Plan groups were then compared in 2009 and 2014 and were further categorized based on change in out-of-pocket cost over time. Nine categories represent each of the possible patterns over time. For each plan type in 2009 (no, low, or high out-of-pocket cost), three categories were created based on change from 2009 to 2014: one for no change and two for change to either of the other cost levels. For example, one group is defined by plans with high out-of-pocket cost in 2009 that changed to having low out-of-pocket cost in 2014 (Table 3).
Patient out-of-pocket cost by year stratified by plan category was summarized using descriptive statistics. A generalized estimating equation was used to model the average proportion of women within a plan with IUD utilization in 2009 and 2014. The model accounted for the dependence resulting from repeated measures per plan and was fit with a Gaussian distribution, an identity link function, and an exchangeable correlation structure. Robust standard errors were obtained to produce valid standard error estimates even if the within-plan correlation does not match the model-specified correlation structure. The primary variables of interest were the plan category, the claim year, and the interaction between plan type and claim year. Additional plan time-varying controls included the plan proportions of those within 400% of the federal poverty line (low income), the plan proportion of those with a race identified as Caucasian or white, and the plan proportion of those aged 41 years or older. Model-based marginal effects were obtained and represent the average predicted level of IUD service utilization within a plan by plan categorization (Table 4). A P value of .05 was considered significant. All analyses were performed using Stata 14.
We identified 1,420,954 women between the ages of 15 and 45 years with at least 12 months of continuous enrollment in 167,964 employer-based health plans (Table 2). Of these plans, our analytic sample consisted of 1,930 plans that were used for IUD services in both 2009 and 2014. These plans included 543,499 women, the majority of whom were Caucasian or white (67%) and with higher income (greater than 400% of the federal poverty level, 58%) (Table 2).
Across all plans and plan categories that used new IUD devices in 2009 and 2014, there was a small but significant increase in average plan-level IUD insertions (12.5%, 95% CI 11.6–13.4% vs 13.8%, 95% CI 13.0–14.7%, P<.001). By categorizing plans based on their out-of-pocket cost pattern over time, we examined this overall change in more detail and found differences between categories in average plan utilization over time. Of the 1,930 plans that were used for IUD insertions in both 2009 and 2014, 49.7% of plans went from low out-of-pocket cost to no out-of-pocket cost, 15.3% of plans went from high out-of-pocket cost to no out-of-pocket cost, 14.5% of plans had no out-of-pocket cost in both years, and 0.8% of plans had high out-of-pocket cost in both years. Each of the remaining combinations represented fewer than 2% of plans and thus were omitted for clarity. Two percent of plans continued to have out-of-pocket costs after the contraceptive mandate in 2014, which is consistent with the number of plans that continued to have grandfathered status at that time.16 In models predicting the probability of IUD insertion by plan category, while controlling for race and poverty level, plans that changed from high cost to no cost increased their use for IUD insertions at the highest rate (3.6%), whereas use among plans that remained no cost did not significantly change (Fig. 3). After controlling for plan levels of poverty along with racial and age compositions, plans that went from high out-of-pocket cost in 2009 to no out-of-pocket cost in 2014 saw a significantly higher average increase in the average level of plan IUD utilization over time (2.4%, 95% CI 0.04–4.5%) compared with plans with no out-of-pocket cost in both 2009 and 2014 (−1.0%, 95% CI −3.3 to 1.4%, P=.02).
Among all plans with out-of-pocket costs for IUD placement, the 75th percentile of out-of-pocket cost in 2009 was $368. By 2014, this number dropped to $0 (Fig. 2). Before the implementation of mandated coverage in 2012, deductible payments appeared to account for much of the observed out-of-pocket cost above the 75th percentile.
Our examination of the effect of the contraceptive mandate of the ACA on a national sample of women in employer-based health plans indicates that full coverage of contraception has successfully led to an increase in the proportion of patients with no out-of-pocket cost for IUDs. We found that elimination of out-of-pocket cost for IUD placement occurred quickly after mandated coverage. Our findings suggest that baseline levels of out-of-pocket cost may help identify groups with unmet demand for IUD placement before mandated first-dollar coverage. Those with the highest out-of-pocket cost at baseline (who are often in high-deductible health plans) saw the largest decreases in out-of-pocket costs and also demonstrated the steepest increases in IUD insertions after elimination of costs. This finding has important implications for the conduct and interpretation of studies on contraception coverage under health care reform.
Some prior studies reported that the implementation of the ACA has had little to no effect on use of IUDs.11,12 Our study adds more nuanced information on the effect of cost sharing on IUD utilization by accounting for baseline out-of-pocket cost. By grouping plans based on out-of-pocket cost before and after mandated coverage, this analysis demonstrates that 1) most commercially insured women already had low or zero out-of-pocket cost and 2) the elimination of out-of-pocket cost for the smaller group of women in plans with high baseline costs was associated with a greater increase in IUD placement. This finding aligns with the large body of existing literature before the ACA, suggesting a strong inverse association between out-of-pocket cost and IUD use.9,10,17 Prior studies on the effect of the ACA on IUD insertion did not account for the fact that most women in these types of health plans already had low out-of-pocket cost and likely little unmet demand as a result of costs. Based on our findings, we recommend that these studies of service utilization after the elimination of out-of-pocket costs should account for baseline costs.18
Despite mandated coverage of contraception, IUD utilization remains low for patients seeking contraception. Beyond reducing out-of-pocket cost, it is important to consider other factors that may represent barriers to IUD insertion such as availability of same-day IUD insertion at outpatient clinics and a sufficient supply of trained health care providers.19–22 Additionally, our findings should be interpreted in light of limitations common to large employer-sponsored insurance claims databases. The sample is drawn from a pool of women with employer-sponsored coverage, which represents approximately 66% of U.S. women; findings may therefore not be generalizable to women with public insurance, no insurance, or marketplace plans. These data rely on coding generated for billing insurance and thus may not capture every IUD insertion (We would not identify IUD insertions that occurred out of plan or if the plan offered no coverage). Conversely, the accuracy of a paid claim for IUD insertion is high. Furthermore, plans used in this analysis had to be used in both 2009 and 2014 for IUD insertion, which limits the number of plans available to be analyzed and could overrepresent plans with above average utilization. Finally, it is also worth remembering that IUD placement and contraceptive use are only intermediate outcomes to the health outcome of interest—unintended pregnancy. Given the well-demonstrated strong association between use of highly effective contraceptives such as IUDs and prevention of unintended pregnancy, IUD insertion is a well-accepted proximate determinant of unintended pregnancy.
This study has several strengths. First, this analysis demonstrates a novel approach to examining the effect of mandated full coverage of contraception use by demonstrating the importance of accounting for baseline costs. Our findings may also have implications for studies that seek to evaluate the effect of out-of-pocket cost changes on women's use of other preventive health services.
Aggregate analyses of utilization may miss changes in important subgroups of women because of large variations in out-of-pocket cost at baseline and subsequent variation in unmet demand. Moving forward, studies that examine responses to changes in patient out-of-pocket cost over time should include baseline cost in their analyses.
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© 2018 by The American College of Obstetricians and Gynecologists. Published by Wolters Kluwer Health, Inc. All rights reserved.
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