In Rare Turn, Competing Health Groups Agree on Drugs, Risk

The Department of Health and Human Services. (Rob Kunzig/Morning Consult)

The strange dance between the pharmaceutical industry, insurers and the Obama administration has taken a new turn. When it comes to one of the wonkiest healthcare policies out there, all three seem close to agreement. They want prescription drugs to be included in determinations about whether a certain pools of patients are riskier than others.

The determinations are important because insurers who take on riskier sets of patients are eligible to receive compensation under Obamacare. Right now, those determinations are made using just medical claims. Drug companies and insurers generally agree that prescription drugs should be included in the risk adjustment models. They currently are not.

On Thursday, the Centers for Medicare and Medicaid Services will hold a meeting on risk adjustment after issuing a white paper on the topic last week.

How risk adjustment is designed gets into the weeds of the health care policy, but the details can have a major impact on new insurance markets. The risk adjustment tool is intended to protect insurers that are participating in risky individual and small group markets from bad guesses about the health of their enrollees, which causes them to lose money.

“Risk adjustment is very important for stabilizing the market and making it an attractive place for health plans to sell insurance. Currently in Washington, there’s a lot of concern about the stability of exchanges,” said Caroline Pearson, senior vice president at Avalere Health, an independent consulting firm.

Avalere released its own study supporting the inclusion of drug data in risk adjustment shortly before CMS released its white paper.

The administration has yet to state a firm position on whether prescriptions should be included in risk analysis, and its white paper discusses both potential concerns and benefits of including drug data.

Still, CMS’ early statements are encouraging. “Based on the research performed so far, we believe that a hybrid model that includes prescription drug data in the HHS-HCC risk adjustment framework deserves consideration,” CMS concludes.

Drug and insurer groups are more firmly in support.

“Improving risk adjustment by including data on whether beneficiaries are using certain classes of medicines could better compensate plans for taking on higher risk patients and so allow these plans to focus on helping patients manage their chronic conditions in a way that avoids costly complications,” said Allyson Funk, a spokeswoman for the Pharmaceutical Research and Manufacturers of America.

PhRMA suggested that risk adjustment models include prescription drugs in a set of policy recommendations released earlier this month. Doing so could discourage “adverse tiering,” a practice in which insurance companies place all medications for a certain disease on the highest cost-sharing tier of a plan.

America’s Health Insurance Plans, not always in agreement with PhRMA, has also voiced its support for including prescription drugs in risk adjustment. Such data is “an important source of clinical and diagnostic information that is not always captured through medical claims,” the group says.

Risk adjustment programs transfer funds from insurers with healthier enrollees to those with sicker enrollees. The idea is to incentivize insurers to offer plans that are attractive to sick people. Without such programs, insurers are more likely to tailor plans that cater to healthy people.

The tricky part is deciding how to calculate an enrollee’s risk. Currently, the formula used takes into account enrollees’ medical diagnoses, but not the prescription drugs they are taking. The average health score of a plan’s total enrollees is used to determine the overall plan’s risk. If a plan’s enrollees are sicker than average, the plan will receive additional funding under the law.

The CMS white paper concluded that information about the drugs that patients are taking could help plans determine more accurately how sick a person is and the severity of any diseases they have. But only to a point.

For example, if a patient with diabetes signs up for an insurance plan but doesn’t see a primary care physician immediately, the insurer might not know the patient has diabetes. This would result in an inaccurate risk score for that person. But the patient would presumably continue to take insulin over the same period of time, a clear indication of the disease. In this scenario, prescription drug data would more accurately portray the risk of this particular enrollee.

On the other hand, CMS officials are worried that including prescription drugs in risk models could create incentives for insurers to game the system to receive more money. If a plan’s patients are on more expensive medications or are being prescribed drugs as a treatment over other alternatives, insurers would receive more money. This could encourage excessive prescribing or choosing more expensive drugs. In some cases, it can also be difficult to determine what a particular drug is being used for if it has multiple uses.

The administration has a vested interest in getting risk adjustment right. Several insurers have had a rocky start on Obamacare’s exchanges. Several have cited financial losses, and more than half of the nonprofit co-op insurers created under Obamacare have failed. This is in part because the newly covered enrollees were sicker, thus cost more, than insurers expected.

The risk adjustment program is supposed to solve this exact problem. The goal is to create stability on exchanges regardless of the distribution of sick people. If it works, insurers, in theory, would be more willing to participate in the market and increase competition, which in turn could incentivize them to offer benefits that help less healthy people.

“There’s been a lot of concern around the benefit designs in the individual market,” Pearson said. “You want to make sure plans have an incentive to cover both healthy people and sick people fully.”

Morning Consult