Erasmus University Rotterdam Patient choice when prices don’t matter What do time-elasticities tell about hospitals’ market power? Academy Health Annual Research Meeting Saturday, June 7, 2008 Washington, DC Marco Varkevisser (Erasmus University Rotterdam) Health Economics Interest Group Meeting 1 Contact:

Erasmus University Rotterdam Outline Background Model Empirical specification Data Estimation results Substitutability of Dutch hospitals? Concluding remarks 2

Erasmus University Rotterdam Background Health system reform in The Netherlands –Introduction of managed competition Van de Ven and Schut (2008, HA) –How to assess Dutch hospitals’ market power? Prices for most hospital services are still fixed Out-of-pocket payments are absent Patients do not yet face restricted provider networks –Varkevisser, Capps and Schut (2008, HEPL): “As a result, in the current context, the time-elasticity approach seems to be the appropriate approach to defining hospital markets in The Netherlands.” 3

Erasmus University Rotterdam The model Based on standard patient utility function –Following previous studies for US hospital choice –Utility patient i visiting hospital j is given by –Travel time (t ij ) and hospital attributes (H j ) as main determinants of patient hospital choice Prices are not included since these are irrelevant –Interaction terms to capture patient heterogeneity 4

Erasmus University Rotterdam Empirical specification Conditional logit model (McFadden, 1974): –Travel time (t ij ) –Hospital attributes (H j ) Type, size, reputation, and waiting time –Patient characteristics (P i ) Gender, age (adult vs. non-adult), and social status Probability that patient i selects hospital j 5

Erasmus University Rotterdam Data Individual patient level data from large Dutch health insurer –Non-emergency first outpatient hospital visits for neurosurgery in 2003 –Patients travelling > 60 minutes are excluded Patient i’s choice set = all hospitals ≤ 60 minutes On average, the choice set includes 26 hospitals –Resulting study sample contains 5,389 visits Mean travel time  19 minutes For 95% of the patients travel time ≤ 45 minutes 6

Erasmus University Rotterdam Estimation results: summary Estimation results –Hausman-McFadden test: IIA assumption seems to hold here –Brief summary of estimated parameters Coefficient for travel time is negative and significant Patients are less likely to visit academic medical centre Overall reputation and waiting time affect choice Several patient attributes seem to affect hospital choice –Model predicts patients’ actual choices fairly well 43% visited hospital with the highest probability 7

Erasmus University Rotterdam Estimation results: detailed coefficients 8

Erasmus University Rotterdam Substitutability of Dutch hospitals? Time-elasticities as an attempt to indirectly estimate hospitals’ demand elasticities –Details: Capps et al. (2001, NBER) –Estimation of hospital j’s isolated time-elasticity 1. Assign all patients to hospital with highest probability 2. Artificially increase travel time to hospital j by 10% 3. Predict hospital j’s “new” market share 4. Divide ∆% market share by ∆% travel time 9

Erasmus University Rotterdam Dutch hospitals’ isolated time-elasticities 10

Erasmus University Rotterdam A closer look at hospitals’ substitutability… 11

Erasmus University Rotterdam A closer look at hospitals’ substitutability… 12

Erasmus University Rotterdam Sensitivity test: Monte Carlo simulation 13

Erasmus University Rotterdam Concluding remarks From our simulations it follows that: –Point estimates of Dutch hospitals’ isolated time- elasticities range from -0.6 to -5.6 –Estimated time-elasticities are overall fairly high, but some hospitals may have market power –Overall, estimated time-elasticities are robust Time-elasticity approach has the potential to become a useful instrument for assessing Dutch hospitals’ substitutability –To health insurers as well as antitrust agencies 14