Feature · Healthcare Lead Scoring Criteria

Score healthcare professional leads on the signals that actually matter.

Sales teams selling into physicians, nurse practitioners, pharmacists, and other healthcare professionals need lead scoring criteria that go beyond generic firmographics. NPI validity, specialty match, practice setting, prescribing volume where available, state licensure status, and compliant engagement history are the signals that predict a closed opportunity. Strkr runs the healthcare professional (HCP) scoring model with NPI validation, specialty taxonomy mapping, and compliant engagement scoring under a HIPAA posture with a BAA. The output is a score with explainability, not a black box.

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Why generic scoring fails on HCPs

The six places off-the-shelf lead scoring misreads a physician.

Generic lead scoring models were trained on B2B SaaS buyers: company size, title, downloads, email opens. Apply them to HCPs and the model confidently ranks a med student above a specialist with ten years of prescribing history. The signals that actually matter are specific to the practice: identity validation, specialty match, practice setting, prescribing or ordering volume where ethically available, state licensure, and engagement that respects the compliance boundary.

Title noise

An MD suffix alone is not a buying signal.

Generic scorers reward any title containing MD or DO. The med student, the retired specialist, and the active cardiologist with a 500-patient panel score identically. Strkr's HCP model requires an NPI validation hit on the active NPI registry and reads back the specialty, practice setting, and sanction status before scoring.

Specialty blindness

Cardiologist and dermatologist same score.

A product calibrated for cardiology is irrelevant to dermatology. Generic scorers see MD on both. Strkr maps the NPI taxonomy code to a specialty hierarchy with the vendor-defined target specialties on the top of the model and off-target specialties on an exclusion list.

Setting ignored

Hospital vs private practice vs group.

Buying power is different for a hospital-employed physician, a private practitioner, and a group member. Generic scorers conflate them. Strkr reads practice-setting from the NPPES registry when available and tags the record with the setting-specific weighting the sales team already uses in deal planning.

Volume absent

High prescribers and low prescribers rank the same.

Open prescribing data (where ethically available and permitted) is the strongest predictor of fit for pharma and medical device sales. Generic scorers never see it. Strkr integrates with licensed data providers to enrich the record with prescribing volume for the drug class, with every pull logged for compliance.

License status missed

Suspended license still shows green.

A physician under state license suspension or revocation is not a sales target and is a compliance exposure. Generic scorers do not check. Strkr checks state license status on configured cadence and flags any status change on the lead record immediately.

Sanction blind

OIG exclusion list never cross-checked.

Selling to a physician on the OIG LEIE exclusion list exposes the vendor to severe penalties. Generic scorers never cross-check. Strkr runs the lead through the OIG LEIE and the SAM.gov exclusion lists on refresh, flags matches, and holds the record off outreach queues until a compliance owner reviews.

Compliant engagement

Email open scores the same as a MedEd signup.

A compliant engagement history (CME event attendance, MedEd portal signup, product sample request) is a stronger buying signal than an email open. Strkr weighs those explicitly: an OnDemand CME attendance scores higher than a nurture open, and the model carries the compliance context so the sales rep knows what they can and cannot reference.

The criteria that matter

The nine signals Strkr's HCP scoring model reads.

Strkr's HCP lead scoring model combines identity validation, specialty match, practice context, licensing and sanction state, prescribing or ordering history where ethically available, and compliant engagement history. The model is explainable: every score shows the signals that contributed, their weights, and the policies that governed the data pull.

NPI validation

Active NPI with first- and last-name match.

The record posts to the NPPES NPI lookup, confirms the NPI is active, matches first and last name within fuzzy tolerance, and reads back the primary taxonomy. A failed lookup drops the record to a review queue. The audit log records the NPI, the match confidence, and the lookup timestamp.

Specialty taxonomy

Taxonomy code maps to target or off-target.

The primary and secondary taxonomy codes from NPPES map to the vendor-defined specialty hierarchy. Target specialties get the positive weight; off-target specialties move the record to the nurture track with a lower weight. The hierarchy is editable by the sales ops lead on the Strkr admin page.

Practice setting

Hospital, private, group, or academic.

The practice-setting tag drives the setting-specific weighting the sales team already uses. A hospital-employed cardiologist for a device sale weights differently than a private practice cardiologist for the same device. The setting is readable from NPPES or from the enrichment provider the team already pays for.

State license status

Active in the primary practice state.

The model checks state license status on the primary practice state (and additional states if the record declares them) through the state board or a licensed data provider. Status is Active, Expired, Suspended, Revoked, or Unknown. Any non-Active status flags the record and holds it off outreach queues pending review.

OIG / SAM check

Exclusion list cross-check on refresh.

The record runs through the OIG LEIE and SAM.gov exclusion lists on a configured refresh cadence (weekly default). A match flags the record immediately, holds it off outreach, and alerts a compliance owner. Clear results are logged with the refresh date for audit.

Prescribing volume

Where ethically available and permitted.

For pharma and medical device teams with proper licensing, Strkr integrates with licensed prescribing-data providers to pull volume for the relevant drug class. The data pull is logged for compliance, the pull reason is recorded, and the sales rep sees a tier (High, Medium, Low) rather than raw figures the rep is not permitted to reference.

Compliant engagement

CME attendance scores above an email open.

CME event attendance, MedEd portal signup, and sample request submissions carry the highest engagement weights. Nurture email opens and clicks carry lower weights. The model respects the compliance context: a Strkr AI drafted email cannot reference an engagement the rep is not permitted to see.

Account alignment

HCP works at a target account.

An HCP affiliated with a target account (health system, IDN, or group practice) gets an account-alignment boost. The affiliation comes from NPPES, from licensed data providers, or from Strkr's native account hierarchy. The boost is one of the signals in the explainability panel the rep sees.

Engagement recency

Recent activity beats dormant historical activity.

The model applies a decay curve to historical engagement so a CME attendance from three years ago weighs less than a sample request from last month. The decay curve is editable by the sales ops lead and the audit log records which curve was in effect for each scored lead.

How the score shows up to the rep

Explainability on the lead page.

A scoring model that the sales rep cannot interrogate is a model the rep will not trust. Strkr renders the score on the lead page with the signals that contributed, their weights, the data sources, and the compliance context. The rep opens the detail panel to see why the lead ranked where it did and what talking points are compliant to reference.

Score breakdown

Every signal shown with its weight.

The lead page shows the composite score and a breakdown by signal: NPI validation plus or minus, specialty match plus or minus, setting weight, license status, OIG state, prescribing tier where visible, engagement sum, and account alignment. The rep sees which signals moved the lead up and which held it down.

Compliance panel

Signal visibility respects the rep's role.

Prescribing volume data is visible to the rep as a tier, not raw numbers, when the compliance policy restricts raw access. The compliance panel on the lead page names what the rep is permitted to reference and what stays internal. The rep writes outreach without crossing the line.

Policy history

Which policy scored this lead when.

The audit log records which scoring policy version was in effect when the lead was scored, which refresh cadence applied to the license and exclusion checks, and which engagement signals were available at scoring time. A compliance audit six months later reproduces the score.

Overrides with reason

A manual bump requires a note.

A sales manager can override the score with a reason captured in the audit log. The next refresh re-scores the lead on the current model but the override history stays visible so the team learns which model-vs-manager disagreements correlated with closed-won outcomes.

Nurture track

Off-target specialties route to nurture, not delete.

A lead that fails to meet the primary-specialty threshold routes to the nurture track rather than discard. If the HCP moves specialty or picks up a cross-training affiliation, the next refresh can pull them into the primary track. The audit log keeps the trail.

Rep feedback loop

Rep marks the lead quality after a call.

After a dispositioned call, the rep marks the lead quality (right fit, wrong specialty, bad data, do not call). The feedback feeds the model calibration without being treated as a scoring signal in isolation. Sales ops reviews the feedback trend monthly to tune the weights.

Compliance and trust

The HIPAA and audit posture the model runs under.

HCP data is sensitive. Strkr runs the scoring model inside a HIPAA-posture tenant with a BAA, with every data pull logged for compliance, with role-based access that respects the compliance boundary, and with append-only audit entries that let a compliance officer reproduce any score months later.

HIPAA with BAA

Full HIPAA posture with BAA available.

Strkr is HIPAA compliant and a BAA is available on request. The HCP scoring model runs inside the tenant boundary with no third-party processor outside the BAA chain. PHI is not stored in the scoring record; the model uses provider identifiers and public registry data, not patient-level information.

SOC 2 Type II

Audit in progress through 2026-Q4.

SOC 2 Type II is in progress through 2026-Q4 with the control inventory published to prospective customers under NDA. The HCP model inherits the controls: access reviews, change management, data retention, and logging. The security review for the model is a short checklist on top of the main audit.

Data provider audit

Every third-party pull is logged.

The licensed data provider pulls (prescribing volume, enrichment, license status) each generate an audit entry with the pull reason, the provider, the response digest, and the acting flow version. A compliance review traces every piece of data that influenced any score.

Role-based visibility

Sales rep sees tier, compliance owner sees detail.

The role matrix governs what each role sees on the HCP record. The sales rep sees the score, the explainability panel, and the engagement context the rep is permitted to reference. The compliance owner sees the raw signals, the policy version, and the audit trail.

Retention policy

HCP records expire on the retention schedule.

The team configures a retention policy per data type. Prescribing data expires on the shortest schedule, enrichment data on a longer one, and engagement history on the team-defined schedule. Expiry triggers a redaction flow that removes the sensitive fields and preserves the audit metadata.

Append-only audit

Every score, every refresh, every override.

The audit log is append-only and tamper-evident. Every lead score, every refresh, every manual override, and every data provider pull writes an entry with the acting system, the acting user, and the policy version. A compliance audit answers questions by filter, not by vendor archaeology.

Score HCP leads on the signals that actually predict a close.

The reference HCP model is production ready with NPI validation, specialty taxonomy, OIG checks, and compliant engagement weighting. Keep the audit log, keep the BAA.

Request HCP scoring access See AI Lead Scoring
Common questions

What buyers ask about this feature.

What makes HCP lead scoring different from generic B2B lead scoring?

Generic B2B lead scoring reads title, firm size, and engagement. HCP scoring adds identity validation (NPI active and name-matched), specialty taxonomy mapping, practice setting (hospital vs private vs group vs academic), state license status, OIG and SAM exclusion checks, prescribing or ordering volume tier where ethically available, and compliant engagement weighting. The output is a score with explainability and a compliance panel that tells the rep what they are permitted to reference.

Does Strkr validate the NPI number automatically?

Yes. The scoring flow posts to the NPPES NPI lookup, confirms the NPI is active, matches first and last name within fuzzy tolerance, and reads back the primary taxonomy code and practice setting. A failed lookup drops the record to a review queue rather than scoring it with bad data. The audit log carries the NPI, the match confidence, and the lookup timestamp.

How does the model handle prescribing data when the sales team is not permitted to see raw volumes?

The model pulls prescribing data from licensed data providers under the pull reasons the compliance policy permits and renders the result to the rep as a tier (High, Medium, Low) rather than raw figures. The compliance panel on the lead page names what the rep is permitted to reference. The raw figures remain visible to the compliance owner and auditable, but the rep writes outreach without crossing the line.

What happens if a physician on an active opportunity ends up on the OIG LEIE?

The next OIG refresh (weekly by default, configurable) flags the match, holds the record off outreach queues, and alerts the compliance owner on the Strkr admin page. The sales rep sees the hold reason on the record. The opportunity does not vanish; the compliance owner reviews, documents the decision, and either removes the hold with a reason captured in the audit log or routes the record to the exclusion workflow.

Can the sales ops lead tune the weights without engineering help?

Yes. The scoring policy lives on the Strkr admin page as an editable table: signals in rows, weights in columns, with a version history. The ops lead edits weights, publishes a new policy version, and the audit log records which policy version scored each lead. The team can roll back a policy if the new weights produce surprising results, and the lead scores re-run on the previous version with no data loss.

How does the model respect HIPAA when it integrates with external data providers?

Strkr is HIPAA compliant with a BAA available on request. The scoring record stores provider identifiers and public registry data, not patient-level information, so PHI does not enter the scoring layer. External data provider pulls (prescribing volume, enrichment, license status) are logged with the pull reason and the response digest. Every data provider in the chain operates under a BAA extension, and the audit log traces the full chain for compliance review.

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AI Lead Scoring for HCPs AI Lead Scoring Lead Scoring Criteria Examples Lead Scoring Models AI Sales Assistant AI CRM Predictive Sales Analytics Account Management

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