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1.
Objective
The aim of the study was to estimate the effect of the state-based reinsurance programs through the section 1332 State Innovation Waivers on health insurance marketplace premiums and insurer participation.Data Source
2015 to 2022 Robert Wood Johnson Foundation Health Insurance Exchange Compare Datasets.Study Design
An event study difference-in-differences (DD) model separately for each year of implementation and a synthetic control method (SCM) are used to estimate year-by-year effects following program implementation.Data Collection/Extraction Methods
Not applicable.Principal Findings
Reinsurance programs were associated with a decline in premiums in the first year of implementation by 10%–13%, 5%–19%, and 11%–17% for bronze, silver, and gold plans (p < 0.05). There is a trend of sustained declines especially for states that implemented their programs in 2019 and 2020. The SCM analyses suggest some effect heterogeneity across states but also premium declines across most states. There is no evidence that reinsurance programs affected insurer participation.Conclusion
State-based reinsurance programs have the potential to improve the affordability of health insurance coverage. However, reinsurance programs do not appear to have had an effect on insurer participation, highlighting the need for policy makers to consider complementary strategies to encourage insurer participation. 相似文献2.
Rajendrababu Sharmila Puthuran George Varghese Alia Laxmi Ananya Uduman Mohammed Sithiq Wijesinghe Hiruni Kaushalya 《International ophthalmology》2022,42(8):2609-2618
International Ophthalmology - To investigate the efficacy and safety of non-valved Aurolab aqueous drainage implant (AADI) surgery combined with phacoemulsification in eyes with refractory glaucoma... 相似文献
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Thomas Asendorf Robin Henderson Heinz Schmidli Tim Friede 《Statistics in medicine》2019,38(9):1503-1528
In some diseases, such as multiple sclerosis, lesion counts obtained from magnetic resonance imaging (MRI) are used as markers of disease progression. This leads to longitudinal, and typically overdispersed, count data outcomes in clinical trials. Models for such data invariably include a number of nuisance parameters, which can be difficult to specify at the planning stage, leading to considerable uncertainty in sample size specification. Consequently, blinded sample size re-estimation procedures are used, allowing for an adjustment of the sample size within an ongoing trial by estimating relevant nuisance parameters at an interim point, without compromising trial integrity. To date, the methods available for re-estimation have required an assumption that the mean count is time-constant within patients. We propose a new modeling approach that maintains the advantages of established procedures but allows for general underlying and treatment-specific time trends in the mean response. A simulation study is conducted to assess the effectiveness of blinded sample size re-estimation methods over fixed designs. Sample sizes attained through blinded sample size re-estimation procedures are shown to maintain the desired study power without inflating the Type I error rate and the procedure is demonstrated on MRI data from a recent study in multiple sclerosis. 相似文献