CRM migration
Field-level mapping, validation, and rollback between Phreesia and Pipedrive. We move data and schema; workflows are rebuilt natively in Pipedrive.
Phreesia
Source
Pipedrive
Destination
Compatibility
12 of 12
objects map 1:1 between Phreesia and Pipedrive.
Complexity
BStandard
Timeline
48–72 hours
Overview
Phreesia is a healthcare-specific patient intake platform centered on registration forms, insurance eligibility checks, consent capture, and appointment workflows. Pipedrive is a general sales CRM built around People, Organizations, Deals, and Activities with a visual drag-and-drop pipeline. The two platforms share virtually no overlap in domain logic, which means the migration is primarily a field-level data translation exercise rather than an object-to-object record carry-over. We extract Phreesia patient records via API, including all custom intake form fields, insurance carrier data, consent records, and appointment history. We then map that data into Pipedrive: Patient → Person (with custom fields for insurance and consent), Insurance carrier → Organization (linked via OrganizationId), Appointments → Activities (with visit type and clinical context stored as custom fields). Phreesia's custom intake forms — built with conditional logic and branching rules — have no native equivalent in Pipedrive's data model; we capture every custom field value and document the form structure for manual rebuild as Pipedrive custom fields and automations. The migration uses Phreesia's API for structured data extraction, preserves original create/update timestamps as custom datetime fields, resolves Phreesia providers to Pipedrive users by email match, and runs a delta-pickup window post-cutover for in-flight records. Workflows, sequences, eligibility verification rules, and EHR integration hooks are not migratable — those are rebuild items surfaced in the migration plan.
Every standard and custom field arrives verified.
AI proposes the map; you confirm before any record moves.
Parent–child, lookups, and ownership stay linked.
Calls, emails, meetings — with original timestamps.
Documents, uploads, and inline notes move with the record.
Why teams make this switch
Leaving
What's pushing teams away
Choosing
What's pulling them in
Object mapping
Each row shows how a Phreesia object lands in Pipedrive, including any object-level transformations, lookup resolution, or schema-design dependencies.
Typical mapping — final map is confirmed during the sample migration step.
Phreesia
Patient
Pipedrive
Person
1:1Direct map. Phreesia patient record maps to Pipedrive Person with name, email, phone, and address fields carried over verbatim. Primary insurance carrier is resolved separately as an Organization and linked via Pipedrive's person-to-organization association. Original Phreesia patient ID preserved as Source_System_ID__c custom field for delta-run de-duplication.
Phreesia
Insurance Carrier
Pipedrive
Organization
1:1Phreesia insurance carrier stored per patient maps to Pipedrive Organization representing the payer. Carrier name becomes Organization name, and the Person record links to it via OrganizationId. When multiple patients share a carrier, Pipedrive deduplicates to a single Organization record. Self-pay patients have no carrier and no Organization link.
Phreesia
Appointment / Visit
Pipedrive
Activity
1:1Phreesia appointments become Pipedrive Activities with Type='Appointment' or Type='Call' depending on visit modality. Original appointment date and time map to Activity due_date and start times. Visit type (new patient, follow-up, telehealth) is stored as a custom field on the Activity since Pipedrive's native Activity model does not include visit-type categorization. Provider name maps to the assigned Pipedrive user on the Activity.
Phreesia
Consent Record
Pipedrive
Person (custom fields)
1:1Phreesia consent records have no direct Pipedrive equivalent. We migrate consent_type (e.g., HIPAA, financial policy, treatment consent) as a custom pick-list field on Person, and consent_timestamp as a custom datetime field. Electronic signature data is not transferable in a standard CRM migration — the consent form itself must be re-executed in the destination system or stored as a linked document.
Phreesia
Custom Intake Form Field
Pipedrive
Person (custom fields)
1:1Every custom field from Phreesia's intake form builder becomes a Pipedrive custom field on the Person object. Field types map as follows: text → varchar, number → int, date → date, checkbox → boolean, dropdown → picklist. Phreesia's conditional logic and branching rules are not migratable — we document the form structure so the practice can rebuild conditional rules as Pipedrive Automations or Smart Docs.
Phreesia
Payment Record
Pipedrive
Person / Deal (custom fields)
1:1Phreesia payment records (amount, status, method, card on file) have no native Pipedrive equivalent. Payment status and last payment amount migrate as custom fields on the Person record. If payments are tied to a specific treatment plan, the plan migrates as a Pipedrive Deal with payment amount as the deal value and payment status as a custom field. Pipedrive's built-in invoicing is not used — payment history is a reference field, not a transactional record.
Phreesia
Insurance Eligibility Check Result
Pipedrive
Person (custom fields)
1:1Phreesia's real-time eligibility verification results (coverage status, copay, deductible remaining) are healthcare-specific and have no Pipedrive equivalent. We preserve the last eligibility check date and status as custom fields on Person for reference, but active eligibility checking requires a third-party integration like VerifyODE or Waystar in Pipedrive's ecosystem — not a migration carry-over.
Phreesia
Clinical Screening Response
Pipedrive
Person (custom fields) / Note
1:1Phreesia clinical screening responses (PHQ-9, SDOH, substance use, social determinants) are structured data that does not map to standard Pipedrive fields. We migrate discrete screening scores as numeric custom fields on Person and store the full screening response as a Note attached to the Person record. Clinical decision-support logic tied to screening results is not migratable and must be rebuilt outside Pipedrive.
Phreesia
Referral Source
Pipedrive
Person (custom fields) / Organization
1:1Phreesia referral tracking (referring provider, facility, source channel) migrates as a custom field on Person identifying the referral type. When a referring provider or facility is named, we create a corresponding Pipedrive Organization record and link it to the Person — similar to the insurance carrier pattern. Anonymous digital referrals (website, Google, walk-in) are stored as custom field text values.
Phreesia
User / Staff Owner
Pipedrive
User
1:1Phreesia staff who own patient records are resolved to Pipedrive Users by email match. Unmatched owners are flagged before migration — the practice must invite those users to Pipedrive or assign their records to a fallback owner. Inactive Phreesia staff are not migrated as Pipedrive users; their records are reassigned to the specified fallback.
Phreesia
Registration / Check-in Event
Pipedrive
Activity
1:1Phreesia registration events (check-in time, kiosk used, self-service vs. staff-assisted) are healthcare-specific and map to a custom Activity field in Pipedrive. These are logged as Activity records with Type='Registration' and a custom field capturing the registration method. The original registration timestamp is preserved as the Activity due_date for reporting on no-show rates and check-in efficiency.
Phreesia
EHR Integration Link
Pipedrive
Not migrated
1:1Phreesia's HL7 and FHIR integrations with Epic, Athena, Cerner, and other EHR systems are not migratable to Pipedrive. Pipedrive does not natively support HL7 feeds. Practices must select and configure a separate integration solution (e.g., Mirth Connect, 1547 Group) to reconnect EHR data flows post-migration. This is surfaced as a rebuild item in the migration plan.
| Phreesia | Pipedrive | Compatibility | |
|---|---|---|---|
| Patient | Person1:1 | Fully supported | |
| Insurance Carrier | Organization1:1 | Fully supported | |
| Appointment / Visit | Activity1:1 | Fully supported | |
| Consent Record | Person (custom fields)1:1 | Fully supported | |
| Custom Intake Form Field | Person (custom fields)1:1 | Fully supported | |
| Payment Record | Person / Deal (custom fields)1:1 | Fully supported | |
| Insurance Eligibility Check Result | Person (custom fields)1:1 | Fully supported | |
| Clinical Screening Response | Person (custom fields) / Note1:1 | Fully supported | |
| Referral Source | Person (custom fields) / Organization1:1 | Fully supported | |
| User / Staff Owner | User1:1 | Fully supported | |
| Registration / Check-in Event | Activity1:1 | Fully supported | |
| EHR Integration Link | Not migrated1:1 | Fully supported |
Gotchas + challenges
Platform-specific issues from each side, plus the pair-specific challenges that don't show up on either platform's page on its own.
Phreesia gotchas
PM/EHR integration configuration must be validated before patient data import
Custom intake forms lack a standard schema export
Phreesia is an intake platform, not a longitudinal patient database
Patient secure authentication links are time-limited and non-migratable
Payment plan configurations require manual reconciliation
Pipedrive gotchas
Custom field hash keys differ per account
Export access gated by visibility groups
Token-based API rate limits since December 2024
Sequences and Automations not exposed via REST API
Cost escalates via workflow caps and add-ons
Pair-specific challenges
Migration approach
Inventory Phreesia data architecture and export all source records
FlitStack AI connects to Phreesia via API using read-only scoped credentials. We extract all patient records, insurance carrier data, appointment history, consent records, custom intake form responses, payment records, referral sources, and registration events. The export is staged in a temporary data store where we deduplicate by patient ID, validate required fields, and flag records with missing critical data (no email, no phone, duplicate names) for practice review before migration. This inventory step also identifies the count of custom intake form fields, conditional logic branches, and insurance carrier variants — the primary cost drivers for the migration quote.
Configure Pipedrive custom fields and Organization structure before data arrival
Before any data moves into Pipedrive, we create the target schema: custom Person fields for insurance (member ID, group number, plan name, relationship), consent (type, timestamp, form version), payments (status, amount, card on file), clinical (visit type, screening scores, referral source), and healthcare metadata. We also create Organization records for all unique insurance carriers identified in the Phreesia export, linking them to the relevant Person records via Pipedrive's person-to-organization association. This pre-configuration prevents validation failures at migration time and gives the practice a chance to review the custom field layout before records land.
Resolve Phreesia providers and staff to Pipedrive users by email
Phreesia staff owners, providers, and front-desk users are matched to Pipedrive users by email address — the primary key for identity resolution across both platforms. Unmatched owners are flagged in a pre-migration report: the practice must either invite those users to Pipedrive or assign their records to a designated fallback owner before the migration run. No patient record lands in Pipedrive without a valid OwnerId. This step also validates that the Pipedrive users have the appropriate visibility group permissions for patient data access, since Pipedrive's visibility groups control which users can see which records — a relevant configuration for multi-location practices.
Run sample migration with field-level diff before full commit
A representative slice of records — typically 100–500 patients spanning different appointment types, insurance carriers, and custom intake form variants — migrates first into Pipedrive's live environment (or a designated sandbox if preferred). We generate a field-level diff comparing each source field against the destination field, so the practice can verify that insurance carrier linking, consent field mapping, visit-type categorization, and custom intake field preservation match expectations. Any mapping corrections are made before the full run. This sample run also surfaces Pipedrive API throttling behavior at the practice's plan tier, allowing us to calibrate batch sizing for the full migration.
Execute full migration with delta-pickup window and rollback available
The full migration runs against Pipedrive, with records loaded in dependency order: Organizations first (insurance carriers), then Persons (patients), then Activities (appointments, registration events), then linked custom fields. A delta-pickup window — typically 24–48 hours from the start of the full run — captures any new patient records, appointments, or consent events created in Phreesia during the cutover. Every operation is logged in an audit trail. If reconciliation fails — a duplicate detected, a required field missing, or a critical mapping error — a one-click rollback reverts the Pipedrive state to the pre-migration snapshot. The rollback is available for 72 hours post-cutover.
Platform deep dives
Phreesia
Source
Strengths
Weaknesses
Pipedrive
Destination
Strengths
Weaknesses
Complexity grading
Standard CRM migration. 3 of 8 objects need a mapping; the rest are 1:1.
Overall complexity
Standard migration
Derived from compatibility, mapping clarity, API constraints, and data volume across Phreesia and Pipedrive.
Object compatibility
3 of 8 objects need a mapping; the rest are 1:1.
Field mapping clarity
Field mapping is derived from defaults — final spec confirmed during the sample migration.
Timeline complexity
8-object category — typical timelines run 2–7 days end-to-end.
API constraints
Phreesia: Not publicly documented.
Data volume sensitivity
Phreesia doesn't expose a bulk API — REST + parallelization used for high-volume runs.
Estimator
Rule-based pricing — no per-record fees, no manual quotes. Migrations over 2M records are scoped individually.
Step 1
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