Data & Methodology

Compliant, transparent,
verifiable audience data

Summit Audience Segments builds patient audience intelligence on a foundation of consented Rx data, HIPAA-compliant infrastructure, and transparent methodology documentation — available for audit by any brand partner.

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Data Sources

Layered data architecture
for precision patient targeting

Rx Behavioral Layer
Prescription Activity
De-identified prescription fill data — drug, dosage, refill cadence, and therapy class — aggregated from pharmacy networks and PBM partners. Stratified by patient journey stage: naive, switch, augmentation, churn.
HCP Activity Layer
Prescribing Patterns
Aggregated HCP prescribing volume and specialty distribution by brand and therapeutic area. Cross-referenced with patient Rx data to identify high-intent prescribing clusters within target patient populations.
Journey Stage Layer
Patient Progression
Disease-state progression models built from longitudinal Rx data. Identifies patients by therapy stage — diagnosis → first fill → persistence → switch — enabling stage-appropriate message sequencing.
Channel Exposure
Cross-Channel Attribution
Matched impression logs from programmatic, social, search, and CTV channels — linked to consented patient cohort via encrypted ID graph. Allows channel-by-channel attribution within the same patient journey.
Consent Signal Layer
Squyr Consent Records
Patient consent status, scope, and duration tracked per individual via the Squyr protocol. Consent is refreshed at each pharmacy touchpoint. Brands only target patients with active, relevant consent status.
Commercial Coverage
Insurance Stratification
Commercial payer coverage distribution across target patient cohort — including Medicare Part D, commercial PMPM, and cash-pay segments. Enables audience stratification by payer economics and formulary status.

Measurement Methodology

Geo holdout experiments with
HIPAA-compliant cohort reporting

Experiment Design
Control: geographically randomized non-exposed patient cohort
Treatment: geographically randomized exposed patient cohort
Assignment: DMA or ZIP3 level, stratified by therapeutic area and payer mix
Minimum sample: 500K patients per arm for statistical significance
Duration: 12-week minimum test window to capture full Rx cycle
Reporting Outputs
Primary: Rx lift vs. control (cohort-level, de-identified)
Secondary: channel attribution decomposition (impression-weighted)
Audience: segment-level Rx lift variance by journey stage, payer
Frequency: weekly cohort reports · monthly attribution stack · quarterly strategic review
Compliance: all cohort sizes >50 to avoid re-identification; no individual-level data shared with brand

Data Quality & Compliance

Every record is first-party,
consent-based, and de-identified per HIPAA Safe Harbor.

The dataset is not a model, not a list purchase, not a probabilistic append. It's the operational output of a decade of condition-specific patient acquisition campaigns. Built operationally. Refreshed continuously. Exclusive for 20 years.

First-Party
Every record originated from a real patient who self-identified on an unbranded condition campaign.
Consent-Based
Patient consent verified at pharmacy point-of-care. Scope, duration, and opt-out all tracked.
HIPAA Safe Harbor
De-identified per HIPAA Safe Harbor methodology. No PII retained. No individual re-identification possible.
Exclusive
20-year exclusive license (2026–2046). No competitor can access the same dataset.

The Squyr Protocol

The identity layer that makes
everything else possible.

Squyr is Summit's bilateral encryption protocol — enabling data partnerships without any PII transit, without vendor middleware fees, without any party losing control of their data.

01
Brand
Local Hashing
Brand hashes their first-party patient identifiers locally. No PHI leaves the brand environment.
02
Squyr Network
Bilateral Exchange
Hashes exchanged bilaterally via Squyr's encrypted protocol. Both parties sign and verify. Identity graph matched in <90 seconds.
03
Summit
Overlap Computed
Matched cohort size and identifier references shared. No underlying PII exchanged. Audit trail generated.
04
Both Parties
Data Used
Both parties use their respective matched identifiers in their own environments. No data leaves either environment.
Learn more about Squyr ↗