Prevalence of employer self-insured health benefits: national and state variation

Sex differences in the temperature dependence of kidney stone presentations: a population-based aggregated case-crossover study

Previous studies assumed a uniform relationship between heat and kidney stone presentations. Determining whether sex and other characteristics modify the temperature dependence of kidney stone presentations has implications for explaining differences in nephrolithiasis prevalence and improving projections of the effect of climate change on nephrolithiasis. We performed an aggregated case-crossover study among 132,597 children and adults who presented with nephrolithiasis to 68 emergency departments throughout South Carolina from 1997 to 2015. We used quasi-Poisson regression with distributed lag non-linear models to estimate sex differences in the cumulative exposure and lagged response between maximum daily wet-bulb temperatures and emergent kidney stone presentations, aggregated at the ZIP-code level. We also explored interactions by age, race, payer, and climate. Compared to 10 °C, daily wet-bulb temperatures at the 99th percentile were associated with a greater increased relative risk (RR) of kidney stone presentations over 10 days for males (RR 1.73; 95% CI 1.56, 1.91) than for females (RR 1.15; 95% CI 1.01, 1.32; interaction P < 0.001). The shape of the lagged response was similar for males and females, with the greatest risk estimated for the 2 days following high temperatures. There were weak differences by age, race, and climatic zone, and no differences by payer status. The estimated risk of presenting emergently with kidney stones within 10 days of high daily wet-bulb temperatures was substantially greater among men than women, and similar between patients with public and private insurance. These findings suggest that the higher risk among males may be due to sexually dimorphic physiologic responses rather than greater exposure to ambient temperatures.

Does Limiting Allowable Rating Variation in the Small Group Health Insurance Market Affect Employer Self-Insurance?

The Affordable Care Act (ACA) imposes adjusted community rating in the small group market, which employers can avoid by self-insuring, raising concerns about adverse selection. We evaluate the impact of limiting allowable rating variation on employer self-insurance across industries with varied health risk, using cross-state variation in pre-ACA rating regulations, the nationally-representative 2008-2013 KFF/HRET Employer Health Benefits survey, and a triple-difference regression approach. We find that lower-risk employers subject to laws limiting allowable premium rating variation have a predicted probability of self-insurance that is about 18 percentage points higher than otherwise-similar higher-risk employers, suggesting that these selection concerns are warranted.

Lessons from state mandates of preventive cancer screenings

We use the 1997-2008 Medical Expenditure Panel Survey (MEPS) and variation in the timing of state mandates for coverage of colorectal, cervical, and prostate cancer screenings to investigate the behavioral and financial effects of mandates on privately insured adults. We find that state mandates did not result in increased rates of cancer screening. However, coverage of preventive care, whether mandated or not, moves the cost of care from the consumer's out-of-pocket expense to the premium, resulting in a cross-subsidy of users of the service by non-users. While some cross-subsidies are intentional, others may be unintentional. We find that users of cancer screening have higher levels of income and education, while non-users tend to be racial minorities, lack a usual source of care, and live in communities with fewer physicians per capita. These results suggest that coverage of preventive care may transfer resources from more advantaged individuals to less advantaged individuals.

Daily mean temperature and clinical kidney stone presentation in five U.S. metropolitan areas: a time-series analysis

BACKGROUND

High ambient temperatures are a risk factor for nephrolithiasis, but the precise relationship between temperature and kidney stone presentation is unknown.

OBJECTIVES

Our objective was to estimate associations between mean daily temperature and kidney stone presentation according to lag time and temperatures.

METHODS

Using a time-series design and distributed lag nonlinear models, we estimated the relative risk (RR) of kidney stone presentation associated with mean daily temperatures, including cumulative RR for a 20-day period, and RR for individual daily lags through 20 days. Our analysis used data from the MarketScan Commercial Claims database for 60,433 patients who sought medical evaluation or treatment of kidney stones from 2005-2011 in the U.S. cities of Atlanta, Georgia; Chicago, Illinois; Dallas, Texas; Los Angeles, California; and Philadelphia, Pennsylvania.

RESULTS

Associations between mean daily temperature and kidney stone presentation were not monotonic, and there was variation in the exposure-response curve shapes and the strength of associations at different temperatures. However, in most cases RRs increased for temperatures above the reference value of 10°C. The cumulative RR for a daily mean temperature of 30°C versus 10°C was 1.38 in Atlanta (95% CI: 1.07, 1.79), 1.37 in Chicago (95% CI: 1.07, 1.76), 1.36 in Dallas (95% CI: 1.10, 1.69), 1.11 in Los Angeles (95% CI: 0.73, 1.68), and 1.47 in Philadelphia (95% CI: 1.00, 2.17). Kidney stone presentations also were positively associated with temperatures < 2°C in Atlanta, and < 10°C in Chicago and Philadelphia. In four cities, the strongest association between kidney stone presentation and a daily mean temperature of 30°C versus 10°C was estimated for lags of ≤ 3 days.

CONCLUSIONS

In general, kidney stone presentations increased with higher daily mean temperatures, with the strongest associations estimated for lags of only a few days. These findings further support an adverse effect of high temperatures on nephrolithiasis.

Modeling employer self-insurance decisions after the Affordable Care Act

OBJECTIVE

To present a microsimulation model that addresses the methodological challenge of estimating the firm decision to self-insure.

METHODOLOGY

The model considers the risk that the firm bears when self-insuring and the opportunity to mitigate that risk by purchasing stop-loss insurance. The model makes use of a structural, utility maximization framework to account for numerous aspects of the firm decision, and a multinomial probit to reproduce the elasticity of the firm's demand for health insurance.

FINDINGS AND CONCLUSIONS

Our simulations provide three important conclusions. First, they project significant increases in self-insurance rates among small firms--presumably induced by the desire to avoid ACA's rate-banding and risk adjustment regulations-only if generous stop-loss policies become widely available. Second, they show that this increase would be due to this hypothetical adoption of widespread, generous reinsurance by the market and not by passage of the ACA. Third, even with a substantial increase of self-insurance rates among small firms, they project negligible adverse selection in the exchanges, as indicated by our finding that the increase in exchange premium is less than 0.5% when assuming very generous stop-loss policies after implementation of the ACA.

Effects of infertility insurance mandates on fertility

Infertility currently affects over 6 million individuals in the United States. While most health insurance plans nationwide do not cover infertility diagnoses or treatments, to date 15 states have enacted some form of infertility insurance mandate. In this paper, I use data from the Vital Statistics Detail Natality Data and Census population estimates to examine whether these state-level mandates were successful in increasing fertility rates. Using a difference-in-differences approach, I exploit variation in the enactment of mandates both across states and over time, and identify treatment and control groups that should have been differentially affected by infertility coverage. My results suggest that the mandates significantly increase first birth rates for women over 35, and these results are robust to a number of specification tests.