Call Extraction: Claims Data Discovery — Private Practice

DDX ID: 0684 Date: 2025-10-06 (same day as 0686 health system call — morning session) Duration: ~47 minutes Participants: Phil Cranmer, Chris Baer (CCO), Doug Kissell (South Florida, 15+ years), Sean Lee (North Texas, referral development focus) — CDL. Daniel Wheaton, Kathryn White — MedScout. Call type: Platform customization session for private practice sales team, building dashboards for November 1 go-live. Triage: Rich. Doug’s geographic targeting methodology, Sean’s referral development use case, and the prescription data idea all surface new commercial logic.

Distinct Insights

1. Doug’s geographic clustering approach — “fly in and plant a flag”

What: Doug: “We’ll look at a specific geography, say we’re going to fly into Charleston and let’s zoom in on Charleston based on the parameters we want to look for. And if we’re prospecting, then we’ll make phone calls. We’ll set up lunches, try to schedule appointments based on their volume, and we’ll look at a Geo and say, let’s go plant a flag here.”

So what: The private practice BDM team doesn’t work from a static territory assignment — they plan trips around geographic clusters of high-volume prospects. A BDM picks a city, filters for practices doing high SPECT / zero PET within that geography, then books appointments and lunches for a focused outreach blitz. This means the claims data platform needs to support radius-based and corridor-based geographic filtering, not just state or territory views. It also means the data needs to be sortable by volume within a geography, because the BDM is triaging which 5-10 practices are worth scheduling during a 2-day trip. Phil initially suggested pre-configuring East/Central/West territories, but Doug preferred flexible geographic selection — he wants to define his own search area based on where he’s traveling, not be locked into administrative boundaries.

Speaker credibility: Doug, 15+ years private practice sales. Very high — this is his proven methodology. Scope: Private practice BDM team. May not apply to hospital team (different approach per Lynette/Todd). Motion: Private practice.

2. Hospital data as competitive framing for private practice sales

What: Doug: “I think the hospital data is helpful to us too… it tells us kind of the total territory potential, if we want to go in and steal it from somebody, it gives us an idea of what all’s in town… we can say, hey, listen, the hospital a mile down the road is doing 2,500 a year. We put a camera in here. You could probably steal some of those because we look at the guys that are referring to the hospital.”

So what: Even though the private practice team targets physician-owned practices exclusively (hospitals are a separate team), they use hospital volume data to frame the opportunity for their prospects. The logic chain: a hospital nearby is doing 2,500 SPECT/year → those patients are coming from referring physicians in the area → if a private practice cardiologist puts a PET camera in their office, some of those referrals could flow to them instead of the hospital → CDL positions the equipment placement as capturing market share that’s currently going to a nearby competitor. Hospital data isn’t just for the hospital team — it’s competitive intelligence that private practice BDMs use to build the business case for their physician prospects. Phil hadn’t initially considered including hospital data in private practice views, but immediately recognized Doug’s point as valuable.

Speaker credibility: Doug, experienced BDM. High — he’s describing how he actually sells. Scope: Private practice motion, but requires hospital data to support it. Motion: Private practice (using hospital data).

3. Sean’s referral development + camera subletting — two post-sale growth levers

What: Sean: “We have a small account out here. It’s a single provider and he is looking for more referrals from PCPs not only just for his PET volume but just in general… it’s just also helping a doctor like him. If he’s looking to sublet his camera, helping him find other cardiologists that may be ordering SPECTs.”

So what: Post-sale growth has two mechanisms, not just one. The first is referral development: identify PCPs who are diagnosing cardiac patients and directing them to cardiologists — then help CDL’s client capture more of those referrals, increasing scan volume on CDL’s equipment. The second is camera subletting: a practice with a CDL PET camera that isn’t running at full capacity can let other cardiologists in the area use it for their patients. This increases equipment utilization without the second cardiologist needing their own installation. Sean’s use case shows a single-provider practice pursuing both — more PCP referrals AND finding other cardiologists to share the camera. Claims data supports both: referral patterns show which PCPs are sending cardiac patients to whom, and SPECT volume at nearby practices identifies cardiologists who might be willing to sublet camera time rather than invest in their own equipment.

Speaker credibility: Sean, active territory with a live customer example. High for this specific use case. Scope: Post-sale private practice motion specifically. The camera subletting angle may not apply to hospital deals where CDL provides the equipment under their own license. Motion: Private practice (post-sale).

4. Prescription data as upstream targeting signal

What: Sean: “There are providers out there that aren’t ordering SPECT or PET-CT, but they’re still prescribing a lot of those medications for CAD as well. So, I think being able to have that prescribing data could be something that we could possibly use to help target physicians.” Doug added statins as a broad criterion.

So what: This is an upstream targeting concept. Current targeting starts with procedure data — who’s doing SPECT, who has PET. Sean’s idea moves one step earlier in the patient journey: PCPs prescribing cardiac medications (statins, ACE inhibitors, ARBs) are managing patients with coronary artery disease. Those patients are candidates for cardiac imaging. If a PCP has a high CAD prescribing volume but isn’t ordering imaging studies, that’s either a referral gap (the PCP isn’t sending patients for imaging when they should be) or a referral opportunity (the PCP is sending patients elsewhere, and CDL’s client could capture those referrals). This connects to Cole’s PCP referral program from the anchor notes — the prescribing data identifies the upstream physicians who control patient flow before imaging even enters the picture.

Speaker credibility: Sean’s idea, validated positively by the room. Novel — not yet tested. The concept is sound but the practical utility depends on whether prescribing data is granular enough to be actionable. Scope: Primarily post-sale (helping existing clients find new referral sources), could also inform pre-sale targeting of areas with high cardiac patient populations. Motion: Private practice (post-sale referral development).

5. “Fresh faces” and “top movers” — market change monitoring

What: Kathryn described emerging capabilities: “Show me somebody who is doing SPECTs for the first time in my geography or show me a site that is ticking up at a significant pace in my geography.” Phil: “These are just right information tidbits that may otherwise generate some action on your part.”

So what: CDL wants to detect market changes, not just snapshot current state. A new SPECT biller in a territory could be a physician who just opened a private practice (immediate prospect). A site ticking up in volume could be a practice gaining referrals (growing opportunity, or a competitor gaining share). A new PET biller could signal a competitor installation (threat to respond to). Commercial claims data refreshes monthly (Medicare lags quarterly), so these change signals for commercial payers are weeks old rather than months or years old. Phil positioned this as a “home screen” feature — the first thing reps see when they log in — which means he sees market change monitoring as a daily workflow, not a periodic analysis.

Speaker credibility: Kathryn (MedScout feature), Phil (usage vision). Phil’s framing as “home screen” shows how he’d operationalize it. Scope: Both motions — applies to private practice and hospital targeting. Motion: Both.

6. CDL evaluated 4+ platforms, chose MedScout — confirmed from private practice side

What: Phil: “This one was hands down the most intuitive robust platform that we thought you guys would enjoy.” Confirmed they evaluated 4+ alternatives with Chris Baer.

So what: Deepens the platform switch insight from 0686. CDL didn’t default to MedScout — they ran a structured evaluation with the CCO involved. “Hands down” and “most intuitive” suggest the decision wasn’t close. For the fingerprint, this tells us CDL invests in commercial data infrastructure and has sophisticated expectations about what a claims data platform should do. They’re not first-time buyers; they’re upgrading from a tool that Lynette described as powering “90% of” her heat map targeting workflow (0852) — they’re not starting from scratch.

Speaker credibility: Phil, confirmed by Chris Baer’s participation. Scope: Company-wide. Motion: Both.

Transcription Notes

• “Catherine” in the transcript likely refers to Kathryn White (MedScout CSM). Same pattern as other transcripts.
• Sean Lee confirmed as North Texas territory, Central area. He focuses on referral development — different emphasis from Doug’s prospecting-first approach.
• Doug Kissell confirmed as South Florida territory, East area. Already found MedScout on the app store before the call.
• MPFS mentioned: Medicare Physician Fee Schedule — the billing mechanism that distinguishes private practice (Part B) from hospital (facility) billing.