Metroflow Playbook · Healthcare & Life Sciences

Executive summary

Deploy Metroflow on-prem or private cloud. Auto-tag PHI-adjacent assets, document trial cohort → outcomes lineage, and export audit-ready provenance on demand.

Healthcare data must stay inside your boundary, and clinical lineage must be defensible under HIPAA and trial protocols. Spreadsheets for PHI tagging and months of manual tracing for audits do not scale. Metroflow maps metadata only: schemas and job names: without moving patient rows.

On-premDeployment inside HIPAA boundary

HoursAudit lineage exports vs months of manual work

100%PHI-adjacent tables tagged with downstream map

01

What broken lineage costs you

Typical patterns at Healthcare & Life Sciences organizations. Ranges, not guarantees.

PHI tagging in spreadsheets

Stale tags, missed downstream consumers

With Metroflow: Auto-tag PHI-adjacent tables with live consumer list in graph.

Trial cohort lineage undocumented

Protocol deviations hard to defend in audits

With Metroflow: Cohort → outcomes path from clinical_staging to fct_trial_outcomes.

Audit prep marathon

3–6 months tracing models for each review

With Metroflow: Exportable lineage reports with cited paths in hours.

Access policy violations

Analysts unaware of PHI downstream impact

With Metroflow: Governance agents flag models consuming patient_id from clinical_staging.

◇

Metadata only. Metroflow crawls schemas, job names, manifests, and dashboard definitions. Your production data rows never leave your network.

02

Your stack, one graph

Sector-specific constraints. Metroflow sits above the data path: unify compliance, velocity, and trusted metrics.

Trace clinical_staging.patient_id through every downstream model: stg_encounters → dim_patients → fct_trial_cohort → fct_trial_outcomes. When load_ehr_batch fails, see every clinical dashboard and trial report affected.

03

Where are you today?

Most teams land at L1 or L2. Target L4 in 90 days.

L1Siloed docsWikis and spreadsheets disconnected from production.

L2Partial lineageSome tool lineage exists. Cross-layer gaps remain.

L3Unified graphOrchestration, warehouse, and BI in one map.

L4Certified metricsKPIs owned, enforced, and traced end-to-end.

L5Proactive opsPre-merge gates. Stale assets caught early.

Quick self-check

Answer "what breaks if X fails?" in under 15 minutes?
Cross-functional teams share one definition of core KPIs?
Incidents include downstream dashboard impact without Slack archaeology?
Changes include cross-layer impact checks before merge?
Named owners for certified metrics and critical pipelines?

0–2: Start Week 1 connect · 3–4: Certify metrics · 5: Add change gates

04

Choose your path

Every org is different. Pick the track closest to your context.

Health system / provider

EHR extracts, clinical data warehouse, population health BI

Priority: Certify first: PHI tagging on clinical_staging and top 20 consumers

Pharma / biotech trials

EDC feeds, cohort models, outcomes reporting

Priority: Certify first: trial cohort → outcomes lineage for protocol audits

Life sciences research

Omics pipelines + clinical joins on-prem

Priority: Certify first: cross-domain provenance for IRB and FDA submissions

05

Who owns what

Assign decision rights up front. Metric fights are governance problems.

Function	Owns	On Metroflow
Data governance / privacy	PHI policies, access controls, audit responses	Own PHI tag registry. Export lineage for compliance reviews.
Clinical analytics	Trial cohort and outcomes models	Document cohort → outcomes paths. Certify trial KPIs.
Data platform	On-prem deployment, EHR ingest pipelines	Register load_ehr_batch and clinical DAGs. Blast-radius on failure.
Clinical operations	Trial reporting, protocol compliance	Self-serve provenance exports. Company Brain for audit Q&A.

06

30 · 60 · 90 day rollout

A program with gates, not just a connector checklist.

Days 1–30

On-prem connect

Deploy Metroflow on-prem or private cloud
Connect warehouse, dbt, orchestration, BI
Tag PHI-adjacent tables in clinical_staging

Gate: patient_id consumers mapped with live downstream list

Days 31–60

Clinical lineage

Document trial cohort → outcomes path
Certify enrollment and outcomes KPIs
Governance agent for PHI access checks

Gate: One trial with end-to-end audit-ready lineage

Days 61–90

Audit operationalization

Export templates for HIPAA and trial audits
Pre-merge impact on clinical_staging changes
Quarterly provenance refresh program

Gate: Audit lineage request answered in under 48 hours

07

Incident runbook

When load_ehr_batch is in trouble. Follow this timeline.

T+0 · Detect

EHR batch load failing

Airflow alert or stale clinical_staging. Open Metroflow.

T+5 min · Blast radius

Run impact query

"Which models consume patient_id from clinical_staging?"

T+15 min · Communicate

Notify governance and clinical ops

Tag privacy officer and trial leads with affected reports.

T+45 min · Fix

Remediate ingest

Replay EHR batch. Verify PHI-tagged paths unchanged.

T+2h · Verify

Confirm trial dashboards fresh

Re-run lineage. Log for audit if trial reporting window active.

Slack template

[INCIDENT] load_ehr_batch failing: clinical_staging stale Impact: patient_id and encounter data not updating Affected: Trial Cohort Dashboard, fct_trial_outcomes, Population Health report Owner: @clinical-data-oncall · ETA 2h Governance: PHI downstream list verified: no new consumers introduced Metroflow blast-radius: [paste link]

08

Metric certification pack

Copy into your governance doc. One definition. One owner. Full lineage.

Trial enrollment (cumulative)

Certify first

Formula: Distinct subjects meeting inclusion criteria per protocol v3.2, by site.

Source: clinical_staging → fct_trial_cohort

Owner: Clinical analytics + Clinical ops

Lineage: EHR → clinical_staging → cohort model → Trial Dashboard

Primary outcome event rate

Certify first

Formula: Confirmed primary endpoint events / enrolled subjects, ITT population.

Source: fct_trial_cohort → fct_trial_outcomes

Owner: Clinical analytics + Biostatistics

PHI-adjacent coverage

Operational

Formula: % of PHI-tagged tables with documented downstream consumers in Metroflow.

Target: 100% by day 60.

Owner: Data governance

09

Daily workflows

Four situations you will hit every week.

🏥

PHI access review

Open tag registry
PHI-adjacent tables and owners.
List consumers
Every model using patient_id.
Policy check
Governance agent flags violations.

📋

Trial audit prep

Cohort → outcomes trace
Full path with citations.
Export report
Protocol-aligned provenance doc.
Brain Q&A
Answer auditor follow-ups.

🔀

Before clinical_staging change

Impact query
All PHI downstream models.
Privacy sign-off
Required before merge.
Update tags
Refresh consumer registry.

🚨

EHR ingest failure

Blast radius
Trial and clinical dashboards affected.
Comms
Notify clinical ops and governance.
Verify PHI paths
Confirm no unauthorized new joins.

10

Copy-paste queries

Company Brain or lineage search. Context included.

PHI consumers

"Which models consume patient_id from clinical_staging?"

Trial provenance

"Trace trial enrollment from clinical_staging to fct_trial_outcomes."

Audit export

"Export lineage for fct_trial_cohort for protocol audit file."

Pipeline failure

"What clinical dashboards break if load_ehr_batch fails?"

Access policy

"Which analysts have models downstream of PHI-tagged tables?"

Schema change

"What trial reports depend on clinical_staging if we add a column?"

11

Glossary

Plain English. "Why it matters" tells you when to care.

PHI

Protected health information governed by HIPAA.

Why: Downstream consumers must be known and auditable.

clinical_staging

Staging area for normalized clinical and EHR data.

Why: Primary source for patient_id lineage tracing.

Trial cohort

Set of subjects meeting protocol inclusion criteria.

Why: Must trace to source encounters for audit defense.

On-prem deployment

Metroflow runs inside your hospital or private cloud.

Why: Satisfies HIPAA boundary requirements.

Metadata-only

Schemas and job names crawled; no patient rows moved.

Why: Privacy teams approve faster than data replication.

Company Brain

Audit Q&A with cited answers from your graph.

Why: Clinical ops answers without engineering backlog.

12

Outcomes checklist

Measure if the program is working.

Success metric	90-day target
PHI-adjacent tables with downstream consumer map	100%
Trial cohort → outcomes lineage documented	100% active trials
Audit lineage export turnaround	< 48 hours
clinical_staging changes with privacy impact review	100%

Ready to put this playbook to work?

Week 1: connect your stack and run your first blast-radius query. Week 4: certify your first KPI. Week 8: operationalize the runbook.

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