Addressing care-seeking as well as insurance-seeking selection biases in estimating the impact of health insurance on out-of-pocket expenditure

Shehzad Ali; Richard Andrew Cookson; Mark Alan Dusheiko

doi:10.1016/j.socscimed.2016.11.005

Addressing care-seeking as well as insurance-seeking selection biases in estimating the impact of health insurance on out-of-pocket expenditure

Shehzad Ali, Richard Andrew Cookson, Mark Alan Dusheiko

Research output: Contribution to journal › Article › peer-review

Abstract

Health Insurance (HI) programmes in low-income countries aim to reduce the burden of individual out-of-pocket (OOP) health care expenditure. However, if the decisions to purchase insurance and to seek care when ill are correlated with the expected healthcare expenditure, the use of naïve models may produce biased estimates of the impact of insurance membership on OOP expenditure. Whilst many studies in the literature have accounted for the endogeneity of the insurance decision, the potential selection bias due to the care-seeking decision has not been taken into account. We extend the Heckman selection model to account simultaneously for both care-seeking and insurance-seeking selection biases in the healthcare expenditure regression model. The proposed model is illustrated in the context of a Vietnamese HI programme using data from a household survey of 1192 individuals conducted in 1999. Results were compared with those of alternative econometric models making no or partial allowance for selection bias. In this illustrative example, the impact of insurance membership on reducing OOP expenditures was underestimated by 21 percentage points when selection biases were not taken into account. We believe this is an important methodological contribution that will be relevant to future empirical work.

Original language	English
Pages (from-to)	127-140
Number of pages	14
Journal	Social science and medicine
Volume	177
Early online date	4 Nov 2016
DOIs	https://doi.org/10.1016/j.socscimed.2016.11.005
Publication status	Published - Mar 2017

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10.1016/j.socscimed.2016.11.005

SSM - Vietnam Health Insurance (submitted Aug 2016 - revision 2)
© 2016 Elsevier Ltd. This is an author-produced version of the published paper. Uploaded in accordance with the publisher’s self-archiving policy
Accepted author manuscript, 1.98 MBLicence: CC BY-NC

Cite this

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title = "Addressing care-seeking as well as insurance-seeking selection biases in estimating the impact of health insurance on out-of-pocket expenditure",

abstract = "Health Insurance (HI) programmes in low-income countries aim to reduce the burden of individual out-of-pocket (OOP) health care expenditure. However, if the decisions to purchase insurance and to seek care when ill are correlated with the expected healthcare expenditure, the use of na{\"i}ve models may produce biased estimates of the impact of insurance membership on OOP expenditure. Whilst many studies in the literature have accounted for the endogeneity of the insurance decision, the potential selection bias due to the care-seeking decision has not been taken into account. We extend the Heckman selection model to account simultaneously for both care-seeking and insurance-seeking selection biases in the healthcare expenditure regression model. The proposed model is illustrated in the context of a Vietnamese HI programme using data from a household survey of 1192 individuals conducted in 1999. Results were compared with those of alternative econometric models making no or partial allowance for selection bias. In this illustrative example, the impact of insurance membership on reducing OOP expenditures was underestimated by 21 percentage points when selection biases were not taken into account. We believe this is an important methodological contribution that will be relevant to future empirical work.",

author = "Shehzad Ali and Cookson, {Richard Andrew} and Dusheiko, {Mark Alan}",

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N2 - Health Insurance (HI) programmes in low-income countries aim to reduce the burden of individual out-of-pocket (OOP) health care expenditure. However, if the decisions to purchase insurance and to seek care when ill are correlated with the expected healthcare expenditure, the use of naïve models may produce biased estimates of the impact of insurance membership on OOP expenditure. Whilst many studies in the literature have accounted for the endogeneity of the insurance decision, the potential selection bias due to the care-seeking decision has not been taken into account. We extend the Heckman selection model to account simultaneously for both care-seeking and insurance-seeking selection biases in the healthcare expenditure regression model. The proposed model is illustrated in the context of a Vietnamese HI programme using data from a household survey of 1192 individuals conducted in 1999. Results were compared with those of alternative econometric models making no or partial allowance for selection bias. In this illustrative example, the impact of insurance membership on reducing OOP expenditures was underestimated by 21 percentage points when selection biases were not taken into account. We believe this is an important methodological contribution that will be relevant to future empirical work.

AB - Health Insurance (HI) programmes in low-income countries aim to reduce the burden of individual out-of-pocket (OOP) health care expenditure. However, if the decisions to purchase insurance and to seek care when ill are correlated with the expected healthcare expenditure, the use of naïve models may produce biased estimates of the impact of insurance membership on OOP expenditure. Whilst many studies in the literature have accounted for the endogeneity of the insurance decision, the potential selection bias due to the care-seeking decision has not been taken into account. We extend the Heckman selection model to account simultaneously for both care-seeking and insurance-seeking selection biases in the healthcare expenditure regression model. The proposed model is illustrated in the context of a Vietnamese HI programme using data from a household survey of 1192 individuals conducted in 1999. Results were compared with those of alternative econometric models making no or partial allowance for selection bias. In this illustrative example, the impact of insurance membership on reducing OOP expenditures was underestimated by 21 percentage points when selection biases were not taken into account. We believe this is an important methodological contribution that will be relevant to future empirical work.

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