Understanding the distributional impacts of health insurance reform : Evidence from a consumer cost-sharing program
© 2021 John Wiley & Sons Ltd..
We examine the heterogeneous effects of reference pricing, a health insurance reform introduced by the California Public Employees' Retirement System (CalPERS), on the distribution of spending by patients and insurers. Using medical claims data for CalPERS and a comparison group not subject to reference pricing, we use the changes-in-changes approach to estimate the quantile treatment effects of the program across different medical procedures. We find that the quantile treatment effects vary across the patient spending distributions, with a range of positive and negative estimates of the QTE, depending on the medical procedure considered. However, across all procedures, the insurer's spending distributions tend to shift left, with the largest reductions occurring in the right-tail of the spending distributions. These effects are not captured by mean estimates but have important policy implications.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2021 |
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| Erschienen: |
2021 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:30 |
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| Enthalten in: |
Health economics - 30(2021), 11 vom: 06. Nov., Seite 2780-2793 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Aouad, Marion [VerfasserIn] |
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| Links: |
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| Themen: |
Distributional effects |
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| Anmerkungen: |
Date Completed 29.10.2021 Date Revised 14.02.2023 published: Print-Electronic Citation Status MEDLINE |
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| doi: |
10.1002/hec.4410 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| PPN (Katalog-ID): |
NLM329616102 |
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| 520 | |a © 2021 John Wiley & Sons Ltd. | ||
| 520 | |a We examine the heterogeneous effects of reference pricing, a health insurance reform introduced by the California Public Employees' Retirement System (CalPERS), on the distribution of spending by patients and insurers. Using medical claims data for CalPERS and a comparison group not subject to reference pricing, we use the changes-in-changes approach to estimate the quantile treatment effects of the program across different medical procedures. We find that the quantile treatment effects vary across the patient spending distributions, with a range of positive and negative estimates of the QTE, depending on the medical procedure considered. However, across all procedures, the insurer's spending distributions tend to shift left, with the largest reductions occurring in the right-tail of the spending distributions. These effects are not captured by mean estimates but have important policy implications | ||
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