Making decisions with incomplete information can be a fact of life for anyone – personally or professionally. That being said, the degree of information that plan sponsors, particularly large ASO plans, are afforded to make critical benefits plan decisions that impact millions or tens of millions of dollars of annual investment almost borders on comical at times. It makes you wonder how that’s even allowed to happen with so much at stake.

The good news is there’s more information available that’s vital to providing a much clearer picture of both the current experience and what is likely to happen moving forward. The bad news is it’s very easy to draw the wrong conclusions from incomplete information currently provided as a standard, conclusions that can put the plan in a much worse position moving forward.

Read: A New Year’s resolution conversation for ASO plan sponsors

Here are some examples of how incomplete information is creating problems for plan sponsors, as well as how more complete information is being harvested and what plan sponsors are doing with it.

1. The deception of proportion and comparative trends. 

This is a common problem for plan sponsors. Given that most plan information provided is at an aggregate level (i.e. not assessed at the transactional or claimant level), two of the few measures that can be assessed in superficial reporting are proportional comparisons and high-level trends.

Example of a recent situation: 

Plan experience information provided by a vendor focused on proportional changes across different benefit lines and comparative trends year-over-year (YOY). This is a critical period for the plan sponsor – it is into collective bargaining and needs to understand how to best proceed with responsible plan change.

The result: 

If you look at YOY changes in spending across different benefit lines on a percentage basis only, you can draw the wrong conclusions. When some of the paramedical lines are trending with YOY increases above 30%, drugs seem like they aren’t an issue at all when they have a far less significant proportional increase. Proportional numbers tell the plan sponsor nothing about existing levels of impairment in the drug benefit spend and where opportunities exist to improve the experience.

Read: Drug plan trends report: How drug plans are addressing skyrocketing costs

The plan sponsor wouldn’t have seen that specialty drug spending increased by more than $400,000 YOY and could have been much higher if more than one of the estimated 22 Hepatitis C claimants in the experience had initiated therapy. The plan also has a future risk of a growth of more than $370,000 per year in specialty spending based on the current plan population. Not such a rosy picture now if everyone thinks drugs are doing well, is it?

2. The solution myth.

In fairness, it’s easy to understand why this trips up plan sponsors. Plans who have made changes and implemented solutions in recent years to address issues often feel their work is done. This happens frequently when plans implement elements such as Mandatory Generic Substitution, Dispensing Fee Caps, Prior Authorization or a Preferred Pharmacy Network (PPN).

Example of a recent situation:

A plan sponsor implemented a PPN with multiple pharmacy vendors. The plan sponsor doesn’t receive any information about how PPN is working outside of market share statistics, so there is no measurement of the value the PPN is driving and/or whether the PPN stores are working within the terms it agreed to.

The result:

This version of the PPN is a disaster. The vast majority of the participants are not providing any tangible benefits and, in fact, if it weren’t for the PDD claims pricing controls, many of the “preferred” stores would have actually been among the most expensive providers.

Read: Sounding Board: Health outcomes and personal choice collide

Everyone wants to believe once the hard work of identifying an opportunity and implementing a solution is complete that all must be well, but that can be (and often is) wishful thinking. By themselves, Generic Substitution, Prior Authorization, PPNs, tiered design, etc., are not enough – they have to be part of a fully integrated design and continue to be measured.

If a plan sponsor is going to go to the trouble of implementing solutions, why not go to the trouble of making sure it is (A) the right solution, (B) implemented properly and (C) properly measured?

3. The trouble with silos.

If you are a plan sponsor paying for multiple benefits, it sure doesn’t help when those benefit lines are not properly integrated from an information perspective. It’s a common refrain from full-service carriers that it’s best to have all benefits under one roof, but if a plan sponsor can’t take advantage of a much more in depth set of information, does this advantage still hold?

Conversely, for ASO plans that have health and dental benefits with one vendor and insured benefits with another, why give up on bringing that data together for integrated analyses? It can certainly be done, just as it can be done for a vendor that has everything under one roof. Why would any plan write off access to any of its information?

The information is there, it’s simply not being leveraged, and that means incomplete information, suboptimal strategic planning and next to no ability to measure ROI and outcomes.

Example of a recent situation:

According to one plan sponsor’s ggregate-level short-term disability (STD) data, 14.3% of employees making an STD claim in 2015 did so due to depression, while just 0.4% of employees did so due to diabetes.

Read: Can stop-loss coverage be optimized for ASO plans?

The plan sponsor was looking to find ways to become more efficient in its plan design to enable resources to be invested in managing employee health and both short- and long-term absences. These absences are a major issue for this plan sponsor.

The plan sponsor also needs to figure out where can they get the biggest bang for their investment – there is no possible way to address every area of opportunity, so what should the priorities be?

The result:

In reality, when the transactional-level drug and disability data were combined, the impact of these two conditions was very different: 38.2% of the employees with an STD claim were actively treating depression and 11.5% were actively treating diabetes. Now we have a very different perspective or “burden of illness.”

More importantly, we also have a much wider range of baseline health and financial metrics than can be used to measure return on investment (both financial and improvements in health outcomes) from initiatives undertaken to better address health and absence concerns.

Looking at the combination of co-morbid chronic diseases is allowing the plan sponsor to focus resources in very specific areas, and the baseline numbers will allow for measurement to see how the experience is being impacted. The ability to measure financial returns through targeted efforts to manage and improve health is critical to ensure sustainable funding for these initiatives.

Read: Implementing a mandatory generic policy on ASO accounts

It’s not possible to solve every problem immediately, and plans won’t always make the perfect decision(s), regardless of the information available. Life is never that easy. However, it sure is easier to make better decisions when there is more meaningful information available.

Mike Sullivan (msullivan@cubichealth.ca) is president of Cubic Health, an analytics and drug plan management company based in Toronto. Follow Mike on Twitter at @cubichealth.

These are the views of the author and not necessarily those of Benefits Canada.

Copyright © 2020 Transcontinental Media G.P. Originally published on benefitscanada.com

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