ABI Conversion to Health Edge Lineage Methodology

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Transformation, Heritage, and Enlightenment

Historical Data knowledge used to guide results and ensure accuracy into the New World –Health Rules.

        •Stored knowledge of where the data:
                              • Originates
                                    • Intersects
                                          • lands

Overall Combined Approaches

Holistic approach –
•Work with Business to gather requirements.
•Convert data into Executive level Presentations to provide an end to end view of the product.
•Recycle gathered conversion information to assist in build out of Data Warehouse Reporting.
Walk thru approach –
•Utilize Power Point, Spreadsheets, and MS Project to enable complete visualization of ABI Methodologies and state of the art Solutions.
•Collaborate with Business Users regarding established deliverables.
•Compile worksheets or understandings of work flows and Cross Reference data that will be implemented by ABI.
Collaborative approach –
•Communicate with Business Leads to tunnel project deliverables into collaborative Training and Business Process documentation – enabling the business to own individual SAAS tool kit utilization going forward.
IRA ABI ETL PIC
Details on approach
1.Heavy use of advanced metadata and code generation
2.Quickly generate Health Rules Loader Staging tables directly from Health Edge metadata specification spreadsheets.
3.Generate SSIS Packages directly from Source using Metadata Mart and Custom SSIS Code Generation tools.
4. Advanced Data Profiling and permanent  Metadata Mart supporting Data Lineage.
5.Double Mentoring all code is fully explained, documented and left behind.
ABI Methodology Slide

ABI Methodology Slide

Health Edge Loaders

Health Edge Loaders

ABI Comprehensive knowledge of
Health Rules Entity Relationships

Health Edge Entity Relationship

ABI Iterative Approach

Business Requirements Matrix

ABI Business Requirements Matrix

Best Practices integrating
Data Profiling within Data Conversion/Migration.

  • Next Generation Profiling tools utilized to prevent future “dirty” data from entering Vendor Application and/or Data Warehouse.
  • Record audit enforced to address any data that is not matched within the load process to analyze and either re-load if needed or bypass due to duplication.
  • Maintain ability to access historical data within the new Application and/or Data Warehouse.
  • Provide Enterprise Solution that is scalable, flexible, and intuitive.

Client Defines Use Cases for Load

  •  Include high volume business partners – providers, hospitals
  •  Include major hospital systems, as these will often require manual conversion.
  •  Include largest claim submitters, as these will often be the messiest.
  •  Identify cases in which the provider file causes a lot of trouble or workaround   (potentially in relation to claim matching, claim payment, provider contracting, reporting, or other processes)
  •  Include cases in which the provider file is expensive/difficult to maintain
  •  Include cases in which there are strange “workarounds” in the provider file
  •  Cases in which an organizations (facility) resemble practicing individuals and practicing individuals that resemble organizations
  •  Examples of a Practitioner working at different facilities and specialties

ABI Importer

Automated code generation utilizing the ABI Importer:

  • Imports Comma Delimited flat files into SQL Server Staging tables.
  • Enable users with no knowledge of SSIS/Visual Studio to import flat files into SQL Server.
  • Auto generates DDL or Staging Table
  • Auto generates SQL Script for SSIS Package.
  • Allows for SSIS Users to import flat files faster and enables SSIS Users to work within package after initial load.

ABI Importer Pic       SQL MGMNT STUDIO PIC

SSIS Integration within ETL

The files required to load HR will be produced by the SSIS ETL code which will combine master data from the MDS database and supporting transactional information from legacy systems as defined by the data specification.

SSIS PIC

Load Testing Reporting and Analysis

HE Errors pic

Data Movement Pic

Conclusion

•Proven Iterative Approach
•Cleansed data within Health Rules
•Accessible Audit trail (LINEAGE) – simplify  issues analysis
•Effective Project Deliverable (Matrix) linking Business Process to Entity/Attributes
•Comprehensive Business Process ensuring solid future proof user configuration
•Marketable rapid implementation methodology and application architecture

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