When it comes to national news, health exchanges may be taking a backseat to the political tumult surrounding them, but few questions have been answered yet as far as health insurers are concerned. Despite the fact that consumers are finding at least four options in most states, many insurers, particularly large ones, remain cautious about entering exchanges, where we don’t know who the insureds or the standard rates will be. Many insurers are considering whether to join exchanges on a very selective, state-by-state basis, according to Qasim Hussain, a health insurance consultant with X by 2.
What we do know is consumers continue to log on, make a choice and leave a very valuable, and hopefully reliable, trail of information, meaning data and predictive analytics will be the backbone of many business and technology decisions health insurers will make in 2014 - 2015.
“Right now, I see a lot of insurers doing predictive analytics to try to see what the risk is going to look like, but they want to know more actual numbers before they want to get started,” Hussain said,. This lack of data is causing many insurers to wait on the sidelines, but there are insurers that see opportunities to gain market share by diving head-first into uncharted waters. “One insurer that was pretty much nonexistent came out with very low pricing on some of the plans to gain market share. So they know that they’re probably losing money on that, but this is opening up an opportunity for others to come in and gain some foothold.”
Analyzing consumer and competitor data is only one of three data-related essentials that health insurers considering, or already competing in, health exchange markets need to be proficient at. Health insurers are also aware of Edge Servers, the IT hubs of the Affordable Care Act (ACA), which insurers need to become compatible with for submitting data as well as processing heretofore unseen subsidies and discounts.
“When [insurers] are signing up for exchanges, there are a lot more calculations. The systems that handle enrollment and claims payment, they weren’t designed to handle these, so there was a lot of work even earlier this year and it’s still going on. A lot of large insurers have very old mainframe membership and claims processing systems, and it’s harder to modify them to accommodate these new subsidies,” Hussain said.“Insurers are also submitting data to the federal government for revenue management and risk assessment. The federal government is still trying to figure out how the data will be submitted, how the risk will be calculated, and all that will start to gain more traction earlier next year when people start using the insurance and claims are generated.”
The data collecting is part of establishing the foundation for federal risk adjusting: insurers submit data to the government, which calculates how much premium insurers have collected, how much they have paid in claims, and determines whether a company is making or losing money. Based on that formula, Hussain explained, it’ll look at the insurers in a given market and tell a company that’s making a lot of money to pay X amount to an insurer that is losing money. This would take away some of the benefits of cornering the best risks in the market, which would likely flock to larger insurers, while bigger risks may be likely to take the cheapest option; risk adjustment is designed to keep this playing field more level, at least that’s the theory behind it.
“This formula that’s supposed to figure it all out is still being worked on, while insurers are trying to do their own internal predictive analytics to see what trends are going to be like. The emphasis I’ve seen on the larger insurance side is that as much as it is about getting new people, it’s also about having all the data you need for the population,” Hussain said.
Indeed, the exchanges are forcing insurers to tighten data operations, which is why data integration is the third tech-related necessity for health insurers. For example, Hussain pointed out a shift in obtaining prognoses from doctors regarding insureds where insurers used to only care about procedures, they must now take pains to build prognoses into the data gathering and modeling processes.
“Both business and tech processes are being put in place to make the integration of data more seamless so that insurers can get as much data as they can to do their predictive analytics, get their data to the government to accurately represent the risk population that they’re covering, and make sure they get a part of the pie that’s going to be X revenue generated,” Hussain said. “Insurers typically have a lot of data, but, at least a lot of larger insurers I know don’t have the data aggregated in one consolidated place, which would make it easy to submit to an external entity. They didn’t have to do that. They didn’t have to submit this claims or membership data to the federal government. Trying to pull all of that data from various systems, putting it all in one place and sending it out, it’s a challenge. You need to build IT processing systems that can aggregate all of it and send it out. They’re all trying to figure out how they’re all going to get there.”
Lastly, all of that data work may go unappreciated if a health insurer can’t price with precision. Insurers no longer have the privilege of getting to know consumers before providing a policy or pricing the risk; potential insureds may only be exposed to a lineup of price tags before making purchases. This presents yet another data challenge: “Everybody is searching for the magic price point, so a lot of analytics are happening. They’re already starting to think, what data do we need to collect, what type of analytics do we do to figure out the best prices? Because the data will start flowing in but you need to have means to capture and store it so you can do that type of analysis,” Hussain said. “Insurers have not typically had to react this fast. That’s what’s making people excited and nervous at the same time.”
Justin Stephani is associate editor for Insurance Networking News.
Readers are encouraged to respond to Justin by using the “Add Your Comments” box below. He also can be reached at firstname.lastname@example.org.
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