The Health Insurance Reform Simulation Model (HIRSM)

Methodological Detail and Prototypical Simulation Results

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Posted to Web: July 31, 2003
Permanent Link: http://www.urban.org/url.cfm?ID=410867

This research was funded by the Employee Benefits Security Administration of the U.S. Department of Labor (Contract No.: J-9-P-7-0044).

The nonpartisan Urban Institute publishes studies, reports, and books on timely topics worthy of public consideration. The views expressed are those of the authors and should not be attributed to the Urban Institute, its trustees, or its funders.

Note: This report is available in its entirety in the Portable Document Format (PDF).


Section 1. Introduction

The Health Insurance Reform Simulation Model (HIRSM) is designed to simulate the coverage, cost, and tax implications of health insurance coverage expansion proposals as well as other reforms to the health insurance system. The model is constructed using nationally representative data on employers, workers, and those outside of the labor market. HIRSM simulates the behavioral choices of insurers, employers, and individuals under the current system and under reform, and allows us to predict the coverage consequences of various policy alternatives. It can simulate the effects of health insurance reforms affecting private health insurance markets and public sector programs. This report details the model in its entirety, including components of the version originally detailed in an earlier methodology report (Blumberg, Nichols, Shen, Buettgens 2002), which are still in operation, and the modifications made since that report was written.

1.1 The Foundation of HIRSM

The design of HIRSM is predicated on the notion that the inter-relationships among decision-makers are key to predicting the effects of changes to insurance markets as accurately as possible. This means that changes in worker preferences should be reflected in the decisions of employers; employer decisions to offer or not offer employer-sponsored insurance to their workers will affect the types of premium offers that insurers make; premium offers will, in turn, affect the attractiveness of coverage to potential enrollees; and coverage options/premiums in one sector of the market (i.e., employer-sponsored insurance, private non-group insurance, public programs) will affect coverage decisions in other sectors of the market. In light of this conceptual framework, a number of innovations are incorporated into HIRSM, which set it apart from other microsimulation models.

First, HIRSM simulates current law before it simulates reforms. In other words, the model's baseline is an output of the model. In technical terms, HIRSM's baseline is endogenous to the model's structure. The notion behind this approach is that one can have greater confidence in the modeling abilities of a simulation if it can accurately replicate what is known about current insurance arrangements. Many models take current law as given and only reveal post-reform effects. HIRSM iterates the full cycle of interrelated decisions 20 times before it reaches equilibrium under current law rules.

Second, premiums for offered insurance policies are generated endogeneously within HIRSM, as opposed to being assigned a priori and being preserved for perpetuity. The particular health expenditure risk profile of individuals enrolling in coverage through specific risk pools is reflected in the premiums that HIRSM insurers offer to potential purchasers each period. In this way, simulation of reforms that affect the composition of risk pools will affect the premiums offered, and this in turn will affect individual and group behavioral decisions regarding coverage.

Third, all behavioral decisions within HIRSM are generated from econometrically estimated equations based upon nationally representative data. In this way, behavior is not driven simply by assumption, but based in our best understanding of how the various players actually make their decisions in the current world. And finally, it is our intent to make the mechanics and assumptions which underlie HIRSM transparent to other analysts, recognizing that sound policy-making must be based upon full information.

Fourth, HIRSM allows for simulations of public and private reforms off of the same analytic platform, thereby ensuring the comparability of simulated effects of these different types of reforms, and allowing us to assess the extent to which reforms in one insurance sector might impact the other. The model also allows us to simulate the effects of "hybrid" types of reforms, which entail an expansion of public insurance in conjunction with a tax credit for purchasing health insurance in the private market.

This report is structured as follows. Section 2 provides a walk through the structure and dynamics of the new HIRSM model using an in-depth flow chart. Section 3 presents further details of the construction of the HIRSM database. Section 4-9 describes further technical details on the behavioral components and the premium determination process within HIRSM. Section 10 compares HIRSM's baseline, for purposes of validation, with data from nationally representative publicly available data sets. Section 11 describes adjustments made to behavioral decisions under various reform scenarios. Section 12 describes the prototypical reform policies used to illustrate HIRSM's capabilities. Section 13 presents simulation results. Section 14 summarizes a series of sensitivity analyses. Section 15 concludes.

Note: This report is available in its entirety in the Portable Document Format (PDF).


Acknowledgments

With an undertaking as complex as this one, we were very fortunate to have been able to call on many colleagues for advice and assistance. We are extremely grateful to them all: John Holahan, Sheila Zedlewski, Len Burman, Phil Cooper, Jessica Vistnes, Jessica Banthin, Bowen Garrett, Jennifer Haley, Marie Wang, Paul Johnson, Sandi Nelson, Linda Giannarelli, Genevieve Kenney, Amy Davidoff, Alshadye Yemane, Grace Ko, Alex Tebay, Laura Wheaton, and Frederic Blavin. In addition, outside reviewers provided many useful suggestions and comments: Joseph Antos, Linda Bilheimer, Martin Holmer, Susan Marquis, Jim Mays, Dahlia Remler, Jack Rodgers, and Jeannette Rogowski. Gillian Hunter, Sonia Conly, and Sherry Glied have also contributed to our thinking on this project. This research was funded by the Employee Benefits Security Administration of the U.S. Department of Labor (Contract No.: J-9-P-7-0044). The views and opinions expressed are those of the authors and should not be attributed to the Urban Institute, its Trustees, or its Funders.


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