🗄️ Data & Analytics

Digitized Aggregation

A centralized health data hub that normalizes, deduplicates, and unifies clinical data from any source building a complete longitudinal patient record across your network.

Request Demo → See How It Works
🤖 AI Deduplication 📡 FHIR Data Store ✅ SNOMED + LOINC
Aggregation Agent · Patient Record Build
// Ingesting from 4 sources → aggregation.ingest("patient: ABHA-4321-8765") source_1: Apollo EHR 42 records source_2: Thyrocare LIS 18 reports source_3: Medanta HMIS 6 episodes source_4: ABHA PHR 12 documents   // Normalizing and deduplicating → aggregation.normalize() terminology: SNOMED CT + LOINC + ICD-10 duplicates_merged: 7 records conflicts_flagged: 2 for review   → aggregation.build_timeline() span: 2019-01-12 → 2025-04-30 events: 71 clinical events status: longitudinal record ready ✓
500M+Clinical records processable
99.8%Patient matching accuracy
6Standard terminologies supported
Real-timeRecord updates from any source
Features

One patient, one record,
every interaction

🔗

Multi-Source Ingestion

Connect to LIS, EHR, HMIS, ABDM PHR, wearables, and pharmacy systems simultaneously. Any format HL7, FHIR, CSV, PDF ingested and normalized.

🧠

AI Patient Matching

Probabilistic patient identity resolution links records across systems even without a common ID using name, DOB, demographics, and ABHA identifiers.

📚

Terminology Normalization

All clinical concepts mapped to SNOMED CT, LOINC, ICD-10, and ICD-11. Eliminates local code fragmentation that makes data unusable for analytics.

📅

Longitudinal Timeline

Every clinical event consultation, diagnosis, prescription, lab result, procedure, hospitalization is arranged on a unified, searchable patient timeline.

📊

Population Analytics Layer

Aggregate anonymized cohort data for disease burden analysis, readmission risk scoring, and resource utilization forecasting across your network.

🛡️

Consent-Based Access

Patient data shared only with explicit ABDM-compliant consent. Role-based access control ensures the right data reaches the right care team member.

How It Works

Fragmented data in,
unified intelligence out

Digitized Aggregation is the connective tissue of your health data ecosystem. Once connected, every new event from any system enriches the longitudinal record in real time.

1
Connect Data Sources

Connect existing LIS, EHR, and HMIS systems via HL7, FHIR, or file-based feeds. Middleware layer handles protocol translation automatically.

2
Match & Deduplicate

AI patient matching links records across systems. Duplicate events are merged; conflicts are flagged for clinical review. Patient MPI is built and maintained.

3
Normalize & Enrich

Local codes are mapped to international standards. Missing data is enriched from linked ABHA records. Every record is structurally validated before storage.

4
Query & Analyze

Access the unified record via FHIR API, analytics dashboards, or export to your BI tool. Real-time and batch query modes supported.

Data analytics and health intelligence dashboard
Impact

From data silos to
population intelligence

360°
Complete longitudinal patient view across all systems
99.8%
Accuracy in patient identity matching across sources
10x
Faster population health reporting vs manual aggregation

Unify your health data.
Unlock its true value.

Book a technical demo. We'll connect to a sample of your data and show you the unified timeline in under 30 minutes.

Book a Demo →