CRM MODERNIZATION FOR A MULTI-SITE HEALTHCARE PROVIDER
Built for a multi-site healthcare provider
A multi-site healthcare provider replaced a patched, unsupported CRM with a consolidated platform that unifies patient and partner records, automates care-coordination hand-offs and keeps an attributable audit trail for compliance.
By Yashwant Daniel · Solvstrat
Key
Facts
- Sector
- Healthcare
- Built
- Modernized multi-site CRM and care-coordination layer
- Stack
- Salesforce Health Cloud · Freshworks · PostgreSQL · Azure
- Constraint
- Patient data stays within approved, access-controlled systems
- Outcome
- One de-duplicated record per patient and partner
Challenges
A regional healthcare provider ran its patient and partner relationships on a patched, aging CRM that fragmented data across teams and forced routine work to move by hand. We rebuilt the platform on a modern CRM foundation, consolidated fragmented records, and automated the coordination steps that were slowing care teams down.
Fragmented Patient & Partner Data
Records lived in disconnected tools, so different teams worked from different versions of the same person.
Manual Care-Coordination Hand-offs
Routine updates, referrals and follow-ups were passed between teams by hand, adding delay and errors.
An Aging, Unsupported CRM
The existing platform was costly to maintain, hard to extend, and a growing compliance and audit risk.
Constraints
Patient data must remain within approved, access-controlled systems.
Existing scheduling, billing and communication tools must keep working.
Historical records must migrate without loss or duplication.
Clinical and front-office teams must retain their current workflows.
Every record change needs an attributable audit trail.
Reference
Architecture
Experience layer
Front-office, clinical and partner teams work from role-based views over the same CRM data. No team maintains a separate list or a local copy of the record.
Salesforce Health Cloud · Role-based views
Record consolidation
A matching and de-duplication layer resolves patient and partner identities before records are written, so the canonical record is created once.
Matching rules · PostgreSQL
Coordination engine
Referrals, follow-ups and status changes are routed automatically with reminders and a named owner for each next step.
Automation rules · Notifications
Integration layer
API-first connections to scheduling, billing and communication tools keep operational systems in sync without manual re-entry.
APIs · Webhooks
Reporting and audit
Operational reporting and an attributable change history support compliance review without a separate reporting exercise.
Reports · Audit log
Data
Flow
- 1
A patient or partner record enters through an intake form, referral or integration.
- 2
The consolidation layer matches it against existing records and resolves duplicates.
- 3
The canonical record is written once and linked to the relevant care teams.
- 4
Coordination rules assign the next step and notify the owning team.
- 5
Scheduling, billing and communication systems receive the update through the integration layer.
- 6
The change is recorded in the audit log with actor, time and source.
Delivery
Foundation
CRM data model, identity matching and migration baseline.
Consolidation
Record migration, de-duplication and integration connections.
Automation
Care-coordination routing, reminders and status handling.
Hardening
Reporting, audit coverage and role-based access review.
Hard
Problems
Matching patients across systems
Problem: The same person appeared under different identifiers, formats and spellings, so naive merges created false matches.
Resolution: Deterministic matching on stable identifiers, fuzzy review for ambiguous cases and a manual adjudication queue before any merge is committed.
Migrating without breaking care
Problem: A hard cutover risked losing history or interrupting active care coordination.
Resolution: Migrated in reconciled batches, validated counts and relationships, and ran legacy and new records in parallel until sign-off.
Automation without losing accountability
Problem: Automated routing can obscure who owns a step and why it moved.
Resolution: Every automated action records an owner, a reason and a timestamp, and exceptions route to a named queue for review.
Results
A Single Source of Truth
One consolidated, de-duplicated record per patient and partner, visible to every authorized team.
Less Manual Work
Routine coordination moved from manual hand-offs to automated routing, freeing staff for higher-value work.
Lower Platform Risk
A supported, compliant platform replaced an aging CRM that was expensive to maintain and hard to extend.
Industry Benchmark
Comparable CRM modernization projects typically reduce manual data-entry time by 30–50% and substantially cut duplicate records. We frame outcomes against these benchmarks rather than publishing client-specific figures.
Technology
Used
Salesforce Health Cloud
Freshworks
PostgreSQL
Azure
Lessons
Data quality is the migration — matching and de-duplication decide whether the new CRM is trusted.
Automate the hand-off, not the judgement; clinical decisions stay with people.
Audit evidence has to be a by-product of normal work, not a separate reporting exercise.
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FAQ
Frequently asked questions
We replaced an aging, unsupported CRM with a modern foundation, consolidated fragmented patient and partner records, and automated the manual coordination hand-offs that were slowing care teams down.
Yes. Records were de-duplicated and migrated from the legacy system in validated batches, so reporting and history stayed continuous with no data loss.
We keep the client anonymous. For reference, industry ranges for comparable CRM modernization projects are a 30–50% cut in manual data-entry time; these are reference ranges, not measured results for this client.
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