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Implications of family risk pooling for individual health insurance markets

Overview of attention for article published in Health Services and Outcomes Research Methodology, May 2017
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  • Among the highest-scoring outputs from this source (#37 of 121)
  • Good Attention Score compared to outputs of the same age (68th percentile)

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Title
Implications of family risk pooling for individual health insurance markets
Published in
Health Services and Outcomes Research Methodology, May 2017
DOI 10.1007/s10742-017-0170-3
Pubmed ID
Authors

Anna D. Sinaiko, Timothy J. Layton, Sherri Rose, Thomas G. McGuire

Abstract

While family purchase of health insurance may benefit insurance markets by pooling individual risk into family groups, the correlation across illness types in families could exacerbate adverse selection. We analyze the impact of family pooling on risk for health insurers to inform policy about family-level insurance plans. Using data on 8,927,918 enrollees in fee-for-service commercial health plans in the 2013 Truven MarketScan database, we compare the distribution of annual individual health spending across four pooling scenarios: (1) "Individual" where there is no pooling into families; (2) "real families" where costs are pooled within families; (3) "random groups" where costs are pooled within randomly generated small groups that mimic families in group size; and (4) "the Sims" where costs are pooled within random small groups which match families in demographics and size. These four simulations allow us to identify the separate contributions of group size, group composition, and family affinity in family risk pooling. Variation in individual spending under family pooling is very similar to that within "simulated families" and to that within random groups, and substantially lower than when there is no family pooling and individuals choose independently (standard deviation $12,526 vs $11,919, $12,521 and $17,890 respectively). Within-family correlations in health status and utilization do not "undo" the gains from family pooling of risks. Family pooling can mitigate selection and improve the functioning of health insurance markets.

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The data shown below were collected from the profiles of 10 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 9 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 9 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 2 22%
Researcher 2 22%
Student > Ph. D. Student 1 11%
Professor > Associate Professor 1 11%
Unknown 3 33%
Readers by discipline Count As %
Medicine and Dentistry 2 22%
Nursing and Health Professions 1 11%
Business, Management and Accounting 1 11%
Economics, Econometrics and Finance 1 11%
Computer Science 1 11%
Other 0 0%
Unknown 3 33%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 5. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 20 August 2018.
All research outputs
#6,598,528
of 24,393,299 outputs
Outputs from Health Services and Outcomes Research Methodology
#37
of 121 outputs
Outputs of similar age
#98,533
of 317,227 outputs
Outputs of similar age from Health Services and Outcomes Research Methodology
#1
of 1 outputs
Altmetric has tracked 24,393,299 research outputs across all sources so far. This one has received more attention than most of these and is in the 72nd percentile.
So far Altmetric has tracked 121 research outputs from this source. They receive a mean Attention Score of 4.9. This one has gotten more attention than average, scoring higher than 70% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 317,227 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 68% of its contemporaries.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them