Optimize Performance-Based Pharmacy Reimbursements

Uncategorized

Over the last several years, PBMs and other payers have instituted performance-based contracts that leverage direct and indirect remuneration (DIR) fees to alter prescription-level reimbursement.

Although each contract can be complex, the burden placed on pharmacy organizations is magnified due to the variety of structures, measures, thresholds, and attribution methods. Maximizing reimbursement requires optimized performance. This comprehensive strategy can help improve pharmacy reimbursements:

Deepen your understanding of contracts.

Pharmacies must understand contract structures, performance measures, and how the performance measures interact with one another. There are many ways to measure pharmacies, including on an absolute scale (e.g., statin population adherence that must exceed 95 percent to attain maximum reimbursement) or a relative scale (e.g., the top 10 percent of high performing pharmacies will receive maximum reimbursement).

Thresholds for reimbursement can vary widely, with little consistency between PBMs and payers. The same is true with attribution methods. How patients are attributed to individual pharmacies is often controversial, with two primary means:

  1. Attribution to the pharmacy with the patient’s most recent fill.
  2. Attribution to the pharmacy with the largest share of the patient’s fills.

Designing your program begins with understanding reimbursement structures and how PBMs and payers identify patients.

Design patient engagement that addresses barriers to engagement.

Patient engagement stratifies according to many lines—demographic, socioeconomic, health status, and more. For example, seniors are more likely to take multiple drugs and struggle with medication adherence. People using mental health medications are also more likely to have adherence difficulties due to side effects and stigma.

Your patient engagement measures will cost less and be more effective if they target the patients with the most adherence difficulties. Targeted messages that speak specifically to these patients’ needs are key. This requires an understanding of these patients and an approach that is never condescending.

Leading pharma company saw 4.6 times greater uplift on therapy using data-driven patient targeting. >>

Prioritize the most impactful, cost-effective interventions.

It’s common for various measures to interact with one another, meaning that an engagement program can potentially positively affect one measure while negatively impacting another. Moreover, the wrong program might have a positive effect, but on a measure that does little to improve patient well-being or reduce costs.

Understanding which measures of engagement are most important is the first step in crafting a patient engagement program that supports patient health and maximizes reimbursement rates. Look at historical reimbursement rates and aggregate patient data when making these decisions.

The most essential measures typically incorporate Centers for Medicare & Medicaid Services (CMS) Star measures endorsed by the Pharmacy Quality Alliance, such as medication adherence for diabetes medications, hypertension (RAS antagonists), cholesterol (statins), and statin use in persons with diabetes. Some programs utilize additional measures or substitute measures for pharmacies that predominantly distribute specialty medications. Use these measures to guide your intervention decisions.

Consider the following conundrum:

  • Contract A: Based on year-to-date performance, the expectation is for results to fall in middle-tier performance, firmly between two thresholds. To achieve the top tier, 200 more patients will need to be adherent.
  • Contract B: Based on year-to-date performance, the expectation is to barely surpass the lower threshold and make it to the middle tier. If 20 patients do not remain adherent, results will go below the threshold and enter the lower tier.
  • Contract C: Based on year-to-date performance, the expectation is to be just below the higher threshold to make the top tier. To achieve the top tier, 30 more patients will need to be adherent.

If there is only enough time and resources to support 40 patients, which 40 should you choose? Should you focus on Contract C and get all 30 of those patients over the threshold, potentially sacrificing the 20 patients from Contract B who may need support?

Is it less important to get to the next tier on Contract C and more crucial to support the 20 patients in Contract B? Should efforts be divided across all three in hopes of supporting all contracts for the next year? Should more people be hired so 300 patients can be supported, allowing all contracts to move to the next tier?

Unfortunately, the answer is more complicated than this example shows, particularly because there are dozens of contracts that are measured independently. To fully answer the question, it is important to know the level of reimbursement that each tier in this example represents and how likely each patient is to be adherent. This example is also very simplistic. In reality, all the factors described above are crucial in determining where to allocate efforts.

Use each interaction to improve program performance.

Most industry programs are dominated by two types of interventions:

  1. Those that use counseling to identify and understand barriers and offer long-term strategies for surmounting those barriers.
  2. Those that facilitate the refill process via synchronized refills, offering access to larger supplies and similar services.

An overall engagement approach needs to implement both types of interventions. Counseling is especially critical because some patients may not realize or reveal they experience side effects until someone asks them the right questions. Doing so then reveals barriers to patient engagement, allowing for the right intervention.

Today’s artificial intelligence (AI) and machine learning capabilities can help you identify common motivators for patient behavior, understand how various patient factors interact to influence behavior, and determine which programs are most likely to have the highest impact. Leveraging the power of AllazoHealth’s AI platform empowers you to dramatically increase the effectiveness and efficiency of a medication adherence program and significantly boost patient engagement and pharmacy reimbursements.

New call-to-action

Tags:
Warning: Invalid argument supplied for foreach() in /home/allazo5/public_html/wp-content/uploads/cache/5f800da4275ef244555fde5cb527b6ed8dac6d4a.php on line 34