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High-risk pooling for mitigating risk selection incentives in health insurance markets with sophisticated risk equalization: an application based on health survey information.
Withagen-Koster, A A; van Kleef, R C; Eijkenaar, F.
Afiliação
  • Withagen-Koster AA; Erasmus School of Health Policy & Management, Erasmus University Rotterdam, Rotterdam, The Netherlands. koster@eshpm.eur.nl.
  • van Kleef RC; Erasmus School of Health Policy & Management, Erasmus University Rotterdam, Rotterdam, The Netherlands.
  • Eijkenaar F; Erasmus School of Health Policy & Management, Erasmus University Rotterdam, Rotterdam, The Netherlands.
BMC Health Serv Res ; 24(1): 273, 2024 Mar 04.
Article em En | MEDLINE | ID: mdl-38438924
ABSTRACT

BACKGROUND:

Despite 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.

METHODS:

We 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.

RESULTS:

The 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.

CONCLUSION:

Our 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.
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Texto completo: 1 Temas: ECOS / Aspectos_gerais / Estado_mercado_regulacao Bases de dados: MEDLINE Assunto principal: Seguro Saúde / Motivação Limite: Humans Idioma: En Revista: BMC Health Serv Res Assunto da revista: PESQUISA EM SERVICOS DE SAUDE Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Holanda

Texto completo: 1 Temas: ECOS / Aspectos_gerais / Estado_mercado_regulacao Bases de dados: MEDLINE Assunto principal: Seguro Saúde / Motivação Limite: Humans Idioma: En Revista: BMC Health Serv Res Assunto da revista: PESQUISA EM SERVICOS DE SAUDE Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Holanda