneity in patients' preferences and willingness-to-pay for dental care attributes.

OBJECTIVES: To examine the amount of heterogeneity in patients' preferences for dental care, what factors affect their preferences, and how much they would be willing to pay for improvement in specific dental care attributes. METHODS: A discrete choice experiment (DCE) was used to elicit patients' preferences. Three alternative dental care services that differed in the type of care provider, treatment explanation, dental staff behavior, waiting time and treatment cost were described to patients. Patients (n=265) were asked to choose their preferred alternative. The study was conducted at a public dental clinic of the School of Dental Medicine, University of Zagreb. Mixed logit and latent class models were used for analysis. RESULTS: On average, the patients would be willing to pay €45 for getting a detailed explanation of treatment over no explanation. This was the most valued attribute of dental care, followed by dental staff behavior with marginal willingness-to-pay (WTP) of €28. Dental care provided by the faculty members and private dental care were valued similarly, while student-provided care was valued €23 less. Patients also disliked longer waiting time in the office, but this was the least important attribute. Four classes of patients with distinct preferences for dental care were identified. Older and/or more educated patients tended to give relatively less importance to treatment explanation. Higher education was also associated with a higher propensity to substitute faculty dental care with the private care providers. CONCLUSIONS: Large heterogeneity in patients' preferences was detected. Understanding their preferences may improve the delivery of dental care. CLINICAL SIGNIFICANCE: Dental care providers should pay particular attention to providing a detailed treatment explanation to their patients. Dental care for older and/or more educated patients should be more attentive to interpersonal characteristics. Faculty dental care provided by faculty members could be price competitive to private care, and student-provided care more affordable.