Direct and indirect remuneration (DIR) fees are a hot topic in the pharmacy industry, and efforts to regulate DIR fees consistently hit the headlines. Recently, the Centers for Medicare and Medicaid Services (CMS) proposed substantial changes to DIR regulations to help pharmacies offset the high costs and impact on their reimbursements.
Fortunately, pharmacies won’t need to wait around hoping proposed legislation becomes reality. Right now, they can use artificial intelligence (AI) technology to make smarter, data-driven decisions and optimize DIR contracts. Here’s how:
How do DIR fees impact pharmacy reimbursement?
Ever-rising DIR fees have a direct impact on pharmacy revenue and reimbursement. In fact, DIR fees have increased by 91,500 percent over the past decade, and many pharmacies—especially small, independently-owned pharmacies with limited resources—struggle to navigate the financial impact on their business.
There’s a lot at play here. For one, pharmacies have several DIR contracts with varying formulas and rating systems for calculating fees. Some DIR contracts focus on population-wide measurements, while others evaluate performance on a relative scale.
As a result, pharmacies must balance multiple goals and prioritize investments into certain DIR contracts. Measures can be clinically-focused, like medication adherence, or administrative, like generic dispensing rate.
Understanding each payer’s contract specifications—including contract measures and fee thresholds—is essential to maximize your ROI and improve DIR measure performance. Because of how contracts are structured, drastic improvements to certain measures will not impact DIR fee totals. For other pharmacies, small improvements make substantial differences in DIR amounts.
Determining which DIR contracts to prioritize and how to achieve the greatest intervention impact is both critical and challenging. This is where AI comes into play.
Can AI technology optimize DIR contracts?
Using healthcare AI technology (like AllazoHealth’s AI engine) allows pharmacies to maximize ROI based on where they are with each metric on each DIR contract. Several DIR variables drive results, including:
- Patient attribution: Where are patients going outside of your pharmacies? Which pharmacies will they be attributed to at the end of the year?
- Metric qualification: How can we determine which patients will qualify for each metric? Will doing interventions impact qualification for metrics?
- Metric achievability: Can we determine metric achievability ahead of time? Can we put together an intervention plan to drive metric achievement?
- Intervention impact: What channel works best for each patient? What should the content of these pharmacy interventions be to change patient behavior?
AI can help with each of these variables. Armed with the right AI technology, your pharmacy can better evaluate how close it is to each DIR threshold and make the best possible resourcing decisions.
DIR Fee Thresholds: An Example
If thresholds for one DIR contract are at 60 and 80, and your pharmacy is at 70, it doesn’t make sense to invest effort into improving those measures. With a goal this lofty, chances are you will only end up wasting valuable resources trying to increase the measure by ten percentage points.
Alternatively, if your pharmacy is at 59 or 61 (or 79 or 81)—meaning your pharmacy is only one percentage point from the next threshold—there’s a greater chance of success. Therefore, you should put more effort into that particular contract.
In addition to helping determine which metrics are most achievable, AI can predict patient behavior, which patients qualify for metrics, and whether investing resources in a particular patient population is the most effective way to maximize value.
For instance, if you’re looking to increase medication adherence among a certain population to improve measure performance, you can use AI to target the right patients with the right interventions. Rather than sending the same generic message to each patient via the same channel and hoping for positive results, you can personalize each intervention based on channel, content, and timing to have the greatest impact.
Want to learn more about using AllazoHealth’s AI engine to reduce DIR fees and optimize performance? Schedule a demo for a firsthand look.
About the Author
Dr. Linda Schultz
Dr. Linda Schultz is a results-oriented Healthcare Pharmacy Executive who excels at leading transformational, top-notch, interdisciplinary healthcare teams to create and execute outcomes driven clinical operations and account management initiatives. Dynamic and knowledgeable in all healthcare business segments, most passionately within the complex Medicare, Duals and Medicaid markets, she is an accomplished, creative motivator and driver of innovative quality and cost of care pharmacy interventions. Dr. Schultz is currently VP, Customer Success at AllazoHealth, a cutting-edge, healthcare artificial intelligence company. Prior to her leadership role at Allazo, Linda founded and led RxHorizons, LLC., an international healthcare consulting group. Her expertise stems from over 25 years of experience within the Managed Care industry, with a focus on leading, strategizing, developing and implementing pharmacy benefit management activities within national PBMs and health plans.