Dataset Information

Health Insurance Dynamics: Methodological Considerations and a Comparison of Estimates from Two Surveys.

ABSTRACT: To highlight key methodological issues in studying insurance dynamics and to compare estimates across two commonly used surveys.Nonelderly uninsured adults and children sampled between 2001 and 2011 in the Medical Expenditure Panel Survey and the Survey of Income and Program Participation.We utilized nonparametric Kaplan-Meier methods to estimate quantiles (25th, 50th, and 75th percentiles) in the distribution of uninsured spells. We compared estimates obtained across surveys and across different methodological approaches to address issues like attrition, seam bias, censoring and truncation, and survey weighting method.All data were drawn from publicly available household surveys.Estimated uninsured spell durations in the MEPS were longer than those observed in the SIPP. There were few changes in spell durations between 2001 and 2011, with median durations of 14 months among adults and 5-7 months among children in the MEPS, and 8 months (adults) and 4 months (children) in the SIPP.The use of panel survey data to study insurance dynamics presents a unique set of methodological challenges. Researchers should consider key analytic and survey design trade-offs when choosing which survey can best suit their research goals.

SUBMITTER: Graves JA

PROVIDER: S-EPMC5034207 | biostudies-other | 2016 Oct

REPOSITORIES: biostudies-other

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Health Insurance Dynamics: Methodological Considerations and a Comparison of Estimates from Two Surveys.

Graves John A JA Mishra Pranita P

Health services research 20160203 5

<h4>Objective</h4>To highlight key methodological issues in studying insurance dynamics and to compare estimates across two commonly used surveys.<h4>Data sources/study setting</h4>Nonelderly uninsured adults and children sampled between 2001 and 2011 in the Medical Expenditure Panel Survey and the Survey of Income and Program Participation.<h4>Study design</h4>We utilized nonparametric Kaplan-Meier methods to estimate quantiles (25th, 50th, and 75th percentiles) in the distribution of uninsured ...[more]

PMID: 26841265

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Project description:Many health technology assessment committees have an explicit or implicit reference value (often referred to as a 'threshold') below which new health technologies or interventions are considered value for money. The basis for these reference values is unclear but one argument is that it should be based on the health opportunity costs of funding decisions. Empirical estimates of the marginal cost per unit of health produced by a healthcare system have been proposed to capture the health opportunity costs of new funding decisions. Based on a systematic search, we identified eight studies that have sought to estimate a reference value through empirical estimation of the marginal cost per unit of health produced by a healthcare system for England, Spain, Australia, The Netherlands, Sweden, South Africa and China. We review these eight studies to provide an overview of the key methodological approaches taken to estimate the marginal cost per unit of health produced by the healthcare system with the aim to help inform future estimates for additional countries. The lead author for each of these papers was invited to contribute to the current paper to ensure all the key methodological issues encountered were appropriately captured. These included consideration of the key variables required and their measurement, accounting for endogeneity of spending to health outcomes, the inclusion of lagged spending, discounting and future costs, the use of analytical weights, level of disease aggregation, expected duration of health gains, and modelling approaches to estimating mortality and morbidity effects of health spending. Subsequent research estimates for additional countries should (1) carefully consider the specific context and data available, (2) clearly and transparently report the assumptions made and include stakeholder perspectives on their appropriateness and acceptability, and (3) assess the sensitivity of the preferred central estimate to these assumptions.

Dataset Information

Health Insurance Dynamics: Methodological Considerations and a Comparison of Estimates from Two Surveys.

Publications

Health Insurance Dynamics: Methodological Considerations and a Comparison of Estimates from Two Surveys.

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