Using Pharmacy Claims Data to Sharpen Your GLP-1 GTM Strategy

A GLP-1 go-to-market strategy is the plan for how a company selling GLP-1–related products or services (Ozempic, Wegovy, and the rest) reaches health systems: by enabling systems already prescribing at scale, replacing parts of the system with an alternative channel, or augmenting them with wraparound services. Pharmacy claims data tells you which of those three plays fits a given health system. Here's how to use it.

If you're building a business around GLP-1s—Ozempic, Wegovy, all the buzzy names—you're probably trying to figure out: Is our strategy about enabling health systems, replacing parts of them, or augmenting what they do?

Enablement, Replacement, or Augmentation: The Fork in the Road

Look, the temptation is always there to launch a parallel GLP-1 service, bypassing and effectively replacing a part of the health system entirely. D2C, virtual, sleek. And sometimes that's right. But often, scaling will eventually require working alongside the big systems, where working through Medicare Advantage (MA) can be particularly effective.

So, which path are you on?

1. Enablement: Partner with systems that are already prescribing GLP-1s at scale. Help them manage patients better.
2. Replacement: Build an alternative channel where the system is falling short.
3. Augmentation: Fill the gaps in wraparound services for the surge in GLP-1 patients.

That's the real question. And it matters. Because how you go to market changes depending on the answer.

But how do you get to that answer? You need to know where GLP-1 prescribing is happening, who is driving it, and what's behind it. That's where account- and provider-level pharmacy claims data — prescribing volume tied to specific health systems — can give you a huge edge.

How Pharmacy Claims Data Sharpens the Choice

You don't need perfect, member-level data to get clarity. Even aggregated and directional provider-level data can guide you if you know how to work with it. Here's how we did it:

1) Start with volume. We pulled pharmacy claims showing GLP-1 prescriptions amongst seniors, sliced by health system. High-volume systems are often more suited for the enablement approach—they're already in deep and likely need support with patient coordination and management. (Note: these volumes are based on a representative sample of MA claims.)

Health System Spotlight: Corewell Health

Here's what surprised us. You might think leading GLP-1 prescribers would be the big-name academic medical centers (AMCs). But the data told us: look at Corewell Health in Michigan. 14 hospitals. Major GLP-1 volume in senior patients. Not the first name that comes to mind.

That's the point. Without the data, you'd default to chasing the usual suspects. With it, Corewell jumps out—a prime candidate for wraparound services like behavioral coaching, lifestyle guidance, and medication management.

2) Normalize the numbers. Raw volume numbers can at times be insufficient. Big systems consistently top the list. So, we estimated the Medicare Advantage population per system. Normalizing showed us the health systems that might be prescribing more than you'd expect based on their size. These are augmentation or even replacement opportunities such as behavioral interventions and turnkey virtual-first services, respectively.

3) Dig into conditions (CCSR categories). We asked, why are these prescriptions happening? Pharmacy data doesn't always tell you, but diagnosis groupings (CCSRs) give hints. Sure, diabetes is there, but we saw other patterns—obesity, hypertension, sleep-wake disorders—suggesting interrelated patient populations to additionally focus on.

Healthcare Provider Data and Segmentation in Practice

Everything above is healthcare provider data and segmentation applied to a live GTM question: rank systems by GLP-1 volume, normalize by Medicare Advantage population to surface over-performers, then cluster by condition (CCSR) to sharpen the message. Segmenting providers this way is what turns a raw claims feed into a prioritized, defensible target list—instead of a list of the usual big names.

What This Means for Your GTM Playbook

Once you see the data, your GTM gets sharper:

• Big-volume systems: go in with an enablement pitch—partner to support what they're already doing.
• Normalized over-performers: these systems may need additional support to keep up with growing demand and/or holistically manage patient health to supplement GLP-1 prescriptions, so augmentation or replacement services might be the best angle.
• Condition-specific clusters: if you see obesity or heart disease driving prescribing, shape your message around that—maybe you're more of a cardiovascular wraparound than a diabetes play.

Don't Let "Imperfect Data" Hold You Back

Startups get stuck waiting for pristine, member-level claims feeds. You don't need it. This was all done with directional, aggregated data. The creativity is in making those numbers work for you.

Final Takeaway

GLP-1s are here, and the stakes are high. Whether you enable, replace, or augment the system—provider data helps you decide. Find your Corewell. Get ahead of the market.

See how Bonfire turns pharmacy claims data into a prioritized GLP-1 target list — explore the Bonfire product platform or book a walkthrough.

Data notes & caveats

• All data shown here is from the Q1 2023 – Q4 2024 time interval.
• This analysis is meant to be directional and illustrative—GTM teams can ideally pair this with plan enrollment and network data for a more complete picture.

Frequently Asked Questions

How do I build a GLP-1 go-to-market strategy?

Start by deciding whether you're enabling, replacing, or augmenting health systems, then use pharmacy claims data to see where GLP-1 prescribing volume actually concentrates. Rank systems by volume, normalize for their Medicare Advantage population to find over-performers, and segment by condition (CCSR) to tailor your message.

How do I get provider-level claims data to build a more precise healthcare sales target list?

You get provider-level claims data one of two ways: license it from a healthcare data vendor, or work with a sales-intelligence platform that has already aggregated and modeled it for targeting. You don't need member-level feeds; aggregated, provider-level medical and pharmacy claims are enough to build a precise target list. Start by aggregating claims to the health-system or account level, rank accounts by the prescribing or procedure volume that maps to your product, normalize by population (e.g., Medicare Advantage lives) to surface over- and under-performers, and segment by diagnosis (CCSR) to match accounts to your specific value proposition. That turns a raw feed into a prioritized, defensible list instead of a roster of the usual big names. Bonfire Analytics does this step for you—layering provider-level pharmacy and medical claims with population and segmentation data so healthtech teams can go straight to a ranked target list.

What data do you need to target GLP-1 prescribers?

You don't need member-level data. Aggregated, provider-level pharmacy claims data is enough to rank health systems by GLP-1 volume, estimate prescribing relative to population size, and identify the diagnosis clusters driving demand.

How do I prioritize which health systems to target first?

Prioritization comes down to layering three signals from pharmacy claims data. First, rank health systems by raw GLP-1 prescribing volume to find where the activity already concentrates. Second, normalize that volume against each system's Medicare Advantage population; this surfaces over-performers that raw volume alone would hide, since large systems otherwise dominate every list. Third, cluster by condition (CCSR categories) to see whether prescribing is being driven by diabetes, obesity, hypertension, or other patterns, which tells you how to position your message. Systems that rank high on all three—high volume, high normalized rate, and a clear condition signal that matches your offering—are your best first targets. This is also how less obvious candidates like Corewell Health surface ahead of bigger-name academic medical centers.

Which health systems prescribe the most GLP-1s?

Volume doesn't always follow name recognition. In our analysis, Corewell Health in Michigan (14 hospitals) showed major GLP-1 volume among senior patients—ahead of many better-known academic medical centers—illustrating why data beats intuition when building a target list.