As the 2016 rates for Affordable Care Act (ACA) marketplace plans are finalized, there will be much interest in seeing to what extent premiums rise. It goes without saying that there is an overwhelming public interest in keeping these markets as competitive as possible. A large share of the total premiums is paid by the federal government. Consumers for their part are very sensitive to prices, and many report struggling with high premiums and out-of-pocket costs. Others remain outside of the marketplaces due to concerns about the price of coverage.
At the same time, in the aftermath of King v. Burwell, there is renewed discussion about the future of state involvement with marketplaces. Many predict a scenario where an even greater number of states will use the federal technology platform, either as federally facilitated marketplaces (FFM) or “supported state marketplaces” that use the healthcare.gov technology platform but conduct other plan- and consumer-oriented functions as state-based marketplaces. However, more states may begin to take an active role in plan management and market regulation.
For all these reasons, it is important to better understand how different regulatory environments may affect the functioning and competitiveness of insurance markets. In the case of rate review, a recent study suggests that pre-ACA premiums were lower in states that took a more active regulatory approach. ACA rate review grants sought to reduce regulatory variation by collectively raising the bar.
On the other hand, an NBER working paper argues that state regulatory backlash against managed care during the late 1990s increased health spending by a non-trivial amount. State regulatory action, therefore, has the potential to both increase and decrease costs for consumers.
Types Of Regulatory Variability
One place where states vary considerably is their approach to managing the participation of carriers in the marketplace. A small number of states have reserved the right to negotiate with plans before allowing them to participate in the marketplace—i.e. active purchasing—while others follow a “clearing house” model that allows all qualified plans to participate.
A related point of differentiation concerns plan design, where some states regulate the plan designs that can be offered, by requiring evidence of “meaningful difference” between plans, limiting the number and/or type of plans that can be offered, defining standard benefit designs, or some combination thereof. The case for regulating plan design is that it lessens confusion for consumers and makes it easier for them to directly compare plans. On the other hand, some argue that too much regulation may impede innovation and lead to less competitive markets.
We don’t know much about whether or how these differences affect insurance markets and consumer welfare. These are empirical questions, but this does not make them easy to answer.
A Look At The Effects Of Different Regulatory Models
The 2015 HIX Compare data provides a look at changes in silver plan characteristics. The distribution of silver plans and carriers by type of state and rating area can be seen in Exhibit 1. Looking at changes in premiums by exchange type (Exhibit 2), it appears that on average premiums rose the most in FFM states and active purchaser states, and declined most in SBM clearinghouse models. The distribution by plan standardization (Exhibit 3) shows a similar pattern, where states that did the most and states that did the least saw the largest increase in premiums, as compared with states that took one action to standardize plans.
While these data suggest that premiums increased the least in states that were moderately active in regulating the plans sold in their marketplaces, it’s very difficult to say why this may be the case. Clearly, there are many confounders. States that are active in plan management tend to be more active in other areas such as rate review, so it’s possible that effects of different state regulatory behavior may be offsetting. Further, many other factors affect premiums, including local health care prices and population characteristics.
Needless to say, these data are by no means conclusive, and are intended primarily to pique interest among various stakeholders. Soon the 2016 plans will be finalized, and this will provide new information on premium changes in states with varying regulatory approaches. At the same time, many states are contemplating new standards for network adequacy. State regulators should consider quality and access as well as affordability, but given the importance of premium prices to enrollment and retention, the impact of state marketplace regulation on competition and plan costs is doubtlessly something that should be better understood.
Table 1. Number of unique plans, carriers, and states in each of the categories described below
States were categorized based on the number of standardization policies that they have enacted. Policy options include: adopting a meaningful difference standard, limiting the number of plans or benefit designs an insurer may offer, or requiring standardized benefit designs. FFM states were categorized into the “do nothing” category with the exception of New Jersey, which was categorized in the “states that did one thing” bucket.
Table 2: Percent change in premiums between 2014 and 2015 by type of Marketplace (unit of analysis = rating area)
The unit of analysis for this table is the rating area, i.e. the dataset was condensed so that each record represented one rating area and the premium variable contained the average premium for that rating area. The table summarizes the average premium by each of these Marketplace types (where one record = one rating area) and then calculates the percent change between 2014 and 2015.
Table 3: Percent change in premiums between 2014 and 2015 by state standardization policies (unit of analysis = rating area)
The unit of analysis for this table is the rating area, i.e. the dataset was condensed so that each record represented one rating area and the premium variable contained the average premium for that rating area. The table summarizes the average premium by category of policy choice (where one record = one rating area) and then calculates the percent change between 2014 and 2015.
from Health Affairs Blog http://ift.tt/1KWsl1a
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