Prescription Data: Why You Want It, How to Get It, and What to Do with It

In 2017, I worked as a Procurement Director for a large senior living provider. I was approached in the hallway by a senior finance leader, and they asked if I thought I could apply the same logic I’d used to save money and contain costs in a long-term care pharmacy to employee benefits spend.

As a self-professed “pharmacy data nerd” my response was simple: “I’m happy to try.”  

Of course, as many self-funded plan sponsors (typically employers or unions that assume financial risk for providing healthcare benefits to their employees or members) know, accessing pharmacy data is sometimes easier said than done. On top of that, they face numerous challenges, including managing costs and ensuring optimal healthcare outcomes.  

Effectively managing these plans requires access to comprehensive and timely data. For the purposes of this article, we’ll be discussing data Pharmacy Benefits Managers (PBMs) provide to plan sponsors.

So, how can you access this data? Why do you want to have it (beyond plan management), and what do you do with it once you have it?

You Have a Right to Your Data

These days in healthcare, everything under the sun is “transparent.” PBMs have used this term liberally, especially with respect to their models. Maybe these services providers count on a lack of understanding and intentionally provide convoluted and complex data – or maybe they don’t provide it at all. But one thing is clear: that’s not transparency; it’s opacity!

Data is a wonderful tool. When used correctly and reviewed by someone with expertise, it can show you everything you need to know about your business performance. It’s a story of sorts: data should tell you what has already occurred and, over time, allow you to predict what might occur in the future.

Unfortunately, data quality is largely dependent on the entity that collects, holds, and provides it. Additionally, there is always the threat of bad actors who conceal data to continue opaque business practices that may harm or disadvantage customers.

That’s why the U.S. Government stepped in and passed several pieces of legislation, all designed to ensure transparency and data access for healthcare plan sponsors.

Those include:

1. ‍Health Insurance Portability and Accountability Act (HIPAA)
   The HIPAA Privacy rule ensures plan sponsors can access Protected Health Information (PHI) necessary for their operations while safeguarding patient privacy. Under HIPAA, plan sponsors are entitled to obtain data necessary for plan administration, provided they comply with privacy safeguards.
   

2. Employee Retirement Income Security Act (ERISA)
   ERISA Section 408(b)(2) requires service providers, including PBMs, to disclose detailed information about the compensation they receive and the services they provide. This transparency is crucial for plan sponsors to assess the reasonableness of fees and the value of services.

3. Consolidated Appropriations Act (CAA) of 2021
   CAA transparency provisions mandate that PBMs provide detailed information about drug costs, rebate arrangements, and pricing methodologies. This act enhances the ability of plan sponsors to scrutinize PBM practices and ensure fair pricing.

Is “Transparent Data” Truly Transparent?

While these regulations are very clear that plan sponsors have a right to access and use their data, how many are aware of this right? How many exercise their right to their data?

For example, Owens & Minor recently sued Anthem Blue Cross Blue Shield for allegedly refusing “to provide necessary claims data and overpaid certain claims on behalf of the plan sponsor, resulting in unnecessary costs.” This proves that even when the issue isn’t directly related to PBMs, it showcases issues within the system at large.

There are also further questions to consider:  

• Does HIPAA prevent plan sponsors from gaining access to an appropriate data set that would serve their fiduciary need?  

• Will the client need to engage in outside services or purchase a pricing reference service to analyze the data?

• How are plan sponsors supposed to honor their fiduciary duties without access to the information that can help them make faster and better decisions?

• If data is provided to clients, is it safe to assume they will understand how to use the data?

• Shouldn’t getting data from any source provide the answers you need instead of more questions?  

But perhaps the most important question: can true transparency in healthcare exist if only one side – the one providing the services – has the data?

What Data Should Employers Be Accessing?

When self-funded pharmacy benefit plan sponsors request their data, certain key data points are critical for effective management and analysis. Here are the most important data points they should request:

• Prescription Drug Claims: Details on every prescription filled, including drug name, dosage, quantity, National Drug Code (NDC), prescribing physician, and pharmacy information.

• Utilization: Number of prescriptions filled per member, frequency of refills, and member adherence rates.

• Rejection Data: Information on claims that were denied, including the reasons for denial.

• Cost: Breakdown of total costs, including ingredient costs, dispensing fees, and any additional fees.

• Manufacturer Revenue: Information on rebates and any other remuneration received from manufacturers, including amounts, timing, and conditions of the payments.

• Copayment and Coinsurance: Member cost-sharing amounts for each prescription.

• Formulary Status: List of drugs covered by the plan, their tier placements, and any restrictions such as prior authorization, step therapy, or quantity limits.

• Formulary Changes: Historical changes to the formulary, including additions, deletions, and changes in drug tier status.

• Prior Authorization: Data on prior authorization requests, approvals, denials, and associated costs.

• Step Therapy: Information on step therapy protocols and member compliance.

• Quantity Limits: Data on drugs with quantity limits and the impact on member utilization.

• Enrollment: Member demographics including age, gender, and geographic location.

• Plan Enrollment Changes: Data on member enrollment changes, such as new enrollments, terminations, and changes in coverage status.

• Medication Adherence: Data on member adherence to medication regimens, including metrics like proportion of days covered (PDC) and medication possession ratio (MPR).

• Disease Management: Information on disease management programs and their impact on drug utilization and outcomes.

• Pharmacy Utilization: Data on the utilization of different pharmacies within the network, including retail, mail-order, and specialty pharmacies.

• Network Pricing: Information on pricing agreements with different pharmacies and any network exclusions or preferred pharmacy arrangements.

• Key Performance Indicators (KPIs): Data on plan performance metrics, such as generic dispensing rate (GDR), brand utilization rate, and specialty drug utilization.

• Benchmarking Data: Comparative data to benchmark the plan’s performance against industry standards or other similar plans.

• Audit Trails: Comprehensive audit trails of all transactions, modifications, and interactions related to claims and member data.

• Regulatory Compliance: Data necessary for compliance with federal and state regulations, including HIPAA, ERISA, and the CAA.

Accessing Data is Just the Beginning

Once you have the data, another question presents itself: what do you do with it?  

For self-funded pharmacy benefit plan sponsors, having direct access to detailed claims data, utilization patterns, and cost metrics is vital.

From a cost management perspective, accessing this data enables plan sponsors to identify cost drivers, assess the impact of formulary decisions, and negotiate better terms with PBMs. Beyond that though, data access also helps improve healthcare outcomes, assists with regulatory compliance, and provides the details necessary to make informed decisions regarding plan design, formulary management, and wellness programs.

I’ve seen this firsthand. When I got a copy of a contract, which was a carved in-arrangement between the PBM and a large health plan in the state, I immediately noted the language in the PBM portion. It wasn’t clear, and it didn’t provide me with the information I needed to understand how each individual drug claim was priced.

Furthermore, the listed definitions for brands and generics favored the PBM and the guaranteed rates for drug prices were in the aggregate. This essentially negated any possibility that the PBM would underperform, regardless of how much pharmacy costs would balloon during the plan year. On top of that, the rebates guaranteed in the contract were lower than what I’d observed in the long-term care space. That seemed off to me, as I would be looking at the whole universe of drugs, not just the subset used to treat the most common conditions in seniors.

Contract Complexity Cannot Be Understated

Obviously, it’s not news to any plan sponsor that PBM contracts are notoriously complex and obtuse, but it should be highlighted that this creates a fundamental and, in some ways, existential problem. After all, if you don't have on-site expertise available to dissect and pull apart the nuances of the contract, then you might miss important nuances.

There are two paths a plan sponsor can take to solve this knowledge gap problem:

• If you don’t have on-site expertise, it’s imperative to hire a pharmacy benefits actuary, to attain your data, and then to get your data over to them.

• If you have in-house expertise, it’s important to make sure your team understands the complexities of the data and that it needs to be parsed by drug type. The goal is ultimately to understand what the per claim rate is versus the aggregate rate.

The Bottom Line: Once You Have Your Data, Use It

The ultimate goal is to understand what the per claim rate is versus the aggregate rate. Aggregate rates favor the PBM, while per claim auditable rates favor the plan sponsor. This is because aggregate rates can’t be held accountable at the claim level.  

When I was doing this work, I found that I would sometimes pay AWP-90 (Average Wholesale Price) or AWP-20 when the aggregate rate was actually AWP-75. This made it very difficult to track down what we were paying per claim (seriously, I had to create my own formula to bring NDC in from Medi-Span files so I could identify pricing).

But the bottom line is this: once you access your data, make sure you’re doing something with it – no matter which path you decide to take.  

Otherwise, what’s the point of collecting that data in the first place?