You probably know that medication adherence measures are one part of CMS’s pay-for-performance Star Ratings system, but they play a critical role in a health plan’s ability to earn 4+ Stars – the coveted threshold which rewards payers with a higher proportion of premium dollars, quality-based bonuses, and opportunities to increase market share. Not only are the three Star medication adherence measures – diabetes, hypertension, and cholesterol – triple weighted, they also impact several of the Part D measures and some of the disease management measures in Part C. In fact, based on 2018 Star Ratings, 37% of Star Rating performance was influenced by proper prescribing and medication adherence, and more than 70% of plans that achieve 4+ Stars overall also earn 4+ Stars on all three medication adherence measures. This means that if you want to be a high-performing Medicare Advantage plan, medication adherence is a great, high-impact place to focus your efforts.
As we’ve helped health plans improve their medication adherence programs over the last six years, we’ve developed (and formalized) a framework that helps us drive successful Star Ratings program strategy: targeting, timing, scale, and effectiveness. Read on to understand why it helps to think about programs this way, and how our solution and client services teams use this framework.
Once the plan has determined which resources will be dedicated to the outreach initiatives, targeting is critical. It isn’t practical to contact every member in the population. By focusing target on member populations whose adherence habits are still undecided, intervention has the most impact. The key is to determine:
- Which members can benefit from the intervention?
- Which members are actionable?
- Which members can be made adherent?
With a proven predictive analytics platform that prioritizes members by adherence risk, receptivity to outreach efforts, and urgency of action, health plans can effectively determine who best to target.
The timing of the interventions must be considered. Unlike other quality measures, where there is often a push towards the end of the year to fill gaps, medication adherence is more complex and must be evaluated throughout the year to ensure goals are met. Members can appear to be adherent for the rest part of the year until suddenly in September or October their status changes to non-adherent, and the plan may have missed the opportunity to intervene. A predictive analytics solution that identifies members before they become non-adherent increases health plans’ effectiveness of their medication adherence programs.
In addition to understanding how many plan members must be impacted in order to reach adherence goals, health plans must evaluate both internal and external intervention resources compared to program requirements. If internal teams are being used for outreach, finite resources such as workforce capacity, call center volume, and training expertise must be considered. If using external resources, the plan must evaluate vendors’ solutions and capabilities, compare cost-effectiveness, and ensure the vendor has scheduling availability and capacity.
Health plans can achieve scale when they have access to a simulation model, based on actual health plan conditions, to strategically guide targeted outreach efforts.
With the intervention mix chosen and the targeted population selected, the health plan must next decide on the intervention mode that will be most effective for a specific member. By creating a profile for the member using key pieces of data – from complexity of their medication regimen to behavioral issues that might influence adherence – health plans have a specific way to evaluate each member as to the most appropriate outreach method and actually affect member behavior. One intervention method is an integrated contact center to perform targeted member outreach.
We describe this framework further and detail a case study on how it works with UPMC Health Plan in our latest whitepaper. You can find it here.