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NPLUS HealthIQHealthcare Data & Physician Intelligence
DATA QUALITY · 4 min read · 2026-08-27

Reading Between the Lines of a Vendor's "Coverage" Claim | NPLUS Global

'Coverage' numbers in healthcare data sales pitches often hide more than they reveal — here's how to actually vet them.

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Every data vendor in healthcare will tell you they cover "90% of practicing physicians" or "the entire acute care market." These numbers get repeated so often they stop meaning anything. Before you sign a contract based on a coverage slide, it's worth understanding what's actually being measured, and what's conveniently left out.

  1. Ask what "covered" actually means. A record can be "covered" because it has a name and a mailing address, or because it has a verified direct dial, a current affiliation, and a specialty code that's been checked in the last quarter. Vendors rarely distinguish between these in the headline number, so the same 90% claim can describe wildly different levels of usability depending on who's saying it.
  2. Coverage of the universe isn't coverage of your universe. A vendor might legitimately cover 85% of all U.S. physicians, but if your target is interventional cardiologists at health systems with more than 200 beds, that aggregate number tells you almost nothing about your actual addressable segment. Always ask for coverage broken out by the specific specialty, site type, or geography you're buying for, not the topline figure.
  3. Static coverage decays the moment it's measured. Healthcare has some of the highest turnover of any professional data category — physicians change affiliations, NPs move between systems, practice managers leave. A snapshot showing strong coverage today says little about what you'll be working with in month four of a campaign unless the vendor can also speak to refresh cadence and how they detect movement.
  4. "Matched" and "verified" are not the same claim. Some vendors count a record as covered once it's matched against a source file like NPPES, even if no human or automated process has confirmed the contact detail is still accurate. Matching tells you a record exists somewhere; verification tells you it's usable. Ask directly which process produced the coverage number you're looking at.
  5. Multi-source aggregation can inflate numbers without adding accuracy. Stitching together several third-party files will almost always raise a coverage percentage, because you're taking the union of what each source has. But if none of those sources independently confirmed the same fact, you've increased breadth while quietly diluting confidence — and the vendor's dashboard won't show you that tradeoff.
  6. Ask how gaps are handled, not just how big they are. A 12% gap that's evenly distributed and disclosed is far more workable than a 12% gap concentrated entirely in rural markets or smaller specialty groups, which happens to be exactly where your campaign might live or die. The honest vendors will tell you where their blind spots cluster instead of just quoting an average.
  7. Coverage claims rarely account for role-level accuracy. A vendor can have strong coverage of an organization and still misattribute titles, department, or decision-making authority within it — which matters enormously in healthcare, where the person with the title "Director of Pharmacy" may or may not be the actual buyer for what you're selling. Coverage of the entity doesn't guarantee coverage of the relevant role inside it.
  8. The comparison baseline is almost never disclosed. When a vendor says they have "40% more coverage than competitors," ask more than once what competitors, what year, and what methodology produced that number, because it's frequently self-reported or drawn from an outdated audit. At NPLUS Global we've found that prospects rarely push back on comparative claims like this, even though they're the easiest ones to inflate.
  9. The only real test is a sample against your own use case. Coverage percentages are marketing artifacts until you've pulled a sample against your actual target list and checked it manually — call a subset, cross-reference against a system you trust, see what holds up. It takes an afternoon, and it will tell you more than any number on a sales deck.

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