Quality information disclosure and health insurance demand: evidence from VA hospital report cards

Abstract

This study examines the effect of public reporting of quality information on the demand for public insurance. In particular, we examine the effect of the introduction of Veterans Affairs (VA) hospital quality report cards in 2008. Using data from the Current Population Survey in 2005–2015, we find that new information about the quality of a VA hospital had a significant effect on VA coverage among veterans living in the same Metropolitan Statistical Area (MSA). Despite the significant effect on VA coverage, the quality report did not have a spillover effect on veterans’ labor supply. Moreover, updated quality information released in later years, which was presented in a less straightforward form, led to no additional changes in VA coverage. These findings suggest that quality reports for public insurance programs can be used as a policy lever to facilitate take up decision among potential beneficiaries.

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Notes

  1. 1.

    In 2017, the national income threshold is $40,694 for veterans with two dependents and $42,899 for veterans with three dependents. The national threshold is adjusted geographically for cost of living.

  2. 2.

    https://www.va.gov/opa/pressrel/pressrelease.cfm?id=1515.

  3. 3.

    The Internet is a primary source of information about VA benefits. According to the National Survey of Veterans in 2010, the majority of Veterans access the Internet (72.3%) and expressed willingness to use the Internet to obtain information about VA benefits (68.8%).

  4. 4.

    Appendix” presents detailed procedure measures used to construct the HEDIS scores and the ORYX scores.

  5. 5.

    The remaining 13 facilities were either not located in an MSA or located in an MSA that were not identified in the CPS.

  6. 6.

    Educational attainment, rather than income, is used for sample restriction because labor supply decisions could be affected by demand for health insurance. Boyle and Lahey (2010) shows access to VA health care reduces labor supply of veterans. Therefore, income is potentially endogenous to VA take-up while educational attainment is likely exogenous.

  7. 7.

    The point estimate is statistically significant at the 15% level.

  8. 8.

    Four measures are constructed as controls: share of veterans with service-connected disability, share of veterans with low-rating service connected disability (rated 10% or lower), share of veterans with medium-rating service connected disability (rated 11–49%), and share of veterans with high-rating service connected disability (rated 50% or higher). These measures are constructed using veteran supplement weights.

  9. 9.

    It is worth noting that instead of reporting the raw data for patient rating, Hospital Compare reports the percentages of patients who gave a high rating (9 or 10), a medium rating (7 or 8), a and low rating (6 and below). A hospital is coded as “received a patient rating above national average” if the percentage of patients who gave a high rating exceeds that of the national average (64%).

  10. 10.

    VA Utilization Profile, https://www.va.gov/vetdata/docs/Quickfacts/VA_Utilization_Profile.pdf.

References

  1. Aizer, A. (2007). Public health insurance, program take-up, and child health. The Review of Economics and Statistics,3, 400–415.

    Article  Google Scholar 

  2. Bansak, C., & Raphael, S. (2007). The effects of state policy design features on take-up and crowd-out rates for the State Children’s Health Insurance Program. Journal of Policy Analysis and Management,26(1), 149–175.

    PubMed  Article  Google Scholar 

  3. Beaulieu, N. D. (2002). Quality information and consumer health plan choices. Journal of Health Economics,21(1), 43–63.

    PubMed  Article  Google Scholar 

  4. Bisgaier, J., & Rhodes, K. V. (2011). Auditing access to specialty care for children with public insurance. The New England Journal of Medicine,364, 2324–2333.

    CAS  PubMed  Article  Google Scholar 

  5. Boyle, M. A., & Lahey, J. N. (2010). Health insurance and the labor supply decisions of older workers: evidence from a U.S. department of veterans affairs expansion. Journal of Public Economics,94(7–8), 467–478.

    PubMed  PubMed Central  Article  Google Scholar 

  6. Boyle, M. A., & Lahey, J. N. (2016). Spousal labor market effects from government health insurance: evidence from a veterans affairs expansion. Journal of Health Economics,45, 63–76.

    PubMed  Article  Google Scholar 

  7. Bundorf, M. K., Chun, N., Goda, G. S., & Kessler, D. P. (2009). Do markets respond to quality information? The case of fertility clinics. Journal of Health Economics,28(3), 718–727.

    PubMed  Article  Google Scholar 

  8. Casalino, L. P., Gans, D., Weber, R., Cea, M., Tuchovsky, A., Bishop, T. F., et al. (2016). Datawatch: US physician practices spend more than $15.4 billion annually to report quality measures. Health Affairs,35(3), 401–406.

    PubMed  Article  Google Scholar 

  9. Chandra, A., Finkelstein, A., Sacarny, A., & Syverson, C. (2016). Health care exceptionalism? Performance and allocation in the US health care sector. American Economic Review,106(8), 2110–2144.

    PubMed  Article  Google Scholar 

  10. Chen, Y., & Meinecke, J. (2012). Do healthcare report cards cause providers to select patients and raise quality of care? Health Economics,21(11), 33–55.

    PubMed  Article  Google Scholar 

  11. Chou, S. Y., Deily, M. E., Li, S., & Yi, L. (2014). Competition and the impact of online hospital report cards. Journal of Health Economics,34(1), 42–58.

    PubMed  Article  Google Scholar 

  12. Congressional Budget Office. (2007). The health care system for veterans: interim report, December.

  13. Congressional Budget Office. (2009). Quality initiatives undertaken by the veterans health administration, August

  14. Cunningham, P. J. (2003). SCHIP making progress: increased take-up contributes to coverage gains. Health Affairs,22(4), 163–172.

    PubMed  Article  Google Scholar 

  15. Dafny, L., & Dranove, D. (2008). Do report cards tell consumers anything they don’t already know? The case of medicare HMOs. The Rand Journal of Economics,39(3), 790–821.

    PubMed  Article  Google Scholar 

  16. Darden, M., & McCarthy, I. M. (2015). The star treatment: estimating the impact of star ratings on medicare advantage enrollments. Journal of Human Resources,50(4), 980–1008.

    Article  Google Scholar 

  17. Decker, S. L. (2007). Medicaid physician fees and the quality of medical care of medicaid patients in the USA. Review of Economics of the Household,5(1), 95–112.

    Article  Google Scholar 

  18. Dranove, D., Kessler, D., McClellan, M., & Satterthwaite, M. (2003). Is more information better? The effects of ‘report cards’ on health care providers. Journal of Political Economy,111(3), 555–588.

    Article  Google Scholar 

  19. Garthwaite, C., Gross, T., & Notowidigdo, M. J. (2014). Public health insurance, labor supply, and employment shock. The Quarterly Journal of Economics,129, 653–696.

    Article  Google Scholar 

  20. Hahn, Y. (2013). The effect of medicaid physician fees on take-up of public health insurance among children in poverty. Journal of Health Economics,32(2), 452–462.

    PubMed  Article  Google Scholar 

  21. Hibbard, J. H., Greene, J., & Daniel, D. (2010). What is quality anyway? Performance reports that clearly communicate to consumers the meaning of quality of care. Medical Care Research and Review,67(3), 275–293.

    PubMed  Article  Google Scholar 

  22. Jung, J. K., Bingxiao, W., Kim, H., & Polsky, D. (2016). The effect of publicized quality information on home health agency choice. Medical Care Research and Review,73(6), 703–723.

    PubMed  Article  Google Scholar 

  23. Kizer, K. W., & Dudley, R. A. (2009). Extreme makeover: transformation of the veterans health care system. Annual Review of Public Health,30(1), 313–339.

    PubMed  Article  Google Scholar 

  24. Kolstad, J. T., & Chernew, M. E. (2009). Quality and consumer decision making in the market for health insurance and health care services. Medical Care Research and Review,66(1_suppl), 28S–52S.

    PubMed  Article  Google Scholar 

  25. Konetzka, R. T., Polsky, D., & Werner, R. M. (2013). Shipping out instead of shaping up: rehospitalization from nursing homes as an unintended effect of public reporting. Journal of Health Economics,32(2), 341–352.

    PubMed  Article  Google Scholar 

  26. Landrum, M. B., Bronskill, S. E., & Normand, S. L. T. (2000). Analytic methods for constructing cross-sectional profiles of health care providers. Health Services and Outcomes Research Methodology,1, 23–47.

    Article  Google Scholar 

  27. Li, D., Richards, M., & Wing. C. (2019). Public quality reporting in the absence of market forces. Evidence from the Veterans Health Administration.

  28. Mukamel, D. B., Weimer, D. L., Zwanziger, J., Gorthy, S. H., Mushlin, A. I., & Mukamel, B. (2004). Quality report cards, selection of cardiac disparities: a study of the publication of the New York. Inquiry,41(4), 435–446.

    PubMed  Article  Google Scholar 

  29. Percy, A., Gilmore, J. M., & Goldberg, M. S. (2009). Quality initiatives undertaken by the veterans health administration (p. 50). Washington: Congressional Budget Office.

    Google Scholar 

  30. Perraillon, M. C., Tamara Konetzka, R., He, D., & Werner, R. M. (2018). Consumer response to composite ratings of nursing home quality. American Journal of Health Economics,5, 165–190.

    Article  Google Scholar 

  31. Peters, E., Dieckmann, N., Dixon, A., Hibbard, J. H., & Mertz, C. K. (2007). Less is more in presenting quality information to consumers. Medical Care Research and Review,64(2), 169–190.

    PubMed  Article  Google Scholar 

  32. Rogowski, J., & Karoly, L. (2000). Health insurance and retirement behavior: evidence from the health and retirement survey. Journal of Health Economics,19(4), 529–539.

    CAS  PubMed  Article  Google Scholar 

  33. Scanlon, D. P., Chernew, M., McLaughlin, C., & Solon, G. (2002). The impact of health plan report cards on managed care enrollment. Journal of Health Economics,21(1), 19–41.

    Article  Google Scholar 

  34. Shoven, J. B., & Slavov, S. N. (2014). The role of retiree health insurance in the early retirement of public sector employees. Journal of Health Economics,38, 99–108.

    PubMed  Article  Google Scholar 

  35. Sommers, B., Kronick, R., Finegold, K., Po, R., Schwartz, K., & Glied, S. (2012). Understanding participation rates in medicaid: implications for the affordable care act. Gains for children: increased participation in medicaid and. ASPE Issue Brief March.

  36. Wedig, G. J., & Tai-seale, M. (2002). The effect of report cards on consumer choice in the health insurance market. Journal of Health Economics,21, 1031–1048.

    PubMed  Article  Google Scholar 

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Appendix

Appendix

See Table 8.

Table 8 Detailed quality measures used to construct the composite scores.

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Li, X. Quality information disclosure and health insurance demand: evidence from VA hospital report cards. Int J Health Econ Manag. 20, 177–199 (2020). https://doi.org/10.1007/s10754-019-09276-9

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Keywords

  • Veterans Affairs
  • Health insurance demand
  • Quality report

JEL Classification

  • I13
  • I18
  • J21