It seems like only yesterday that we were counting the days until school let out for the summer (or at least our kids were). Now, August is upon us. In our world, that means not just back-to-school shopping but also planning for open enrollment.
As we think about what’s coming for group health plans in the year ahead, math looms large. Financial analytics are a big part of open enrollment planning every year. But for 2023 specifically, due to recent regulatory changes to the Affordable Care Act (ACA) affordability threshold calculation and quantitative treatment limitation (QTL) calculations under the mental health parity rules, math is more important than ever.
Here’s why we are explaining to our children that, yes, in fact, there are REAL WORLD applications for what they are learning in math class. (The member of this duo who still sometimes counts on her fingers and claims her children’s algebra classes give her PTSD is explaining the applicability in a pained voice, but she is making the point nonetheless!)
It’s not often that the IRS shocks us. We’ve been at this job a while and we like to think of ourselves as unflappable. But when the 2023 cost-of-living adjustment to the ACA affordability threshold was recently announced, you could have knocked us over with a feather. For plan years beginning in 2023, this threshold DROPPED from 9.61% to 9.12%. Instinctively, it’s crazy that in a time of high inflation we see an inflationary factor going down instead of up. But, this makes a little more sense when realizing that the IRS is essentially stating that individuals have less money available now to pay for their health insurance and responding by saying therefore applicable large employers (ALEs) will need to pay more.
As a reminder, the ACA requires ALEs (those averaging 50 or more full-time employees in the prior calendar year) to provide affordable, minimum value health coverage to their full-time employees or pay a tax penalty. Affordability for this purpose is measured based on whether the total cost of the least-expensive employee-only plan option exceeds 9.5% (as adjusted for inflation) of the employee’s household income. Since employers don’t know the details of their employee’s household income, the IRS established safe harbors. Each of these safe harbors is keyed off that 9.5% affordability threshold, so the lowering of the threshold to 9.12% has our attention because each ALE’s share of the total cost of coverage will need to go up to maintain affordability in 2023. As health care costs continue to rise dramatically, this means on a national basis employers’ costs will grow at an even faster pace.
Considering this change, employers and their advisors will need to pay extra-special attention to the numbers when developing their premium contributions for 2023. The .5% drop in the affordability threshold may motivate more employers to “roll the dice” and not offer coverage at a rate guaranteed to shield them from tax penalty liability. Employers often deploy this strategy when they believe they will end up spending less on ACA penalties for not offering affordable coverage than they would on paying for their share of that coverage. This has historically worked well for some entities because, unlike the penalty for failing to offer coverage, the penalty for failing to offer affordable coverage is assessed on a person-by-person basis and only triggered when an employee ends up purchasing government-subsidized coverage through an exchange.
If a business is risk-averse or just does not want to offer “unaffordable” coverage to its eligible employees, the employer still needs to pay more attention than normal when establishing how much they versus their employees will pay towards monthly premium costs for the single-employee premium. The 9.5% affordability benchmark normally goes up a bit each year, so lots of employers and their advisors have come to rely on 9.5% as a rule of thumb when setting premium rates before open enrollment because, in a normal year, plugging in that number gives the employer a bit of wiggle room. This year, to have the same degree of confidence that their premium rates will always meet the “affordability test,” an employer will want to use 9% as their benchmark.
It is also worth noting that because of the recent extension of expanded ACA premium tax credit subsidies, as well as the potential of the “family glitch fix,” more employees than ever may take government subsidies towards coverage through an exchange in 2023. Given that eligible employees with premium tax credits are what triggers the employer penalty for offering unaffordable coverage, we are pretty sure we know what’s triggering all those dreams about showing up for a calculus exam without having ever gone to class.
Speaking of showing up unprepared for the test—we recently saw our first Department of Labor general health plan audit letter asking for a copy of a plan’s quantitative treatment limitation (QTL) analysis as required by the Mental Health Parity and Addiction Equity Act (MHPAEA). No typo there—the DOL is now asking plans to demonstrate their compliance with the QTL rules, in addition to the non-quantitative treatment limitation (NQTL) MHPAEA rules. Admittedly, we are pretty obsessed with mental health parity compliance. We’ve written about it here and here and here. But, that focus hasn’t always extended to QTLs, quite frankly because no one seemed to be looking at those other than eyeballing plan-level cost sharing and deeming it “okay.” In fact, until last year, at least one of us firmly believed a QTL analysis could be performed by simply reviewing a plan’s benefits structure. (Spoiler alert…she was wrong.)
The final regulations implementing the QTL rules were published back in 2013. At the time, most of the industry was focused on implementing the ACA, and, as the whole NQTL debacle has shown, not much attention was paid to mental health parity. In addition to spelling out the rules for the NQTL analysis, the final regulations also enumerate the process for testing quantitative treatment limits. Like NQTLs, this analysis is done in six basic categories: (1) inpatient in-network, (2) inpatient out of network, (3) outpatient in-network, (4) outpatient out of network, (5) emergency care, and (6) prescription drug. Unlike NQTLs, plans can break down the outpatient categories to consider office visits separately from other outpatient services.
Within each of these categories, plans must first determine which types of quantitative treatment limitations apply to “substantially all” or 2/3 of medical and surgical benefits within that category. For this purpose, plans consider types of QTLs rather than the level at which the QTL applies. As an example, coinsurance is a “type” of QTL, whereas 20% coinsurance is a “level.” If a type of QTL applies to substantially all claims in a given category, then that type of QTL may be applied to mental health and substance use disorders in that category. Then, the plan needs to ensure that the level of any QTL that applies to any mental health or substance use disorder benefit applies to at least 50% of the claims in the corresponding medical/surgical category.
To make matters more complicated, to calculate the value of claims attributable to any QTL for this purpose, the plan needs to count any claim to which a given QTL might apply—not review how claims were actually adjudicated. We like to explain it this way: say a member goes to the doctor, and the allowed amount for the office visit is $200. Under the member’s plan, a deductible applies, after which the member must pay coinsurance unless that member has reached their out-of-pocket maximum. In this case, the member doesn’t have to contribute anything. When performing a QTL analysis, the $200 allowed amount would be included in the claim’s calculation for all three types of QTLs: the deductible, coinsurance, and out-of-pocket maximum. This means most existing claims reporting systems can’t perform the needed calculations and specialized solutions need to be built to complete the analysis. Those systems require a lot of logic (and math) to build—trust us, we’ve been working so hard at building one that we recently hired a new MZQer with a Ph.D. in Math. (Seriously, he starts at the end of August, and we can’t wait…)
Ultimately, the results of the QTL testing are needed to finalize the plan design. If a plan sponsor doesn’t know if a QTL is permitted, they can’t ensure their design for the next plan year complies with the mental health parity rules. So, this is one more set of calculations we strongly recommend performing annually before open enrollment, especially since the DOL is now paying close attention!
Well, friends, tell us, are you “math people”? Do all these numbers sort of excite you or send you running for cover? In either case, we’ve got your back and are here to help!!
