Healthcare IT: Role of EDI in Affordable Care Act Reforms


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Technology leaders in Healthcare industry are faced with a changing technology and regulatory landscape.

At one end of the spectrum, the industry faces an increasingly tech-savvy population, a huge amount of data which needs to be processed using unconventional methods and the need to improve efficiency of healthcare delivery through effective use of technology.

At the other end, there is the challenge of ensuring that systems match the updated and /or evolving federal requirements, meet the privacy constraints and switch to the diagnostic and procedural codes.

It’s like walking a tight-rope with an extremely stiff timeline!

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Healthcare IT: Role of EDI in Affordable Care Act Reforms

  1. 1. Welcome to the Webinar on Healthcare IT: Role of EDI in Affordable Care Act Reforms By Harbinger Systems © Harbinger Systems |
  2. 2. Panellists Mandar Kulkarni Maheshkumar Kharade Marketing Manager Harbinger Systems Associate Architect Harbinger Systems © Harbinger Systems | 2
  3. 3. Agenda • • • • • • Challenges in Healthcare IT Project Case 1 Project Case 2 Project Case 3 Summary Q&A © Harbinger Systems | 3
  4. 4. Challenges in Healthcare IT Growing Data Real time Reporting and Access of Data Transition to New Standards Challenges in Healthcare IT Interoperable Systems to Create a Truly Enabling Healthcare IT Environment Security of Data Compliance Management © Harbinger Systems | 4
  5. 5. Case Study 1 • Business Problem Statement – 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 with size more than 500 GB – ISV user base 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 © Harbinger Systems | 5
  6. 6. Case Study 1 (Continued…) • Key Challenges – Quick Response time – Being a SaaS based application, System stores data for millions of patients – Every records contains 500+ fields with complex structure – Need to support quick look up using any field from patient record © Harbinger Systems | 6
  7. 7. Case Study 1 (Continued…) External Systems Data Files HBase Data Set Data Record Message Queue © Harbinger Systems | Solr Indexing S E A R C H E N G I N E 7
  8. 8. Case Study 1 (Continued…) • Highlights – Distributed processing of patient data using messaging queues – Indexing process runs on separate indexing server in the background – Call to index respective data sets based on inserts/updates – Reference to data location is indexed, search is two step i.e. find reference and then fetch actual record © Harbinger Systems | 8
  9. 9. Case Study 2 • Business Problem Statement – Streamline and automate the management, identification and resolution of compliance exceptions within the CMS regulated Medicare industry • Challenges – Manual process for understanding over few hundreds of business rules for compliance management – Develop a customizable and flexible model to facilitate varied customer needs and frequently changing compliance rules. © Harbinger Systems | 9
  10. 10. Case Study 2 (Continued…) Analytics External Systems Data Files Reports DB ETL Batch Process Business Rules © Harbinger Systems | Message Queue DRL(s) 10
  11. 11. Case Study 2 (Continued…) • Highlights – Use of ETL tools and jobs for simplified and fast implementation of import process for variety of data sources – Use of decision table for converting complex business rules into easy to maintain excel decision table format – Rule repository in the form of DRL files, to avoid runtime compilation of rules – Batch processing to operate on multiple records effectively – Messaging Queue implementation to offload DB updates and save data in Async call to improve performance © Harbinger Systems | 11
  12. 12. Case Study 3 • Business Problem Statement – In order to remain compliant, Medicare Advantage organizations must have solutions and processes in place to exchange adjudicated encounter data from health plans and data from certified professional coders with CMS. – Plans must have the ability to receive, store, submit and process all encounter data in a format and via a protocol specified by CMS © Harbinger Systems | 12
  13. 13. Case Study 3 (Continued…) • Key Challenges – The environment is characterized by often imperfect source data due to elements such as claims communications breakdowns, disorganized provider tables and incomplete source data originating from a chart review. – Further, the 837 format is very complex and the CMS requirements are far more extensive than exist for the current RAPS(Risk Adjustment) system. – This volume and complexity results in more opportunity for errors, exceptions and rejects of submitted diagnosis codes © Harbinger Systems | 13
  14. 14. Case Study 3 (Continued…) Worker 1 Claim Files [837 - 5010] Claim Files [Custom/ Old Formats] P R E P R O C E S S O R Validation Initiator Message Queue Validation Aggregator Worker 2 Validations - Syntax - CMS Rules - Situations [DT] -Member,Provider Worker n DB Message Queue © Harbinger Systems | 14
  15. 15. Case Study 3 (Continued…) • Highlights – Highly scalable architecture with an ability to add/remove worker nodes at run time – Step by step implementation for multiple validations, flexibility to plug-in/out validations as per requirement changes/customizations – Ability to map data from older/custom formats into standard specific schema by means of pre-processor © Harbinger Systems | 15
  16. 16. Summary • Big data solutions are way forward for handling growing data size • Frequently changing compliance rules can be handled using technology like Decision Tables, which enables defining rules outside code • For complex, multi stepped and time consuming processes, distributed and asynchronous processing is a good strategy to achieve desired system performance © Harbinger Systems | 16
  17. 17. Q&A © Harbinger Systems | 17
  18. 18. Thank You! Visit us at: Write to us at: Blog: Twitter: (@HarbingerSys) Slideshare: Facebook: LinkedIn: © Harbinger Systems | 18