Assessing the Impact of Developments in Genetic Testing on Insurers' Risk Exposure.

Genetics Health Insurance Health Screening Science, Technology, and Innovation Policy United Kingdom

Journal

Rand health quarterly
ISSN: 2162-8254
Titre abrégé: Rand Health Q
Pays: United States
ID NLM: 101622976

Informations de publication

Date de publication:
Aug 2022
Historique:
entrez: 14 10 2022
pubmed: 15 10 2022
medline: 15 10 2022
Statut: epublish

Résumé

Predictive genetic testing provides individuals with information about their future risk of developing health conditions. Theoretically, predictive genetic tests could have positive or negative impacts on the insurance industry. If genetic test results stimulate actions to reduce health risks, they may reduce costs to insurers. If disclosed to insurers, such information may allow them to better understand individual- and population-level risks and make insurance more affordable. However, if individuals who know they are at high genetic risk of becoming ill or dying are more likely to apply for insurance than those not at high risk, this may lead to an unanticipated increase in claims. It may be exacerbated if people at low genetic risk are less likely to apply for insurance compared to the general population. If this happened on a large scale it could make the insurance market unsustainable. Determining whether a genetic test could affect the insurance industry is complex and needs to be evaluated on a per-test basis. The Cambridge Centre for Health Services Research, a collaboration between RAND Europe and the University of Cambridge, developed a framework for evaluating the potential impacts on the UK insurance industry arising from predictive genetic tests. It considers the characteristics of genetic tests and behavioural aspects that influence their uptake. It is intended to provide a transparent approach for evaluating whether a specific condition for which a test is available could impact the insurance industry, currently or in the future, and understanding the key factors that influence this.

Identifiants

pubmed: 36237999
pmc: PMC9519094

Types de publication

Journal Article

Langues

eng

Pagination

5

Informations de copyright

Copyright © 2022 RAND Corporation.

Références

Public Underst Sci. 2020 Oct;29(7):702-717
pubmed: 32664786

Auteurs

Classifications MeSH