\n| Reducing gatekeeper time and generic inbox loops<\/td>\n | Limited<\/td>\n | Yes (direct channels + suppression)<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n Pilot validation checklist (run this before you migrate anything):<\/strong><\/p>\n\n- Identity anchor:<\/strong> Can you store NPI on the clinician record and use it to merge duplicates?<\/li>\n
- Duplicate rate:<\/strong> How many \u201cnew\u201d records are actually the same clinician already in your ATS\/CRM?<\/li>\n
- Phone outcomes:<\/strong> Track Connect Rate and Answer Rate on a fixed cohort (same specialty + geo).<\/li>\n
- Email outcomes:<\/strong> Track Deliverability Rate, Bounce Rate, and Reply Rate on the same cohort.<\/li>\n
- Suppression:<\/strong> Are opt-outs, bounces, and wrong numbers suppressed so they don\u2019t re-enter future exports?<\/li>\n<\/ul>\n
<\/span>Framework: The \u201cFacility vs Clinician\u201d Framework: What you\u2019re actually buying<\/span><\/h2>\nMost \u201cdatabase disappointment\u201d in recruiting comes from buying the wrong unit of value.<\/p>\n If you\u2019re comparing facility intelligence vs clinician contact data<\/em>, you\u2019re really deciding whether your next bottleneck is account targeting (facility) or direct outreach (clinician).<\/p>\n\n- Facility data<\/strong> helps you understand organizations: locations, affiliations, ownership, and where care is delivered. Definitive Healthcare is primarily facility\/org intelligence.<\/li>\n
- Clinician data<\/strong> helps you reach people: the individual provider identity (often anchored by NPI<\/strong> and license matching<\/strong>) plus contact channels (mobile, email) that actually connect. Heartbeat.ai is clinician person-level contact data.<\/li>\n<\/ul>\n
The trade-off is\u2026 facility intelligence accelerates account targeting, while clinician contact data accelerates speed to conversation because you can reach providers directly instead of routing through a main line.<\/p>\n MYTH_BUST:<\/strong> \u201cIf I know the facility, I can find the doctors.\u201d In practice, that turns into hours of switchboards, directory loops, and stale web pages\u2014especially when clinicians split time across sites or own private practices.<\/p>\n<\/span>Step-by-step method<\/span><\/h2>\n<\/span>Step 1: Decide what you\u2019re trying to ship this week<\/span><\/h3>\nPick one outcome and build the data stack around it:<\/p>\n \n- Outcome A: Build a target account list<\/strong> (systems, hospitals, clinics, service lines) \u2192 facility data is primary.<\/li>\n
- Outcome B: Submit candidates fast<\/strong> (reach clinicians, book calls, move to CV) \u2192 clinician data is primary.<\/li>\n
- Outcome C: Do both<\/strong> \u2192 pair tools with a clean handoff (next step).<\/li>\n<\/ul>\n
<\/span>Step 2: Use a pairing workflow (facility targeting \u2192 clinician outreach) when you need both account context and direct clinician reach in the same req<\/span><\/h3>\n\n- Start with facility data<\/strong> to pick targets: service line, ownership, locations, and affiliations.<\/li>\n
- Extract the clinician universe<\/strong> you actually recruit: specialty, role, geography, and affiliation signals.<\/li>\n
- Resolve identities<\/strong> so each clinician becomes one record in your ATS\/CRM (NPI first; license matching when needed).<\/li>\n
- Append contact channels<\/strong> (mobile + email) for outreach and track outcomes by channel.<\/li>\n
- Suppress bad channels<\/strong> (bounces, wrong numbers, opt-outs) so you don\u2019t keep paying the penalty.<\/li>\n<\/ol>\n
<\/span>Step 3: Lock identity keys before you buy more \u201ccontacts\u201d<\/span><\/h3>\nIdentity resolution (definition):<\/strong> the process of matching records that refer to the same real-world clinician across sources using stable identifiers (for example, NPI<\/strong>) plus supporting attributes (name, specialty, address history, and license matching<\/strong>).<\/p>\nPractical identity keys for healthcare recruiting:<\/p>\n \n- NPI<\/strong> as the primary anchor for clinicians<\/li>\n
- State license<\/strong> and license number to disambiguate common names or fill gaps<\/li>\n
- Location history<\/strong> to confirm you\u2019re contacting the right person<\/li>\n<\/ul>\n
Minimum fields to store on the clinician record (for clean merges and reporting):<\/strong><\/p>\n\n- NPI (primary clinician key)<\/li>\n
- License state + license number (secondary key)<\/li>\n
- Specialty and recruiting segment tags<\/li>\n
- Primary practice location (and prior locations if you track them)<\/li>\n
- Suppression flags: email suppressed, phone suppressed, opted out<\/li>\n<\/ul>\n
<\/span>Step 4: Run a small connectability pilot before you migrate anything<\/span><\/h3>\nDon\u2019t evaluate tools by UI. Evaluate by whether your team can connect with clinicians quickly.<\/p>\n \n- Pick one specialty and one geography you actively recruit.<\/li>\n
- Pull 100 clinicians you would genuinely contact.<\/li>\n
- Run your normal outreach sequence for 5 business days.<\/li>\n
- Log outcomes in one place (ATS\/CRM activity + dialer logs + email platform results).<\/li>\n<\/ol>\n
Heartbeat.ai includes ranked mobile numbers by answer probability<\/strong> so recruiters can prioritize dials when time is tight.<\/p>\nIf you want to validate fit without committing, you can start free search & preview data<\/strong> in Heartbeat.ai and run the pilot above.<\/p>\n<\/span>Diagnostic Table:<\/span><\/h2>\n |
![\"54290\"](\"http:\/\/hc.heartbeat.ai\/wp-content\/webp-express\/webp-images\/uploads\/2026\/02\/definitive-healthcare-alternative-d9ad1857.png.webp\")
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