How to Leverage Your EDI 837 Data in Snowflake

EDI 837 data: It’s a common term in the healthcare industry, but how well do you understand its function for your organization, and could you be doing more with it?
March 31, 2023
Share
How to Leverage Your EDI 837 Data in Snowflake - EDI 837 data - Hakkoda

The Healthcare Electronic Data Interchange (EDI) is a method of exchanging data between businesses in a standardized electronic format. Specifically, the 837 EDI data file is a standardized electronic format for healthcare providers to submit insurance claims to payers. The 837 file contains information about the healthcare services provided to the patient, including patient information, provider information, diagnosis codes, and procedure codes. With all of this valuable information stored in one file, healthcare providers have everything they need to contact insurance companies for payment. 

This article will focus on the role of 837 files in healthcare as well as how to effectively segment and parse EDI 837.

Types of EDI 837 Data Files in Healthcare

Each type of EDI 837 data files has its own unique requirements and specifications. It’s important for healthcare organizations to ensure they are using the correct version of the 837 file for the type of services being provided as well as to comply with payer requirements. The EDI 837 file comes in several different versions or types, such as:

  1. 837P – Professional claims: Used by healthcare providers to submit claims to payers for services provided to individual patients.
  2. 837I – Institutional claims: Used by hospitals and other institutional providers to submit claims to payers for inpatient and outpatient services.
  3. 837D – Dental claims: Used by dental providers to submit claims to payers for dental services provided to patients.

How the EDI 837 Data Format Is Leveraged in Healthcare

The usage of EDI 837 files is widespread in healthcare organizations because it’s the standard format for electronic submission of insurance claims to payers. Virtually all healthcare providers, including hospitals, clinics, and individual practitioners use EDI 837 files to submit claims to insurance companies for reimbursement.

The use of EDI 837 files has several benefits for healthcare organizations, including improved efficiency and accuracy in claims processing, reduction of errors and rejections, and faster reimbursement times. By using a standardized electronic format, healthcare organizations can streamline their claims submission process, reduce administrative costs, and increase revenue.

In addition to claims submission, EDI 837 files are also used for other healthcare-related transactions, such as eligibility verification, claim status inquiries, and remittance advice. As the healthcare industry continues to adopt electronic systems and move towards interoperability, the usage of EDI 837 files is expected to continue to grow and evolve.

Why Do We Parse EDI 837 Data Files?

Parsing EDI files, including the 837 file, is essential for healthcare organizations to efficiently process and manage their claims. The 837 file contains a large amount of data that needs to be accurately captured and processed. The good news? By parsing the 837 file into structured data, healthcare organizations can automate their claims processing and reduce errors and delays.

Parsing also enables healthcare organizations to perform data analysis and reporting. When converted into structured data, healthcare organizations can easily extract and analyze specific data points, such as the number of claims submitted or the total amount of claims paid.

Segmentation of EDI 837 Data Files

As you’ve probably discerned already, the format of the 837 files is not easily understandable. The 837 file is divided into segments, which are further divided into data elements. Each segment represents a specific type of data, such as patient information, provider information, or claim information. Every data element contains specific information, such as the patient’s name, date of birth, or diagnosis code.

In EDI 837 files, segments play a critical role in organizing and formatting the data being transmitted. These are individual units of data that contain specific information related to a particular transaction or aspect of a claim. Segments are identified through a unique three-letter code that specifies the type of data being conveyed.

Segments exist to provide a standardized way of organizing and transmitting data in EDI 837 files, which helps to ensure accuracy and consistency in the data being transmitted. Each segment is designed to contain specific types of information, such as patient demographics, provider information, diagnosis codes, and procedure codes.

Segments can also be repeated within a transaction to accommodate multiple occurrences of the same type of information. For example, the SV1 segment is used to convey information about a single service line on a claim, but this segment can be repeated multiple times to accommodate multiple service lines.

Using segments in EDI 837 files helps to ensure that data is transmitted accurately and efficiently between healthcare providers and payers. Transmission, errors and rejections can be reduced through a standardized format, and claims processing times can be shortened.

How Do We Parse EDI 837 Data Files Using Snowflake?

Snowflake is a cloud-based data warehousing platform that enables organizations to store, process, and analyze large amounts of data. Snowflake provides several tools for parsing EDI files, including the use of external functions and Snowpipe and existing Python or Java libraries. Snowpipe is a continuous data ingestion service that enables organizations to automatically load data into Snowflake. With Snowpipe, organizations can parse EDI files as soon as they are received, enabling real-time data processing.

Are EDI 837 Data Files Being Replaced?

While the healthcare industry is moving towards more advanced electronic systems and standards, EDI 837 files are still widely used for claims submission and other healthcare-related transactions. However, there are other formats and standards that are being developed and implemented in the healthcare industry, such as FHIR (Fast Healthcare Interoperability Resources) and HL7 (Health Level Seven) messaging standards.

FHIR is a modern healthcare data exchange standard that uses web-based APIs to enable real-time data sharing between different systems and applications. It is designed to be lightweight and flexible, making it easier to implement and use compared to traditional standards like EDI 837. FHIR is gaining popularity in the healthcare industry, and some organizations are using it for clinical data exchange and other applications.

HL7 is another messaging standard used in healthcare, which defines a set of rules for exchanging clinical and administrative data between different healthcare applications. It is widely used for electronic health records (EHR) and clinical information systems. While HL7 is not a replacement for EDI 837, it is another important standard in the healthcare industry that complements and enhances the functionality of EDI 837 files.

Overall, while EDI 837 files are still the standard for claims submission and other transactions in the healthcare industry, they may be complemented or replaced by other standards and technologies in the future as the industry continues to evolve and adopt new technologies.

How Can Hakkoda Help?

Our healthcare data experts have backgrounds across the payor and provider ecosystem; many joined Hakkoda after leading teams at some of the largest healthcare organizations in the US. What all Hakkoda healthcare experts have in common is a commitment to using data to make healthcare more effective, efficient, and forward-thinking. 

Our healthcare data practice specializes in helping your organization process and parse complex files, power interoperability, and ultimately, improve patient outcomes while reducing operation costs. If 837 files are your challenge today, our team can parse them out in a structured format that is understood by IT professionals. Contact one of our experts today to build solutions and power better insights with your data.

Hakkōda 2024 Generative AI State of Data Report: 85% of Organizations Expect to Have Implemented Generative AI data tools by Year's End

Hakkōda 2024 Generative AI State...

Education, government and healthcare lag behind all other industries in Gen AI deployment.
Unlocking the Full Potential of Snowflake for SAP Data with Hakkōda

Unlocking the Full Potential of...

Although many organizations deploy tools alongside SAP to maintain enterprise functions, cross-functionality can be limited. Snowflake offers a platform where…
Summit 2024: Retail and CPG Data Insights and Trends from Modernization to AI

Summit 2024: Retail and CPG...

Explore some of the biggest retail and CPG data insights, themes, and takeaways from Data Cloud Summit 2024, including data…

Never miss an update​

Join our mailing list to stay updated with everything Hakkoda.

Ready to learn more?

Speak with one of our experts.