AllazoHealth’s William Grambley, Chief Operating Officer, and Dr. Linda Schultz, VP, Clinical and Customer Success, address the factors that pharmacies should consider when prioritizing their DIR contracts. Their discussion includes how to evaluate thresholds and population attribution, and how AI can optimize your DIR decisions.
What do you mean by prioritizing a DIR contract?
William: For the person that has responsibility for multiple DIR contracts, the question typically is, “Which contract do I put my resources into?” So you might have a team of 50 people that can make patient intervention phone calls, and you need to determine which contract they will focus on.
Comparing value in DIR contracts
William: A key objective is the likelihood of getting maximum value from your investment of effort. You should ask yourself, how close are you to the next threshold in the contract?
Let’s say your thresholds in a DIR contract are at 60 and 80, and you’re at 70. You’re a long way from either threshold. So it doesn’t make a lot of sense to invest a lot of effort in that contract. On the contrary, let’s say you’re at 70 and the thresholds – instead of being 60 or 80 – are 69 and 71. You have a greater chance of getting over 71. And so you would want to put more effort into that contract.
Another factor in getting maximum value is determining how much exceeding a threshold is worth. Let’s say you’ve got two contracts, and you’re 2 percentage points away from the next threshold on both. But one contract gives you an incremental $1 per claim. The other gives you an incremental $3 per claim. Of course you want to focus on the $3 per claim contract.
Relative scale contracts
Linda: Some of the contracts evaluate your performance by a relative scale, comparing you against other pharmacies. It’s a moving target. With a relative scale contract you have no clue how other pharmacies are prioritizing their efforts, let alone how they will perform. It’s like the Star metrics, where the cut points can change every single year, on every single measure, and your results are dependent on whether you’re able to outperform other pharmacies on that DIR agreement.
A majority of DIR contracts give pharmacies an idea of the goals they need to meet. But this is complicated because there are multiple measures within each contract. They can be clinical measures like medication adherence, or they can be administrative measures, such as generic dispensing rate.
Population attribution: read the fine print
Linda: Population attribution is also a factor when assessing the DIR agreements. For example a contract may say, “We will attribute the population for these adherence measures to the pharmacy that has the majority of claims for the drug this year.” But another contract might say, “We will attribute the population for these adherence measures to the pharmacy that provided the last fill of the drug this year. ”
William: So if the attribution is based on the last fill of the year for a patient, you could’ve been supporting that patient for 10 months. But if their last fill of the year is at a different pharmacy, all of your effort has just been wasted. It’s very important to look at the fine print within the contracts to see how attribution works.
How can AI optimize your DIR contract decision making?
Linda: AI (artificial intelligence) can detect the pattern of a patient’s behavior. Say that one patient has consistently used one pharmacy for three years. There is less risk of them being attributed to another pharmacy.
But let’s say you are engaging with a new patient and you don’t have access to their history. Are they likely to be a snowbird, so they get fills from different pharmacies seasonally? Or are they likely to switch pharmacies, or get prescribed new medication? For contracts that have attribution based on the last fill, AI can accurately predict whether investing resources in this type of patient population is most effective way to deliver value.
Additionally, AI can help evaluate your investment in individual measures. For instance, cholesterol versus hypertension versus diabetes. Within the claims data, AI can perceive patterns and identify specific measures where you can bend the curve more cost-effectively.
AllazoHealth uses artificial intelligence to make a positive impact on individual patient adherence. We work with pharmacies to optimize adherence programs and intervention workflows. The result: improved clinical outcomes and increased reimbursement from pay-for-performance contracts such as DIR.
Case Study: Leading national pharmacy achieves 2.3x greater uplift in patient fill rate
Learn how AllazoHealth used AI to help a national pharmacy improve cost efficiency for their patient interventions.