You can’t see the full patient journey.
Marketing, intake, and clinical systems all live on different domains and vendors. Nobody has a clean view from first touch to booked appointment or ongoing care.
Industry · Healthcare & Virtual Care Analytics
Healthcare analytics that respects privacy and still tells you what's working.
We help virtual care and healthcare organizations design analytics that support growth, access, and outcomes—without leaking PHI into the wrong systems. Think HIPAA-aware tracking, consent-driven journeys, and data pipelines your compliance and engineering teams can live with.
- Multi-domain funnels (marketing → intake → EMR/clinic) with end-to-end visibility.
- Server-side and warehouse-first designs that keep PHI out of GA4, ad platforms, and random tools.
- Governance, consent, and access control woven into the measurement layer—not bolted on later.
Built for physician-led organizations, virtual care platforms, and healthcare operators who need strong analytics without compromising patient trust.
Example · Virtual Care Patient Journey (De-identified)
1
Awareness & education
Anonymous traffic from search, ads, referrals → tracked in GA4 with consent + strict data minimization.
2
Self-assessment / intake funnel
Screening flows instrumented with event-level analytics, but no PHI sent to GA4 or ad platforms.
3
Booking & clinical systems
Server-side events and warehouse pipelines join marketing identifiers to de-identified clinical and billing data under strict access control.
Result: growth, operations, and clinical leadership see a full funnel—from outreach to booked consults and beyond—without PHI ending up in tools it shouldn't.
Healthcare Reality
Healthcare can't be a data black box—but it also can't spray PHI into every tool.
The choice is not “track nothing” vs “ignore HIPAA.” The real work is designing data flows, tagging, and pipelines that keep protected health information out of analytics and ad platforms—while still telling you what channels, messages, and experiences are working.
Compliance shuts down measurement ideas.
Every time someone suggests better tracking, someone else says “HIPAA will never allow it”—and the discussion dies instead of becoming a real design problem.
Vendors bolt on tracking with no governance.
Landing page tools, booking systems, and EMRs add their own tags and pixels. No one is watching what data they actually send or where it goes.
You’re stuck between zero tracking and risky tracking.
Either you track almost nothing, or you discover PHI and sensitive fields inside GA4, Meta, or random tools—with no clear path to fix it.
Compliance-Aware by Default
We design analytics with HIPAA and privacy guardrails from day one.
We're not a law firm. But we are relentless about technical patterns that keep PHI where it belongs, keep marketing tools de-identified, and give your compliance team fewer things to worry about—not more.
PHI never goes into GA4 or ad platforms.
- No names, diagnoses, medications, detailed symptoms, or EMR IDs in analytics or marketing tools.
- Event and parameter design that separates marketing analytics from clinical and billing data.
- Front-end and tag manager filters that block sensitive fields before they leave the browser.
Server-side and warehouse-first by design.
- Use server-side tagging and ETL pipelines to keep raw, sensitive data inside controlled environments.
- De-identify before joining marketing and clinical/billing data for outcomes and ROI analysis.
- Minimize whatever reaches external tools; keep detailed joins and modeling in your warehouse.
Consent and geography-aware measurement.
- Consent flows and regional logic built into tagging, not manually toggled per campaign.
- Measurement strategies that adapt to different privacy regimes and payor requirements.
- Clear documentation your legal and compliance teams can actually review and approve.
Access control and governance as first-class citizens.
- Role-based access to dashboards and raw data, aligned with clinical, admin, and marketing needs.
- Change control for events, funnels, and data models—especially around clinical or outcomes data.
- Audit trails for key changes so you can explain how numbers are derived to regulators and partners.
Reference Architecture
A healthcare analytics stack that lines up with how care is delivered.
We design the analytics stack around your real-world journey—from someone finding you online to being matched with a provider and receiving ongoing care. The pattern is always the same: keep PHI in secure systems, move only what's needed into analytics, and join data in a governed warehouse.
Channel & Web Layer
- Marketing site (public, content / education-focused).
- Self-assessment and quiz flows (no PHI in events).
- Landing pages and campaign microsites.
Typical tech
GA4 (strictly de-identified), GTM/web, consent & CMP, Meta/Google Ads tags (minimal identifiers).
Intake & Booking Layer
- Intake forms with sensitive questions routed to secure systems.
- Booking engines and telehealth platforms on separate domains.
- Referral forms from partners and providers.
Typical tech
Server-side tagging, event relays, and custom APIs to send non-PHI conversion signals back to GA4/Ads.
Clinical & EMR Layer
- EMR/EHR, practice management, and internal clinical tools.
- Clinical outcomes, diagnoses, medications, treatment plans.
- Provider and care team data.
Typical tech
No direct analytics tags. Secure ETL/ELT processes into a governed warehouse with strict RBAC.
Warehouse, BI & Modeling
- De-identified, joined views for marketing, operations, and leadership.
- Attribution models tuned to healthcare realities (wait times, cancellations, long cycles).
- Performance and capacity dashboards for clinics and care teams.
Typical tech
BigQuery/Snowflake/Redshift, Looker Studio / Power BI, dbt or SQL modeling, governed access for teams.
Selected Healthcare Engagements
From "we can't track that" to "we finally know what works."
Names and details can be anonymized, but the problems repeat everywhere: fragmented journeys, compliance concerns, and leadership making big calls with incomplete data. Our job is to fix that without creating new risk.
Virtual mental health provider
Problem: High demand, complex triage flows, and strict privacy expectations. Marketing and clinical systems were fully separated with no unified analytics.
What we did: Designed HIPAA-aware tracking for marketing and intake, implemented server-side conversion reporting, and built a de-identified warehouse model for funnel and outcomes analysis.
Impact: Leadership saw clear channel performance, capacity, and wait-time impacts without exposing PHI in analytics tools.
Multi-clinic primary care & telehealth
Problem: Multiple booking systems and local sites, inconsistent tracking, and no shared measurement across clinics and modalities.
What we did: Standardized events and funnels across clinics, built cross-domain and server-side tracking, and wired de-identified clinic-level performance dashboards.
Impact: Regional and clinic leaders could finally see which channels and flows drove access and utilization—for in-person and virtual care.
Specialty care network
Problem: Long patient journeys, complex referral paths, and siloed teams made it impossible to understand which programs actually drove downstream value.
What we did: Mapped end-to-end journeys, built a privacy-safe attribution and outcomes model in the warehouse, and created dashboards that tied initiatives to real impact.
Impact: Operations and leadership shifted budget and effort to programs with proven downstream outcomes, not just top-of-funnel impressions.
For clinical & medical leadership
See where patients come from, where they drop off, and which programs drive outcomes—without exposing PHI in the wrong tools or asking you to trust black-box models.
For growth & marketing teams
Understand channel performance, campaign ROI, and capacity impact in a way compliance can live with—and leadership can act on.
For operations, product & engineering
Clear event specs, integrations, and data models that don't fight your architecture—and are maintainable as you add clinics, providers, and services.