Data Management

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Healthcare organizations today need to build best-in-class capabilities and mature solutions around EDW, big data, predictive modelling, machine learning, streaming analytics and real-time information sharing. They also need to address multiple challenges around data integration and management.

The CitiusTech Data Management Proficiency designs and supports architectures, policies, practices and roadmaps, to address the information needs of a healthcare enterprise.

The highlights of the proficiency are:

  • Strong consulting capabilities to address lifecycle needs – data capture, quality, management, transmission and streaming analytics
  • Industry standard data adapters (HL7, CCD, QRDA, etc.), utilities, best practice and KPIs
  • A comprehensive suite of managed services, including certified teams, technology expertise and best-in-class frameworks / methodologies

Data Management: Practices

The CitiusTech Data Management proficiency supports development and execution of architectures, policies, practices and roadmaps, to address the information needs of a healthcare enterprise.

Healthcare IT, Citiustech

Integration & Interoperability

  • Interoperability standards – HL7 v2 / v3, EDI X12, CDA, NCPDP, DICOM, LOINC, SNOMED, FHIR
  • IHE Profiles - PIX / PDQ / XDS
  • EAI tools – Rhapsody, Cloverleaf, Ensemble, Iguana, BizTalk, IBM Integration Bus, TIBCO
  • Integration with EPIC, Cerner, AllScript, eClinicalWorks and others
  • Integration of both structured and unstructured data sources
  • Out-of-the-box data adapters and Big Data accelerators
  • Real-time data integration and streaming analytics

EDW Strategy & Planning

  • Consulting and assessment - EIM strategies, EDW design
  • Modern data warehouse reference architectures and implementation guides
  • Enterprise data models – QDM, FHIM, OMOP, UDMH, I2B2, SHRINE
  • Data governance tools – Idera, SQLMDS, IBM InfoSphere, Informatica MDM, SAP Master Data Governance
  • Exhaustive healthcare data quality rules library
  • Templates for interactive dashboards and reports with drill through / down features

Big Data

  • Big Data powered Modern Data Warehouse reference architecture
  • Big Data architecture as an enabler for Streaming Analytics, Machine Learning, Deep Learning
  • Hadoop distributions - Hortonworks, Cloudera
  • NoSQL datastores - HBase, Cassandra, Hive, Impala
  • In-memory computing – Apache Spark, Ignite
  • Real-time processing – Apache Spark, Storm
  • Leveraging Cloud platforms (AWS, IBM, Microsoft Azure)
  • CitiusTech accelerators - parsers, rules engine, data quality to reduce time-to-market