Next-Generation Healthcare Data Management Platform

With massive volumes of data from EHRs, claims systems, medical devices, labs, pharmacies, consumer apps, etc. streaming in, healthcare organizations need data strategies that enable them to generate data insights and drive business performance. However, to make data actionable, organizations need a data interoperability solution that can integrate and curate data from a diverse set of healthcare applications, to establish an enterprise’s data architecture. Healthcare organizations are now facing significant challenges in integrating and managing data. 

H-Scale, CitiusTech's healthcare data integration and management platform, helps organizations build confidence in their data and accelerate their data strategies. With its modular configurable and scalable architecture, it addresses key healthcare information needs including data acquisition, real-time processing, data security and advanced analytics. It offers strong Master Data Management (MDM) capabilities for data lifecycle management across various healthcare systems (EHR, HIS, claims, labs, etc.). H-Scale is a one-stop interoperability solution that is portable to any data platform including Hadoop, NoSQL, MPP, RDBMS etc. and supports both on-premise as well as cloud deployments.


H-Scale: Advantage

  • Largest regulatory coverage HEDIS®, STAR, ACO, HCC, VBP, MIPS, PCMH etc.
  • Interoperability focused platform specialized in healthcare data acquisition, storage, curation and provisioning
  • H-CDP for acquiring, parsing, validating and persisting structured / semi-structured clinical and claims data
  • H-IQM for real-time management of data quality at source and monitor interfaces
  • Business user-driven data lifecycle management supporting batch as well as real-time analytics
  • Consistent solution strategy across on-premise as well as cloud deployments
  • Compatible with various Hadoop distributions - Hortonworks, Cloudera and IBM BigInsights
  • Compliant with healthcare privacy and security considerations - HIPAA, 21CFR, Meaningful Use


H-Scale: Accelerating Big Data in Healthcare

CitiusTech’s H-Scale enables healthcare organizations to accelerate the use of Hadoop and other big data technologies in healthcare, while addressing unique healthcare industry requirements such as data security and encryption, data privacy, user and access management, and support for interoperability (HL7, FHIR) and clinical terminology standards.


Discover the 3 C's to build a robust healthcare data quality strategy for error-free data quality and monitoring

Success Story

Collaborative Patient Management Using Automated Analytics

Talk to an expert

Enter your information
Healthcare Data Processing, Healthcare Data Lake, Hadoop Distributions

Modular Architecture

Enabling integration and storage of high volume, velocity and variety of healthcare data.

  • Apache Hadoop-based ecosystem compatible with various Hadoop distributions including Hortonworks, Cloudera and IBM BigInsights
  • Data ingestion from disparate sources
  • Highly secure and scalable healthcare data lake for data storage
  • Late binding for easy adaptability to frequently changing market requirements
  • Multitude of delivery options (cloud or on-premise) to allow organizations to quickly ramp up their capabilities in a HIPAA-compliant manner

H-IQM (Interop & Quality Monitoring)

H-IQM -  real-time data quality management at source and monitoring of interfaces, through seamless integration with existing systems, prebuilt data quality rules and integrated dashboards.

  • Integrates tightly with interface engines (incl. Mirth, Cloverleaf) and standard healthcare data feeds (HL7, FHIR, CSV, EDI etc.)
  • Provides authoring module of data quality rules + pre-built library with 1,500+ data quality rules
  • Offers real-time data quality tracking (incl. quality trends and recommendations​) & source traceback​
  • Provides GUI based guided decision making and Interface engine agnostic actionable dashboards​
  • Cloud hosted solution with minimal on-premise footprint – easy and cost effective deployment

Learn more about H-IQM >

H-CDP (Data Integration Adaptors/ Parsers)

H-CDP –  a modular solution for acquiring, parsing, validating & persisting structured / semi-structured clinical & claims data.

  • Enables business user driven data lifecycle management for providers and payers to improve quality scores
  • Pipeline builder” capability to create data pipeline using pre-built components – parsers (CCDA, HL7, X12), data quality, standardization, transformation and reconciliation
  • In-built audit, logging and lineage capability along with ready adapters for apache atlas, Cloudera Navigator etc.
  • Is compatible across major Hadoop distributions including Hortonworks, Cloudera, Azure HDInsights, Azure DataBricks etc

Learn more about H-CDP >

Master Data Management

Allowing customers to proactively manage and monitor data curation to ensure high-quality data to use in downstream systems.

  • Data quality, data normalization and data reconciliation to enable MPI capabilities
  • User configurable rules library for master data management
  • Actionable insights with advanced analytics for data quality reporting
  • Reporting from different perspectives allowing data lineage and root cause identification

Network Intelligence

Management of automated analytics and messages going to patients, care givers, care managers and providers to drive proactive decision making at the right time and place.

  • Analytics-driven insights available at the point and time of decision making
  • Real-time and automated analytics to monitor organizational KPIs
  • Reduced alerts fatigue by setting threshold and triggering notifications to solve systemic problems
  • Management of patients, processes and staff in real-time to ensure maximum efficiency and effectiveness
  • Personalization of rules for individuals KPIs and thresholds

H-Scale: Healthcare Data Integration

Why H-Scale?

Accelerate the use of big data technologies, while addressing data security, access management and interoperability challenges in healthcare.