EDI parser

Technology to translate and Parse x12 eDI files

What is an EDI Parser?

An Electronic Data Interchange (EDI) parser is engineered to read 5010 HIPAA data from an X12 ANSI file into a rich EDI .NET Object model.  A developer can interact and code against that API with an EDI C# object loaded into memory.  This is a powerful way of quickly reading EDI, enriching with rules, and implementing custom lookup logic. An EDI Software solution like T-Connect provides advanced EDI parsing capabilities. 

Some of the major Segments parsed include:

  • ISA / IEA is the first segment that the EDI parser reads to begin the interchange.  It is typically referred to as the “outer envelope” of the EDI document.  Crucial info contained in the ISA is the segment, element and component separators and delimiters that help that dictate how to read the EDI content..
  • GS / GE is referred to as the “functional groups”. Each interchange between EDI trading partners may contain functional groups. Each instance of a functional group applies to a specific business function, defined by the specific application to which it applies.
  • ST / SE contain transaction sets containing loops and segments such as claim lines, EDI 834 Enrollment additions and terminations, etc.

Figure 1 - Sample 834 EDI File as ANSI X12

Parsing EDI 834 files

This is Caliber Health’s Free EDI editor tool (X12 Studio) that uses our T-Connect’s EDI software provides a robust EDI parser with a graphical interface to navigate, validate EDI, and edit EDI in a hierarchical format.

Figure 2 – Sample EDI 834 file viewed in X12 Studio, our free editor

EDI 834 File Validation

Next, looking at our EDI parser object model, it’s just a couple lines of code to fully interact with our EDI parser C# object model:

Figure 3 - Example of interacting with object model

T-Connect’s EDI Parser engine is our secret sauce.

It is light years ahead of any alternatives.  T-Connect EDI Software is enterprise grade to handle millions of claims or enrollments WITHOUT splitting.  We’ve replaced EDI parser solutions out there that claim to be performance focused but start to run into EDI performance bottlenecks with very large files that contain many ST segments.  In one of our most recent customers, we’ve replaced an “industry leader EDI solution” with T-Connect’s EDI parser engine and the process went from 8 ½ hours to only 28 seconds.

Our EDI Parser engine is developed from the ground up and utilizes the latest innovations available.  We focused on areas that other parser engines fall short of like speed, human readable validation results, non-cascading validation errors, and an object model that can be queried.

How do we get that speed?

Any developer can generate an EDI Document Object Model (DOM) from a schema, but T-Connect has 1,000s of hours invested in the EDI parser solution to provide developer friendly, rich object model methods, and querying object capabilities.  We utilize X12.org TR3 schemas and have a partnership with Washington Publishing Company (WPC). Our customers can feel confident they are getting the proper HIPAA Compliance SNIP validation and all included Segments, Loops, and Elements.

Provides EDI Validation

An EDI Parser for healthcare should provide EDI validation that translates and ensures documents are accurate.  In Healthcare, this level of validation is typically referred to as SNIP Levels 1 and 2.  The EDI parser engine must perform EDI validation and return the results as an acknowledgement (999 ACK).  Our EDI parser has a very user-friendly EDI validation text results that allows users to quickly navigate and remediate or report the error.

WEDI SNIP Level 1

When T-Connect’s EDI Parser validates to SNIP Level 1 requirements, it looks for EDI standard integrity.  It ensures that the EDI file can be parsed and includes Snip 1. It check for things like checking if segments and elements are actual expected segments – ex: not a string blob and the data types of the elements as well  (numbers are numbers).

WEDI SNIP Level 2

T-Connect EDI software tests if the X12 validation results align with the HIPAA implementation guide, that is specific to a companion guide.  It checks required segments and elements, repeat counts, intra segment requirements (ex: if REF01 element exists then the REF02 must as well).  It also checks for min and max occurrences as well.

Our EDI Parser engine also supports higher SNIP Levels 3-7.  We have written a few blogs on SNIP 3, SNIP 4, SNIP 5, and SNIP 6.

EDI Parser Utilities

T-Connect’s EDI parser engine goes beyond EDI validation and EDI processing speed.  We have created “smart” utilities and EDI tools that are commonly used in the healthcare space.  This really sets us apart from our competition because we are laser focused on HIPAA X12 ANSI document types and the business problems they face.

Splitting EDI files

Our EDI Parser can easily be configured to start splitting EDI files in many different ways.  Split by ST, record count, rebalance the files after splitting, segment value (e.g. By NPI).

EDI Enrollment 834 Optimizer

Wouldn’t it be great for an EDI parser that can process a large monthly 834 EDI file and sort by transaction type, split by transaction type: Adds / Terms / Changes / Reinstatements, and even throttle those files into an adjudication system, database, or file folder?  Our T-Connect EDI parser does this with a few simple configurations.  Add in your custom member lookup hook into the API for a complete and optimized 834 EDI parser solution.

EDI to Claim UB-04 and CMS1500 PDF Forms

Our EDI Software also provides an out-of-the-box solution to easily parse 837I and 837P claims and generate PDF standardized forms with that EDI data.

Figure 4 - Sample CMS1450 (or UB-04) form from an 837I EDI file

Sample UB04 Form

Extracting Invalid Records

A common problem for most EDI parser translators, is handling invalid EDI records.  There are typically two ways – 1) reject the entire file with a 999 when the EDI validation process encounters a SNIP level error. 2) Continue processing the valid records, and split out the invalid records into a new file.  T-Connect’s EDI parser supports both methods.  In this utility, we will discuss how to handle the second way – extracting invalid records after the EDI validation process.

Establishing a unique identifier for each record is paramount. Our EDI parser utilizes the ST02 value and stores that in a list while the EDI validation is being performed.  Once the parser completes the validation process, the solution utilizes our EDI split methods.  One important consideration is to make sure the GE01 count is properly updated with the correct adjusted counts.  T-Connect takes care of all of this out-of-the-box.  With a simple configuration setting, the EDI parser and EDI validation engine will automatically start to extract the invalid records.

Once the EDI parser extracts the invalid records, a popular configuration is to send the invalid records to a separate file folder directory.

QNXT Connect Optimizer 

QNXT is utilized by many health plans as a claims adjudication system.  Our T-Connect EDI parser engine provides additional utilities to improve the intake into QNXT Connect (which uses BizTalk Server). We provide easy to adopt plug-ins to increase EDI speed and optimize the QNXT intake process.  Comparing EDI software to find optimal speed, tracking, and database persistence is key to improving the overall EDI process.

A great EDI parser engine can pre-process the EDI files prior to QNXT Connect.  T-Connect EDI Software can provide the EXACT validation as QNXT Connect (BizTalk under the hood) so that the EDI files can be smoothly processed after going through a better managed parsing solution.  Another big concern is tracing EDI when issues happen within the lifecycle process.  T-Connect has pre-built EDI parser and EDI validation utilities that plug into the Plan Data database as well as QNXT pre and post processing agents.

Figure 5- Example of QNXT Optimization and Performance Flow

QNXT EDI Optimization Flowchart

EDI to Relational Database

Most EDI parser translators treat EDI as transient messages.  T-Connect’s EDI parser engine stores the complete entire EDI segments, loops, and data elements with one simple method call.  From there, you can ETL, report, and create custom correlations on data previously processed.  Additionally, some of our customers have created their own data access layer persisting code and write directly to their existing database or API.  Our T-Connect EDI Database Plus SDK solution can also be utilized to write directly into a “data lake” to support big data needs with all the hooks to tag key data elements.

Figure 6- T-Connect EDI Parser saving to relational database

Parsing to EDI Databases

Generate Sample EDI Files

Most healthcare companies that utilize EDI parser engines need a solution to generate test files for testing purposes.  A pre-built solution is available with any of our T-Connect EDI Software solutions – even our free EDI Editor Tool, X12 Studio Toolbox Pro. This solution can generate SNIP 1, 2 valid EDI sample files and generate the corresponding 999 ACK.

Figure 7- X12 Studio utilizes our EDI parser schema to generate HIPAA Sample EDI files

Sample EDI File Creation

Sample EDI File Generator

Generate 999 Acknowledgements (ACK)

An EDI parser for healthcare should be capable of producing a validation result file that describes what EDI records were invalid.  This is mostly used when EDI files are sent between trading partners and those partners host or comply with a companion implementation guide.  Typically, HIPAA 5010 acknowledgements take the form of a 999 ACK.  The AK9 indicates if the file was accepted with the code ‘A’ or rejected with ‘R’.

  • IK501 – details acceptance or rejection of the transaction sets (ST)
  • IK3 segment in AK2/IK3 Loop – details segment and looping errors in the transaction
  • IK4 segment lists data element errors in the transaction

Figure 8- A sample 999 shown in T-Connect X12 Studio with AK9 code 'A' as accepted

EDI 999 Ack Generator

Build versus Buy

If you are thinking about building an EDI parser script or translator, here are some reasons you may want to compare EDI software as an alternative:

  • No HIPAA Compliance validation, SNIP 1 and 2
  • Parsing may become process intensive and slow
  • Developer labor intensive and costly
  • Difficult to Test and QA an entire 834, 837I or 837P
  • Can’t scale as an enterprise solution
  • X12.org TR3 Schemas are published only by WPC, which may require a partnership and added expense

T-Connect Products

Check out our EDI Parser as you compare EDI software to see which one is right for you.

SDK for Developers

Database plus SDK for Developers

EDI Gateway, Enterprise Suite