Dataset Information

Risk equalization in competitive health insurance markets: Identifying healthy individuals on the basis of multiple-year low spending.

ABSTRACT:

Objective

To study the extent to which risk equalization (RE) in competitive health insurance markets can be improved by including an indicator for being healthy.

Study setting/data sources

This study is conducted in the context of the Dutch individual health insurance market. Administrative data on spending and risk characteristics (2011-2014) for the entire population (N = 16.6 m) as well as health survey data from a large sample (N = 387 k) are used.

Study design

The indicator for being healthy is low spending in three consecutive prior years. "Low spending" is defined in three ways: belonging to the bottom 60%, 70%, or 80% of the annual spending distribution. Versions of the Dutch RE model 2017 with and without the indicator are compared on individual-level payment fit and, using the survey data, group-level payment fit.

Principal findings

All three alternative models outperform the Dutch RE model 2017. However, significant unpriced risk heterogeneity remains. Compared with the 60% threshold, the 80% threshold comes with a larger improvement in fit but identifies a less selective group.

Conclusions

The performance of the RE model can be improved by adding an indicator for being healthy based on multiple-year low spending. However, risk-selection potential remains, warranting high priority to further improvement of RE.

SUBMITTER: Eijkenaar F

PROVIDER: S-EPMC6407341 | biostudies-literature | 2019 Apr

REPOSITORIES: biostudies-literature

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Publications

Risk equalization in competitive health insurance markets: Identifying healthy individuals on the basis of multiple-year low spending.

Eijkenaar Frank F van Vliet René C J A RCJA van Kleef Richard C RC

Health services research 20181016 2

<h4>Objective</h4>To study the extent to which risk equalization (RE) in competitive health insurance markets can be improved by including an indicator for being healthy.<h4>Study setting/data sources</h4>This study is conducted in the context of the Dutch individual health insurance market. Administrative data on spending and risk characteristics (2011-2014) for the entire population (N = 16.6 m) as well as health survey data from a large sample (N = 387 k) are used.<h4>Study design</h4>The ind ...[more]

PMID: 30328096

Similar Datasets

Project description:BackgroundDespite sophisticated risk equalization, insurers in regulated health insurance markets still face incentives to attract healthy people and avoid the chronically ill because of predictable differences in profitability between these groups. The traditional approach to mitigate such incentives for risk selection is to improve the risk-equalization model by adding or refining risk adjusters. However, not all potential risk adjusters are appropriate. One example are risk adjusters based on health survey information. Despite its predictiveness of future healthcare spending, such information is generally considered inappropriate for risk equalization, due to feasibility challenges and a potential lack of representativeness.MethodsWe study the effects of high-risk pooling (HRP) as a strategy for mitigating risk selection incentives in the presence of sophisticated- though imperfect- risk equalization. We simulate a HRP modality in which insurers can ex-ante assign predictably unprofitable individuals to a 'high risk pool' using information from a health survey. We evaluate the effect of five alternative pool sizes based on predicted residual spending post risk equalization on insurers' incentives for risk selection and cost control, and compare this to the situation without HRP.ResultsThe results show that HRP based on health survey information can substantially reduce risk selection incentives. For example, eliminating the undercompensation for the top-1% with the highest predicted residual spending reduces selection incentives against the total group with a chronic disease (60% of the population) by approximately 25%. Overall, the selection incentives gradually decrease with a larger pool size. The largest marginal reduction is found moving from no high-risk pool to HRP for the top 1% individuals with the highest predicted residual spending.ConclusionOur main conclusion is that HRP has the potential to considerably reduce remaining risk selection incentives at the expense of a relatively small reduction of incentives for cost control. The extent to which this can be achieved, however, depends on the design of the high-risk pool.

Dataset Information

Risk equalization in competitive health insurance markets: Identifying healthy individuals on the basis of multiple-year low spending.

Objective

Study setting/data sources

Study design

Principal findings

Conclusions

Publications

Risk equalization in competitive health insurance markets: Identifying healthy individuals on the basis of multiple-year low spending.

Similar Datasets

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