Effects of state reinsurance programs on health insurance exchange premiums and insurer participation

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.     

Intermediate-term outcomes of combined phacoemulsification and Aurolab aqueous drainage implant in eyes with refractory glaucoma and coexistent cataract

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...     

Differentiating poor validity from probable impairment on the medical symptom validity test: a cross-validation study

Aims: In neuropsychological evaluations, it is often difficult to ascertain whether poor performance on measures of validity is due to poor effort or malingering, or whether there is genuine cognitive impairment. Dunham and Denney created an algorithm to assess this question using the Medical Symptom Validity Test (MSVT). We assessed the ability of their algorithm to detect poor validity versus probable impairment, and concordance of failure on the MSVT with other freestanding tests of performance validity.

Methods: Two previously published datasets (n?=?153 and n?=?641, respectively) from outpatient neuropsychological evaluations were used to test Dunham and Denney’s algorithm, and to assess concordance of failure rates with the Test of Memory Malingering and the forced choice measure of the California Verbal Learning Test, two commonly used performance validity tests.

Results: In both datasets, none of the four cutoff scores for failure on the MSVT (70%, 75%, 80%, or 85%) identified a poor validity group with proportionally aligned failure rates on other freestanding measures of performance validity. Additionally, the protocols with probable impairment did not differ from those with poor validity on cognitive measures.

Conclusions: Despite what appeared to be a promising approach to evaluating failure on the easy MSVT subtests when clinical data are unavailable (as recommended in the advanced interpretation program, or advanced interpretation [AI], of the MSVT), the current findings indicate the AI remains the gold standard for doing so. Future research should build on this effort to address shortcomings in measures of effort in neuropsychological evaluations.