Healthcare Data Pipeline for healthcare data ingestion, aggregation and standardization  

Healthcare organizations today need to effectively aggregate healthcare data from diverse source systems to create longitudinal patient records and better quantify performance. However, they face multiple data challenge around data ingestion and processing, due to large volumes of data received from varied source systems in multiple formats.

Download the HDP Brochure
Login with LinkedIn or Google for a seamless experience
OR
Enter your information
  • Yes, I would like CitiusTech to contact me based on the information provided above. Read our Privacy Policy for details on how your information may be used

To overcome these challenges and to make integration of clinical data scalable and future-proof, healthcare organizations need a robust and scalable data acquisition solution that also drives downstream use cases.

CitiusTech's HDP (Healthcare Data Pipeline), is a state-of-the art solution that enables healthcare organizations to acquire, parse, validate and persist structured / semi-structured healthcare data. The solution includes specialized modules for data parsing, data quality, data standardization, MPI, storage and ETL. With HDP, healthcare IT and analytics teams can not just ingest and process clinical data, but also to consume it in standardized formats.

HDP enables IT and analytics teams design and deploy their own data pipelines using a simple ‘Pipeline Builder’ feature. It provides a highly configurable user interface that allows teams to set rules for data transformation, standardization and reconciliation.

 

 

Key Solution Highlights:

  • Reusable parser framework to streamline clinical data ingestion and processing across formats such as CCDA, HL7 and FHIR
  • Apache Spark based scalable engine to meet the speed of business
  • Simple ‘Pipeline Builder’ functionality - parsers, data quality, standardization,  transformation, reconciliation and storage
  • Modular, scalable and self- managed components for data lineage and data lifecycle management

 

" " " " " " "" " " " " " "