A structural microsimulation model for demand-side cost-sharing in healthcare.

Demand-side cost-sharing reduces moral hazard in healthcare but increases exposure to out-of-pocket expenditure. We introduce a structural microsimulation model to evaluate both total and out-of-pocket expenditure for different cost-sharing schemes. We use a Bayesian mixture model to capture the healthcare expenditure distributions across different age-gender categories. We estimate the model using Dutch data and simulate outcomes for a number of policies. The model suggests that for a deductible of 300 euros shifting the starting point of the deductible away from zero to 400 euros leads to an average 4% reduction in healthcare expenditure and 47% lower out-of-pocket payments.

Minimum generosity levels in a competitive health insurance market.

An important condition for optimal health insurance is that the level of health care coverage is inversely related to the elasticity of demand. We show that this condition is not satisfied for voluntary deductibles in the Netherlands, which are optional deductibles on top of the mandatory deductible introduced by the Dutch government. We find that low-risk types, that mainly choose voluntary deductibles, have a lower elasticity of demand than high-risk types. Moreover, we show that voluntary deductibles introduce equity problems as it results in non-trivial cross subsidies from high-risk to low-risk types. Capping the level of voluntary deductibles (imposing minimum generosity) is likely to be welfare enhancing in the Netherlands.

Payment schemes and treatment responses after a demand shock in mental health care.

We study whether two groups of mental health care providers-each paid according to a different payment scheme-adjusted the duration of their patients' treatments after they faced an exogenous 20% drop in the number of patients. For the first group of providers, self-employed providers, we find that they did not increase treatment duration to recoup their income loss. Treatment duration thresholds in the stepwise fee-for-service payment function seem to have prevented these providers to treat patients longer. For the second group of providers, large mental health care institutions who were subject to a budget constraint, we find an average increase in treatment duration of 8%. Prior rationing combined with professional uncertainty can explain this increase. We find suggestive evidence for overtreatment of patients as the longer treatments did not result in better patient outcomes, i.e. better General Assessment of Functioning scores.

Causes of regional variation in Dutch healthcare expenditures: Evidence from movers.

We assess the relative importance of demand and supply factors as determinants of regional variation in healthcare expenditures in the Netherlands. Our empirical approach follows individuals who migrate between regions. We use individual data on annual healthcare expenditures for the entire Dutch population between the years 2006 and 2013. Regional variation in healthcare expenditures is mostly driven by demand factors, with an estimated share of around 70%. The relative importance of different causes varies with the groups of regions being compared.

Unintended effects of reimbursement schedules in mental health care.

We evaluate the introduction of a reimbursement schedule for self-employed mental health care providers in the Netherlands in 2008. The reimbursement schedule follows a discontinuous discrete step function-once the provider has passed a treatment duration threshold the fee is flat until a next threshold is reached. We use administrative mental health care data of the total Dutch population from 2008 to 2010. We find an "efficiency" effect: on the flat part of the fee schedule providers reduce treatment duration by 2 to 7% compared to a control group. However, we also find unintended effects: providers treat patients longer to reach a next threshold and obtain a higher fee. The data shows gaps and bunches in the distribution function of treatment durations, just before and after a threshold. About 11 to 13% of treatments are shifted over a next threshold, resulting in a cost increase of approximately 7 to 9%.