Oscar Health Insurance burst on the payer market in July 2013 and by April 2015 the company was valued at 1.5 billion dollars. However, in March of this year, Oscar revealed it lost over 100 million dollars last year.

While the news about Oscar may make the biggest splash, the heavily touted startup is not alone in reporting losses. Large, well-established health insurance companies are finding it difficult to be profitable. Most of the losses occurred on the Affordable Care Act (ACA) exchanges where United Health Group lost more than 720 million dollars last year and Blue Cross Blue Shield drained more than 650 million dollars from its reserves.

Additionally, of the 23 consumer operated and oriented plans created by the ACA, 10 have failed or announced they will not offer policies in 2016 due to financial hardships. 

Through the exchanges, these companies were flooded with new members who were sicker than expected and drove healthcare costs up. The ACA’s medical loss ratio (MLR) rule states that at least 80 percent of member premiums must be spent on health care claims and quality improvements. However, for many payers, their ratio was off and they were not prepared to cover these high costs.

But not all companies are feeling the crunch. For example, GlobalHealth, a regional payer in Oklahoma, has found a way to decrease its MLR and improve its offerings to members through the use of a predictive and prescriptive analytics program.

“GlobalHealth is very innovative health plan,” said Jay Reddy, president and CEO of VitreosHealth, the population health analytics company that partnered with GlobalHealth. “They use predictive analytics to understand the drivers of population risk at the local level, then develop customized, high-touch care management programs to reach specific high risk members before costly events occur.”

“We have an initiative in place this year where we want to reduce our healthcare costs by 10 percent,” said Scott Vaughn, CEO of GlobalHealth. “With the data we get from VitreosHealth, we can predict 70 percent of our hospital admissions. Through our outreach program we’re improving health outcomes and reducing costs.”

Discover how predictive analytics can help produce a comprehensive, 10 percent MLR reduction program – click here.

Losses Due to a Sicker Population Than Expected

The share of Americans without health insurance has dropped to a historic low of about 9 percent. However, many payers were caught off guard when a sicker than expected population filled the ACA exchanges.

Because the ACA limits information that insurance companies can collect about potential members pre-existing conditions, (to ensure members are not rejected based on prior conditions) most new members acquired through exchanges have been high risk and high cost.

The result is that the ACA exchanges have created a marketplace where payers are competing for new members by offering lower premiums without a thorough understanding of the risk potential of new members resulting in a very high MLR.

The Solution – Local, Data-Driven Plans

“Leveraging predictive analytics to risk stratify the new membership can be the answer these companies are looking for,” said Reddy. “Once they gain a better understanding of their new members, they can develop customized, proactive outreach care management programs to improve clinical outcomes and lower the cost of care.”

According to Reddy, one of the reasons a company like GlobalHealth is able to provide comprehensive services to its members while operating at a profit is because their analytics program provides insights that otherwise would have gone unnoticed until too late.

“Healthcare in this new operating environment has to be local,” said Reddy. “Generic care-delivery programs that are driven by corporate headquarters of large health plans are a mile-wide but inch-deep and don’t deliver results. Health plans that are local – ones that go beyond the clinical drivers of its members to understand the non-clinical drivers – and are data driven are better equipped to develop and deliver customized, high-touch, proactive care management.

“Plans that leverage predictive analytics for clinical risk management can identify high-risk members at the health risk assessment stage. Then, with a carefully developed proactive care plan, they can avoid negative and costly outcomes like hospitalizations and ER visits.”

A company will have to be nimble. Succeeding in this current market requires a willingness to transform away from an outdated operating model.

“Healthcare doesn’t have to be expensive to be good,” said Vaughn. “If we can improve the health of our members then the cost will go away. Both the costs that we’re incurring as a health plan and the costs that members incur through copays.”

To learn how predictive analytics can help reduce MLR, click here.

Payers are Hemorrhaging Money – Can Predictive Analytics Stop the Bleeding?

Leave a Reply

Your email address will not be published. Required fields are marked *