Final published version
Licence: CC BY: Creative Commons Attribution 4.0 International License
Research output: Contribution to Journal/Magazine › Journal article › peer-review
Research output: Contribution to Journal/Magazine › Journal article › peer-review
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TY - JOUR
T1 - Health insurance system fragmentation and COVID-19 mortality
T2 - Evidence from Peru
AU - Anaya-Montes, Misael
AU - Gravelle, Hugh
PY - 2024/8/27
Y1 - 2024/8/27
N2 - Peru has a fragmented health insurance system in which most insureds can only access the providers in their insurer’s network. The two largest sub-systems covered about 53% and 30% of the population at the start of the pandemic; however, some individuals have dual insurance and can thereby access both sets of providers. We use data on 24.7 million individuals who belonged to one or both sub-systems to investigate the effect of dual insurance on COVID-19 mortality. We estimate recursive bivariate probit models using the difference in the distance to the nearest hospital in the two insurance sub-systems as Instrumental Variable. The effect of dual insurance was to reduce COVID-19 mortality risk by 0.23% compared with the sample mean risk of 0.54%. This implies that the 133,128 COVID-19 deaths in the sample would have been reduced by 56,418 (95%CI: 34,894, 78,069) if all individuals in the sample had dual insurance.
AB - Peru has a fragmented health insurance system in which most insureds can only access the providers in their insurer’s network. The two largest sub-systems covered about 53% and 30% of the population at the start of the pandemic; however, some individuals have dual insurance and can thereby access both sets of providers. We use data on 24.7 million individuals who belonged to one or both sub-systems to investigate the effect of dual insurance on COVID-19 mortality. We estimate recursive bivariate probit models using the difference in the distance to the nearest hospital in the two insurance sub-systems as Instrumental Variable. The effect of dual insurance was to reduce COVID-19 mortality risk by 0.23% compared with the sample mean risk of 0.54%. This implies that the 133,128 COVID-19 deaths in the sample would have been reduced by 56,418 (95%CI: 34,894, 78,069) if all individuals in the sample had dual insurance.
U2 - 10.1371/journal.pone.0309531
DO - 10.1371/journal.pone.0309531
M3 - Journal article
VL - 19
JO - PLoS One
JF - PLoS One
SN - 1932-6203
IS - 8
M1 - e0309531
ER -