The Effects of Federal Parity on Substance Use Disorder Treatment | Page 2
Published Online: January 23, 2014
Susan H. Busch, PhD; Andrew J. Epstein, PhD; Michael O. Harhay, MPH; David A. Fiellin, MD; Hyong Un, MD; Deane Leader Jr, DBA, MBA; and Colleen L. Barry, PhD, MPP
We examined 3 HEDIS-based SUD performance measures. We measured identification as the share of all health plan enrollees who had a new SUD claim within a calendar year. New treatment episodes were those with no SUD treatment during the prior 60 days. We measured treatment initiation as the share of enrollees with a new episode of SUD treatment who initiated treatment within 14 days of their initial diagnosis. Following HEDIS, all patients for whom identification of SUD occurred through a hospital admission were considered to have initiated treatment, but inpatient detoxification services were not considered treatment initiation. We measured treatment engagement as the share of enrollees with a new episode of SUD treatment who received at least 2 SUD services within 30 days of their initial diagnosis. For the treatment engagement measure, multiple services could not occur on the same day. To ensure that we were identifying only new episodes, we did not consider episodes that began during the first 60 days of the calendar year. For both the initiation and engagement measures, we omitted episodes that did not allow for a 30-day follow-up (ie, those that occurred late in the year).
Our explanatory variables were indicators for whether an observation occurred after federal parity implementation (ie, in 2010) and whether the individual was enrolled in a plan newly subject to parity (ie, a self-insured firm). We also controlled for enrollee sex, age (ie, age 18-31, 32-46, 47-62 years in 2009), and state.
We estimated the effect of federal parity using a difference-in-differences model. For binary outcomes we used logistic regression. For spending outcomes we used a 2-part model to estimate the probability of any SUD use and then estimated spending conditional on any use using a generalized linear model with a log link and gamma distribution, as indicated by the results of a modified Park test.18 To estimate the relationship between parity and share of total spending paid out of pocket, we estimated a fractional logit model, which was implemented as a generalized linear model with a logit link and binomial distribution.19 To facilitate interpretation, we transformed relevant coefficients to the original scale of the outcome using the method of recycled predictions. We calculated confidence intervals using a nonparametric block bootstrap method that accounts for repeat observations for individuals.20 This study was exempted from review by Yale University Institutional Review Board.
We compared characteristics of the self-insured treatment group and fully insured comparison group enrollees in 2009 (Table 1). Self-insured enrollees were significantly more likely to be female and younger, although these differences are not large enough to be clinically meaningful. Although differences were small in absolute terms, self-insured enrollees were 57% more likely than fully insured enrollees to have an SUD diagnosis (1.1 % vs 0.7 %).
Table 2 reports difference-in-differences estimates for the probability of use of SUD treatment and total spending on SUD treatment per enrollee. After accounting for secular trends in the use of SUD treatment, we found no significant difference in the probability of using SUD treatment attributable to MHPAEA. We did find a significant increase of $9.99 (95% confidence interval [CI], $2.54-$18.21) in total spending on SUD treatment per enrollee attributable to MHPAEA, compared with a base rate of $36.51 in the self-insured group. We found no significant difference in total spending on SUD treatment per user, although the point estimate was relatively large ($608). Table 3 indicates that we detected no effect of MHPAEA on out-of-pocket spending on SUD treatment or proportion of spending paid out of pocket among users.
Table 4 summarizes the effects of MHPAEA on the HEDIS- based identification, treatment initiation, and treatment engagement performance measures. We found no significant effect on identification of SUD, treatment initiation, or treatment engagement associated with implementation of MHPAEA.
This study is the first to examine the effects of MHPAEA on SUD treatment use and spending. The new law led to a significant increase in SUD spending of $9.99 per health plan enrollee. The average cost of an employer-sponsored individual health insurance policy in 2010 was $5049,21 suggesting this is a negligible increase. During the congressional debate over passage of MHPAEA, employers and health plans raised the concern that the law would greatly increase healthcare spending.22 This study suggests that, at least related to SUD treatment, this concern was unfounded. Once a controversial and much debated issue, the inclusion of SUD services in parity appears unlikely to affect either health plan profitability or overall rates of insurance coverage.
That we found no change in out-of-pocket SUD spending suggests federal parity did not lead to increases in financial protection for SUD treatments. This result is surprising given data indicating that higher cost sharing for SUD services was common prior to MHPAEA.2 Under parity, 2 potentially offsetting changes to out-of-pocket spending might be expected. First, equalization of cost sharing between general and medical care services might lead to lower cost sharing for SUD services and thus reduce out-of-pocket spending. Second, increases in the number or intensity of services due to reduced out-of-pocket price or elimination of treatment limits might lead to increases in total costs and total out-of-pocket spending. To shed light on the relative importance of these competing effects, we examined the proportion of total costs paid out of pocket. If cost sharing were declining, we would expect the proportion of total costs paid out of pocket to decline as well. That we found no change in the proportion of total costs paid out of pocket suggests that the elimination of treatment limits may be an important cause of increased spending. This would be the effect expected if increases in treatment expenditures result from the elimination of day or visit limits rather than reductions in cost sharing.
We also note that our data included claims for SUD treatments paid for by private insurance. If MHPAEA resulted in a switch from SUD services self-financed by families to services financed by insurance, out-of-pocket spending reported in claims might have increased, but actual out-of-pocket spending by SUD treatment users might have declined. We found no significant increase in SUD identification, treatment initiation, or treatment engagement after parity implementation. We note that these measures only captured whether individuals were more likely to begin treatment and did not measure the duration or the intensity of treatment. Although not definitive, that we found increases in SUD total expenditures of 27% (an increase of $10 with an initial expenditure of $37 per enrollee for the self-insured group, as indicated in Table 2) without similar increases in identification suggests there were increases in treatment duration or treatment intensity after MHPAEA implementation. The point estimate of total spending per SUD treatment user suggests an increase in yearly total spending of approximately $600 per year, although this finding is not statistically significantly different from zero due to imprecision in the estimate caused by the relatively small number of SUD treatment users in our sample. In these data the payment for a physician visit for SUD treatment of low to moderate intensity was approximately $70, suggesting this increased spending may yield 8 additional visits for SUD treatment. Treatment increases may be an important benefit of parity given the level of unmet need associated with SUD and evidence that treatment provides important benefits and reduces social costs.23
Understanding the effects of MHPAEA on SUD treatment is critical because provisions of the Patient Protection and Affordable Care Act will extend the law to the individual and small group insurance markets under state and federal health insurance exchanges beginning in 2014. Substance use disorder services are required as part of the essential health benefit under the Affordable Care Act, although states may differ on the scope of SUD benefits covered.
Strengths of this study include the use of a comparison group to control for secular trends in SUD treatment use, geographic heterogeneity in the study population, and detailed SUD treatment use and spending data. Like all studies, our research is limited by the type of data considered. These data did not include patient interviews or medical chart reviews to confirm information regarding diagnosis or services received, or information on treatments not financed by insurance. There is little reason to expect that these data limitations differentially affected the intervention and comparison groups, suggesting our estimates of changes in use and spending were unbiased. Yet if providers systematically changed recorded diagnoses in response to parity (due to increased coverage for SUD treatments), our results would be biased. In addition, we found little difference in reimbursement levels between the self-insured and fully insured groups.
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