Re-insurance in the Swiss health insurance market: Fit, power, and balance
Introduction
Since the seminal work of Arrow [1], it has been recognized that market failures are inherent in health insurance markets due to the prevalence of information asymmetries. Many countries therefore implement strong regulations including mandatory health insurance to eliminate adverse selection, defined co-payments to reduce moral hazard, and – in case risk rated premiums are not allowed – risk equalization schemes to counteract insurers’ incentives for risk selection (risk equalization is applied in the United States, Switzerland, the Netherlands, Germany, Ireland, and Belgium; see [2], [3], [4], [5], [6], [7], respectively). The latter denotes the incentives for insurers to attract relatively healthy consumers with below-average risk to increase profits. Although risk equalization reduces this incentive, it also reduces incentives for cost containment as savings from reduced utilization might be redistributed among insurers. Put differently, there is a tradeoff between goals of limiting costs and eliminating risk selection [8], [9].
Although the importance of this trade-off is well known, the theoretical and empirical literature on assessing the health insurer incentives embedded in the payment system is rather scarce [9]. In particular, most studies focus on a single feature of the payment system, that is, on risk equalization alone. However, an isolated focus on risk equalzation ignorning other features such as premiums, tax credits, and re-insurance might be misleading. Geruso and McGuire [9] propose three measures called fit, power, and balance to analyze the de facto insurer incentives. While fit measures the incentive to practice risk selection, power originates from contract theory (e.g. [10]) and quantifies to which extent insurers’ savings from reduced utilization are not redistributed through risk equalization. On the other hand, balance assesses differences in power across different services, that is, the incentives to distort the allocation of resources among these services. We apply these measures in the Swiss context to evaluate the current payment system that exhibits risk equalization and community-rated premiums. This is our first contribution to the literature.
An alternative to risk equalization is mandatory re-insurance that covers high expenditures. While risk equalization is often perceived as complicated, re-insurance has been applied for centuries and professionals are very familiar with its concept. In addition, it is important to note that even sophisticated risk equalization formulas do not improve the financial situation of outlier risks from the insurers’ perspective [11]. However, potential improvements of the payment system such as re-insurance and high risk pooling are not frequently implemented, though the underpayment of high expenditure individuals is an important issue. Notable examples are the cost sharing between insurers in the Netherlands [12] and the temporary high risk pooling in Germany. The latter was not found to be effective [13], [14]. Similar evidence is provided by the literature on re-insurance and high cost pooling in the Swiss context [15], [16], [17], [18].
The seemingly poor performance of re-insurance in Switzerland and Germany has two reasons. First, re-insurance and risk equalization has been analyzed seperately (a notable exception in that regard is the analysis by Drösler et al. [19] on re-introducing a high cost pool in Germany). For instance, fit was calculated on all individuals receiving no re-insurance payments. As the fit did not increase in the payment system “with” re-insurance, the researchers concluded that re-insurance does not improve the payment system. Thus, this is related to the point made by Geruso and McGuire [9] and Layton et al. [20] that the entire payment system should by analyzed. Second, the focus was mainly on predictable outlier risks and ex-ante risk selection. According to van Barneveld [12], unpredictable outlier risks might never be victimes of risk selection. However, insurers might alter their services in order to become less attractive for high cost individuals. Such a behavior enables them to select against high risks although the risk is not observed in advance [21]. In addition, insurers might also nudge outlier risks to leave the insurance as soon as the high expenditures are observed. This argument qualifies van Barnefeld's position substantually. Although re-insurance will probably not alter the cost ranking of the high risk individuals, it reduces their outlier costs and makes expected healthcare expenditures more predictable which is important for a risk averse health insurer. Insofar re-insurance is even Rawls compatible as it targets the least privileged insured and improves their situation with respect to the other insured. Therefore, we complement the current Swiss risk equalization scheme by a re-insurance and evaluate the effects of re-insurance on the entire payment system applying fit, power, and balance. This is our second contribution to the literature.
Regarding the current system, we find that the incentives to practice risk selection is rather high though these incentives are weakened by the plannend improvments of the risk equalization scheme. Given the trade-off between risk selection and cost containment, it is not surprising that we find very high incentives for the insurers to contain healthcare costs. In addition, our results suggest that health insurers in Switzerland have only very little incentives to distort the allocation of resources among different services. Turning to re-insurance, we find that the incentives to practice risk selection are strongly reduced. In addition, the incentives to contain costs are decreased but not by much. The evidence regarding the distortion of the resource allocation is similar. Thus, we find that re-insurance should be considered as an extension of the current Swiss risk equalization scheme.
The remainder of this paper is organized as follows. In the next Section, we discuss the measures that are used to grade different payment systems. Section 3 provides some details on the Swiss health insurance market and risk equalization in Switzerland. Section 4 describes our data and the empirical approach. The results are discussed in Section 5 and, finally, Section 6 contains concluding remarks.
Section snippets
Theoretical background and methodology
Suppose we have i = 1, …, N individuals where individual i has healthcare costs xi and the average healthcare cost in the population is . The payment pi for individual i consists of the individual's insurance premium, risk equalization payments, and any other payment to the insurance for that individual. The payment system fit is defined asthat is, fit is similar to an R2 and measures how well the portion of the variance in healthcare costs is explained by the variance
Institutional background
The Swiss healthcare system combines competitive elements with social insurance (for a comprehensive overview, see [22]). Basic health insurance is compulsory for all Swiss residents and provides comprehensive coverage of medical services and pharmaceutical products. Premiums for basic health plans are community-rated based on 43 geographic premium regions. However, basic health insurance plans are offered by approximately 60 private insurance companies. Profits on basic health plans are not
Data
The data are drawn from the records of the CSS insurance within the time period from 2011 to 2012. CSS insurance is the largest Swiss health insurer with roughly 1.2 million enrollees in mandatory health insurance plans. We randomly select 30% of all insured individuals who are enrolled over both years and aged at least 19 years. For each individual, we have information on the risk equalization group (gender, age-group and hospitalization in the previous year), canton of residence, PCG, and
Fit, power, and balance
The first column of Table 1 shows the fit of several payment systems with and without re-insurance. Current risk equalization achieves a fit of roughly 0.15 and improves the simple age-gender based risk equalization by 6.5 percentage points (8th line in Table 1). In addition, the future changes both increase the fit further. The current risk equalization extended with PCGs achieves a fit of 0.21 and binary indicator for previous year drug expenditures (instead of PCGs) performs even better and
Conclusion
Healthcare systems which are based on the principles of managed competition (see [34]) and without (fully) risk rated premiums require risk equalization schemes to mitigate insurers’ incentives to practice risk selection. However, risk equalization can reduce incentives for cost containment and create incentives to distort the allocation of resources among different types of service. We apply three measures proposed by Geruso and McGuire [9] for quantifying these incentives and thus comparing
Acknowledgements and disclosure
For their perceptive and valuable comments, we thank two anonymous referees, Lukas Kauer, Thomas G. McGuire, Maria Trottmann, and participants of the 2nd Swiss Health Economics Workshop and the 15th Meeting of the Risk Adjustment Network. The authors were employees of CSS Insurance Switzerland at the time of study conduct, but CSS Insurance played no role in study design, analysis, preparation of the manuscript, or decision to publish. All remaining errors are our own.
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