Provider contact data for healthcare recruiters

Ben Argeband, Founder & CEO of Heartbeat.ai — Write for burned-out recruiters; skimmable; workflow-first.

Who this is for

This hub is for healthcare recruiters and locum staffing teams who need provider contact data that supports speed-to-submittal and workflow fit. If your team is dialing a lot and talking to few humans, the issue is usually connectability, identity resolution, and refresh—not effort.

You’ll get a repeatable method you can run inside Bullhorn or Apploi, plus micro-assets you can copy into your team playbook.

Quick Answer

Core Answer

Use provider contact data as a workflow: identify the right clinician, validate channels, rank for connectability, run compliant outreach, and refresh continuously to reduce wasted attempts.

Key Statistic

Heartbeat observed typicals: ~10% Connect Rate typical; 100–200 outreach attempts (calls + emails + texts) per placement; mobile accuracy 82% (first mobile); email accuracy 95%. Measured on outbound recruiting attempts.

Best For

Healthcare recruiters and locum staffing teams needing accurate provider contact data.

Compliance & Safety

This method is for legitimate recruiting outreach only. Always respect candidate privacy, opt-out requests, and local data laws. Heartbeat does not provide medical advice or legal counsel.

• Jump to: Lookup TL;DR
• Jump to: Step-by-step method
• Jump to: Diagnostic Table
• Jump to: Weighted Checklist
• Jump to: Outreach Templates
• Jump to: Evidence and trust notes
• Jump to: FAQs
• Jump to: Next steps

What “connectable” means in practice: you want higher Connect Rate (connected calls / total dials, per 100 dials), higher Answer Rate (human answers / connected calls, per 100 connected calls), and strong Deliverability Rate (delivered emails / sent emails, per 100 sent emails).

TL;DR: Recruiters don’t need “more contacts”; they need connectable contacts. Provider identity keys reduce duplicates. Refresh is a workflow, not a purchase. If you want to see what usable looks like on a live req, start free search & preview data. If you’re evaluating sourcing and verification, review how our data is sourced and structured.

Framework: Recruiter-First Data Workflow: Identify → Validate → Rank → Outreach → Refresh

• Identify: Resolve the clinician record using stable identity keys (not just name + city).
• Validate: Confirm channels and suppress bad ones fast (bounces, wrong numbers, opt-outs).
• Rank: Prioritize the channels most likely to reach a human now.
• Outreach: Run a tight sequence with clean logging and respectful opt-out handling.
• Refresh: Re-check and update based on outcomes; decay is normal.

TODO (visual note): Data workflow diagram (no image): Identify → Validate → Rank → Outreach → Refresh, with a feedback loop from Outreach outcomes back to Validate/Rank.

Data fields that matter (for recruiting ops)

Lookup TL;DR (what to do when you’re stuck)

If you’re mid-req and need a fast decision, use this compact table to pick the next action and the metric to watch.

Step-by-step method

1) Identify the clinician using identity keys (reduce duplicates before you dial)

Start by anchoring the person record. In recruiting, duplicates are expensive: they create repeated outreach, messy CRM history, and bad handoffs between recruiters.

• NPI can help anchor identity when available. Reference: CMS NPI overview and the NPPES NPI Registry.
• License matching helps disambiguate common names and confirm state-level identity.
• Practice context (specialty, facility affiliation, geography) reduces wrong-person outreach.

2) Validate channels and suppress fast (before you scale)

Validation is not a one-time checkbox. It’s a loop: validate, outreach, learn, suppress, refresh.

• Email: suppress bounces and refresh before you scale a segment.
• Phone: separate office lines vs mobile in your workflow so your team doesn’t treat every number the same.
• Consent + opt-out: store and honor opt-out status across tools so you don’t re-contact someone who said “stop.”

The trade-off is… deeper validation takes time up front, but it prevents the slow bleed of wasted attempts and recruiter burnout later in the req.

3) Rank for connectability (not just “has a number”)

Most teams treat contact data like a static field. Treat it like a queue. Your goal is to put the most connectable channel at the top for this req, this week.

• Rank by likelihood of reaching a human during realistic call windows.
• Sequence phone + email so you’re not burning the same channel repeatedly.
• Use outcomes (connected, wrong person, voicemail, bounce, reply) to re-rank.

Heartbeat.ai supports this by providing ranked mobile numbers by answer probability so your first dials aren’t random.

4) Outreach with tight logging (so the data gets better, not noisier)

Outreach is where data quality becomes measurable. If you don’t log outcomes consistently, you can’t tell whether the issue is the data, the message, the timing, or the channel.

• Log call outcomes in Bullhorn or Apploi with consistent dispositions (connected, voicemail, wrong number, no answer).
• Log email outcomes (delivered, bounced, replied) and suppress bounces quickly.
• Track opt-out requests and apply them across all sequences.

If you’re stitching systems together, Zapier or Make can push outcomes back into your CRM so the next recruiter doesn’t repeat the same dead-end.

5) Refresh continuously (because decay is normal)

Refresh is a workflow, not a purchase. Build refresh triggers into req hygiene:

• Refresh after a bounce, wrong number, or repeated no-answer patterns.
• Refresh when a clinician changes facility, role, or state.
• Refresh before re-opening an old pipeline for a new req.

Use cases (how teams apply this without adding headcount)

• Locums speed: prioritize ranking + short sequences so you get to a qualified conversation fast, then refresh immediately on dead channels.
• In-house pipeline reactivation: re-validate and refresh older records before you re-open outreach, so you don’t burn reputation on stale channels.
• Agency margin protection: reduce wasted attempts by suppressing bounces/wrong numbers quickly and re-ranking weekly based on outcomes.

Micro-Asset: Diagnostic Table

Micro-Asset: Weighted Checklist

Use this to evaluate whether a provider contact data source is usable for recruiting (not just “big”). Score each item 0–2 and total it.

• (2) Identity resolution supports NPI and license matching to reduce duplicates.
• (2) Clear separation of channel types (mobile vs office) and ability to prioritize.
• (2) Suppression support for opt-out and bad channels (bounces, wrong numbers).
• (2) Workflow fit: can push/pull to Bullhorn or Apploi with clean fields.
• (2) Automation hooks via Zapier or Make for logging outcomes and refresh triggers.
• (2) Refresh capability is operational (you can re-check and update), not a one-time export.
• (1) Transparent metric definitions (connect, deliverability, accuracy) with denominators.
• (1) Clear process for honoring consent notes and opt-outs across channels.

Interpretation: 12–14 = ready for production workflows. 9–11 = usable with tight suppression + validation. <9 = expect wasted attempts and recruiter fatigue.

Micro-Asset: Outreach Templates

Template 1: First-touch email (short, recruiter-real)

Subject: Quick question about your next role

Hi Dr. [Last], I’m recruiting for a [Role] in [Region]. Are you open to hearing details this week, or should I close the loop?

If you’d rather not get messages from me, reply “opt out” and I’ll stop.

— [Name], [Team] | Heartbeat.ai

Template 2: Voicemail (15 seconds)

Hi Dr. [Last], this is [Name]. I’m calling about a [Role] opportunity in [Region]. If you’re open to a quick overview, call/text me at [Number]. If not, tell me and I’ll close it out.

Template 3: Text (only where appropriate; keep it respectful)

Hi Dr. [Last] — [Name] recruiting. Are you open to a quick call about a [Role] in [Region]? Reply STOP to opt out.

Common pitfalls

• Buying static exports and calling it a strategy. Buying static lists is risky because of decay. The modern standard is Access + Refresh + Verification + Suppression.
• Not anchoring identity. If you don’t anchor on NPI and license matching, you’ll duplicate outreach and poison CRM history.
• Measuring activity instead of outcomes. “We sent 5,000 emails” isn’t a recruiting metric. Track delivered, replies, and connects tied to submittals.
• Letting tools drift. If Bullhorn/Apploi fields aren’t standardized, your refresh loop breaks and reporting becomes noise.
• Ignoring burnout signals. If recruiters are doing repetitive cleanup, they’ll stop trusting the data and revert to old habits.

Burnout check: If your team spends more time fixing duplicates, hunting for a better number, or re-sending bounced emails than talking to candidates, the workflow is broken—not the recruiters.

How to improve results

Define the metrics (so everyone measures the same thing)

• Connect Rate = connected calls / total dials (per 100 dials).
• Answer Rate = human answers / connected calls (per 100 connected calls).
• Deliverability Rate = delivered emails / sent emails (per 100 sent emails).
• Bounce Rate = bounced emails / sent emails (per 100 sent emails).
• Reply Rate = replies / delivered emails (per 100 delivered emails).
• Mobile accuracy = correct first mobile numbers / first mobile numbers attempted (per 100 first-mobile attempts).
• Email accuracy = correct, in-use email addresses / email addresses attempted (per 100 attempted). (Separate from Deliverability Rate, which measures delivery outcomes after sending.)

Uniqueness hook worksheet: MEASUREMENT_FORMULA (time-to-fill math you can run on any req)

Measure this by… building a simple funnel from attempts → connects → qualified conversations → submittals → placements. You don’t need new software; you need consistent denominators.

• Connects per 100 dials = (connected calls / total dials) × 100.
• Human answers per 100 dials = (human answers / total dials) × 100.
• Placements per 100 connects = (placements / connected calls) × 100.

TODO (visual note): “Time-to-fill math” box: connects per 100 dials; placements per 100 connects.

How to run your baseline in 7 days (no new tools required)

• Day 1: Standardize dispositions in Bullhorn/Apploi (connected, voicemail, wrong number, no answer) and email outcomes (delivered, bounced, replied).
• Days 2–6: Run your normal outreach, but enforce suppression: bounces and opt-outs are suppressed promptly and applied across channels.
• Day 7: Pull totals and compute the worksheet funnel. Compare segments by call window, specialty slice, and channel order.

If you need automation, Zapier or Make can sync opt-outs and bounces across systems so suppression is consistent.

Legal and ethical use

Recruiting outreach is allowed, but you still need to run it like a professional operation.

• Opt-out: If someone asks you to stop, stop. Store the opt-out and apply it across channels.
• Email compliance: Use accurate sender identity, include a working opt-out mechanism, and honor it promptly. Reference: CAN-SPAM compliance guide.
• Calling/texting rules: Follow applicable calling/texting rules and internal policies; document your process. Reference: TCPA overview.
• Texting: Use only where appropriate under your internal policy and applicable law, and always honor opt-out requests.
• Data minimization: Only collect what you need to recruit and to honor opt-outs.

Heartbeat.ai does not provide legal advice. If you’re building high-volume outreach, involve counsel and document your consent and suppression processes.

Evidence and trust notes

Identity anchoring: We use stable identifiers like NPI where applicable to reduce duplicates and wrong-person outreach. References: CMS NPI overview and NPPES NPI Registry.

Compliance references: For outreach rules and expectations, see TCPA overview and the CAN-SPAM compliance guide.

Heartbeat observed typicals: ~10% Connect Rate typical; 100–200 outreach attempts (calls + emails + texts) per placement; mobile accuracy 82% (first mobile); email accuracy 95%. These are measured on outbound recruiting attempts and vary by specialty, geography, message, and call windows. We do not claim guaranteed accuracy.

How to verify in your environment: Log dispositions consistently in Bullhorn/Apploi, suppress bounces and opt-outs centrally, and compare funnels using the worksheet above.

For how Heartbeat approaches sourcing quality, verification, and measurement, see: Trust & methodology.

FAQs

What should I look for in provider contact data as a recruiter?

Prioritize connectability and workflow fit: identity keys (NPI, license matching), suppression/opt-out handling, refresh capability, and clean integration into Bullhorn or Apploi.

How do I reduce duplicate outreach to the same clinician?

Anchor records on stable identifiers (NPI where available) plus license matching, then enforce one master record in your CRM. Sync merges and suppressions across tools.

How often should I refresh contact data?

Refresh on triggers (bounce, wrong number, repeated no-answer, job/location change) and before reactivating old pipelines. Treat refresh as part of weekly req hygiene.

How do I measure whether my contact data is working?

Track Connect Rate per 100 dials, Deliverability Rate per 100 sent emails, and Reply Rate per 100 delivered emails. Tie outcomes to submittals and placements.

Can I push this into Bullhorn or Apploi automatically?

Yes. Many teams use Zapier or Make to sync records, log outcomes, and apply opt-out suppression across systems. The key is standardized fields and dispositions.

Next steps

• Run a live test: start free search & preview data and measure Connect Rate per 100 dials on a real req.
• See what’s included: review how our data is sourced and structured.
• Plan workflow + budget: see pricing and map it to your outreach volume and margin targets.
• Go deeper by workflow:
  • Locum outreach workflow (speed-first)
  • Phone lookup workflow for recruiting
  • Email finding workflow for recruiting
• When you’re ready to operationalize access: get my data access.

About the Author

Ben Argeband is the Founder and CEO of Swordfish.ai and Heartbeat.ai. With deep expertise in data and SaaS, he has built two successful platforms trusted by over 50,000 sales and recruitment professionals. Ben’s mission is to help teams find direct contact information for hard-to-reach professionals and decision-makers, providing the shortest route to their next win. Connect with Ben on LinkedIn.