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Assessing the impact of high deductible health plans on health‐care utilization and cost: a changes‐in‐changes approach

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  • Bijan J. Borah
  • Marguerite E. Burns
  • Nilay D. Shah

Abstract

High deductible health plans (HDHPs) have become an increasingly common form of benefit design used by employers to manage health‐care costs. Numerous studies have evaluated the uptake and impact of HDHPs on health‐care utilization. Most studies have employed the standard difference‐in‐differences (DID) methodology. In this paper, we employ three alternative methodologies to evaluate a natural experiment in which a traditional health plan was fully replaced by a HDHP. We implement the standard DID and the quantile difference‐in‐differences (QDID) estimators to evaluate the impact of the HDHP on following six outcomes: overall cost, medical cost, pharmacy cost, outpatient visit count, inpatient visit count and emergency room visit count. We compare these results to a changes‐in‐changes (CIC) estimator, a generalized version of the standard (DID) estimator. We find that both the DID and CIC models yielded similar results, while the QDID model provided additional insights on the HDHP impact across different parts of the outcome distributions. Overall, introduction of HDHP had no impact on health‐care costs, positive impact on the number of outpatient visits and mixed impacts on the inpatient and emergency room visit counts. The QDID estimates suggest HDHP introduction generally impacted subjects in upper percentiles (50th, 75th and 90th). Copyright © 2011 John Wiley & Sons, Ltd.

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  • Bijan J. Borah & Marguerite E. Burns & Nilay D. Shah, 2011. "Assessing the impact of high deductible health plans on health‐care utilization and cost: a changes‐in‐changes approach," Health Economics, John Wiley & Sons, Ltd., vol. 20(9), pages 1025-1042, September.
  • Handle: RePEc:wly:hlthec:v:20:y:2011:i:9:p:1025-1042
    DOI: 10.1002/hec.1757
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    2. Mullahy, John, 2018. "Individual results may vary: Inequality-probability bounds for some health-outcome treatment effects," Journal of Health Economics, Elsevier, vol. 61(C), pages 151-162.
    3. Stefan Boes & Michael Gerfin, 2016. "Does Full Insurance Increase the Demand for Health Care?," Health Economics, John Wiley & Sons, Ltd., vol. 25(11), pages 1483-1496, November.
    4. Richard Peter & Sebastian Soika & Petra Steinorth, 2016. "Health Insurance, Health Savings Accounts and Healthcare Utilization," Health Economics, John Wiley & Sons, Ltd., vol. 25(3), pages 357-371, March.
    5. John Mullahy, 2017. "Individual Results May Vary: Elementary Analytics of Inequality-Probability Bounds, with Applications to Health-Outcome Treatment Effects," NBER Working Papers 23603, National Bureau of Economic Research, Inc.
    6. M. Kate Bundorf, 2016. "Consumer-Directed Health Plans: A Review Of The Evidence," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 83(1), pages 9-41, January.
    7. Vincenzo Atella & Joanna Kopinska, 2014. "The impact of cost-sharing schemes on drug compliance in Italy: evidence based on quantile regression," International Journal of Public Health, Springer;Swiss School of Public Health (SSPH+), vol. 59(2), pages 329-339, April.
    8. Shao, Shuai & Xu, Le & Yang, Lili & Yu, Dianfan, 2024. "How do energy-saving policies improve environmental quality: Evidence from China’s Top 10,000 energy-consuming enterprises program," World Development, Elsevier, vol. 175(C).

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