SaaS based Enterprise Electronic Health Record System


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A SaaS based enterprise BIG Data application for maintaining Electronic Health Records (EHR).

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SaaS based Enterprise Electronic Health Record System

  1. 1. HSTC8302 SAAS BASED ENTERPRISE ELECTRONIC HEALTH RECORD SYSTEM ©2013 Harbinger Systems. All Rights Reserved
  2. 2. HARBINGER SYSTEMS Overview Technologies Harbinger Systems is a leading provider of software engineering services to some of the world's best product companies. Our services span solution consulting, software design, development, testing and test automation.  Mobility  Enterprise Software Development  Cloud  Open Source Development  Web Applications  Advanced Testing Services  Open Sources  BI and Analytics By leveraging cutting-edge technologies, Harbinger Systems works with its customers as a partner in technology innovation. Services   Performance Engineering  Security Testing   Systems Testing Test Automation eLearning Solutions A Harbinger Systems Case Study Also Read Our White Papers… Industries Comparing Adobe Flex & JavaScript The Enterprise Software Makeover Guide Five Javascript Frameworks: A Point-by-point Comparison Software Product Companies  Mobile Application Developers  Healthcare Companies  Consumer Internet Companies  High-Tech Systems Vendors  Interactive User Experience (IUX): Going Beyond Interfaces  eLearning Follow us: Blog | Twitter | Facebook | SlideShare | LinkedIn ©2013 Harbinger Systems. All Rights Reserved
  3. 3. SAAS BASED ENTERPRISE ELECTRONIC HEALTH RECORD SYSTEM Situation Challenge Startup ISV in healthcare domain wants to develop a SaaS application for hospitals and medical institutions ISV has acquired a company with huge database of health related records stored using legacy database (GT.M) with size more than 500 GB ISV userbase is growing rapidly. They want to quickly access user details from huge dataset and also cope up with this growth leveraging a big data technology stack. Need to develop a SaaS platform that supports both, legacy system features and migration to Big Data technology stack at same time Migration of existing dataset from old DB system into NoSQL database with added flexibility and extensibility Implementing optimized integrated solution to support scalability in both data storage and data look up Harbinger Solution Devised a unique approach of storing the data simultaneously in GT.M and Hbase. RPC connector implemented for connection APIs between Mumps procedures i.e. legacy application and GT.M. Hbase communication was achieved using DataNucleas APIs. A migration framework was built using MapReduce job for transferring existing data into Hbase. Framework provides ability for one on one as well as schema level mapping between fields or tables for copying data from source [GT.M] data store into target [Hbase] data store. Multiple technology options were evaluated. Implemented a solution using Zookeeper for distributed coordination among Hbase, Hadoop and Solr cluster to achieve consistent performance and scalability. NoSQL Database type by means of Hbase and Hadoop was used to address huge data size and unstructured data model. Integration with Solr implemented for faster data retrieval. Benefits Support handling of both Relational and NoSQL schema in parallel on rapidly growing data Technologies & Tools Hbase , NOSQL DB JAVA Solr Apache Kafka – messaging system Optimal use of legacy system & data store helped client in supporting existing customers. And incremental upgrade to use Big Data technology stack equipped the client to cater to the growing user base and data, effectively. Migration framework implemented using MapReduce Jobs resulted into smooth data migration in very short time. Also generic implementation approach resulted into reusable components, saving overall cost and time needed for development. Integrated solution using Hadoop, Hbase & Solr helped in implementing a scalable & distributed storage system to support faster search and high throughput. This resulted in a smooth user experience, generating complex summary reports easily and increasing user base efficiently. Use of NoSQL DB resulted into additional support for unstructured schema model, enabling system to process billions of records very fast to generate analytical reports on patient records and disease trends which were almost impossible to implement using legacy implementation on commodity hardware. Hadoop BOTTOM LINE A SaaS based enterprise BIG Data application for maintaining Electronic Health Records (EHR). ©2013 Harbinger Systems. All Rights Reserved