Tuesday, 02 January 2024 12:17 GMT

IRI Supports PHI De-Identification For HL7, X12 & FHIR EDI Files


(MENAFN- EIN Presswire)

PII / PHI data data masking wizards in IRI DarkShield

HL7 PHI element selection for DarkShield discovery and de-identification

Applying masking rules to X12 PHI in DarkShield

Data Discovery & Consistent Masking Functions in DarkShield for HIPAA Compliance

PHI data classes in the IRI Workbench GUI for DarkShield (and other data masking tools like FieldShield) support consistent definitions and rules for masking data and preserving referential integrity.” - Tylor QuinleyMELBOURE, FL, UNITED STATES, January 14, 2025 /EINPresswire / -- Innovative Routines International (IRI), Inc., a/k/a The CoSort Company, has added data discovery and de-identification for healthcare EDI files in HL7, X12 and FHIR formats to its DarkShield data masking package. New fit-for-purpose job wizards allow DarkShield users to define key protected health information (PHI) groups with additional control over segments and fields in each of these file formats as data classes, and thus mask them consistently.

HL7 (Health Level Seven) files are a set of messaging formats and clinical standards that define how healthcare systems exchange, integrate, manage, and retrieve electronic information. The HL7 data classification and masking wizard for DarkShield is documented in this blog article:


The X12 standard governs the exchange of business documents (e.g., purchase orders, invoices, healthcare claims, etc.) in standard electronic formats between trading partners – for example, the EDI 837 Health Care Claim Transaction Set. The DarkShield X12 wizard is documented in this blog article:


FHIR (Fast Healthcare Interoperability Resources) files are documented in a newer format to represent healthcare information, such as clinical observations and services, as well as non-clinical data such as patient information or practice guidelines. The DarkShield FHIR wizard is documented in this blog article:


PHI data classes in the IRI Workbench GUI for DarkShield (and other IRI tools like FieldShield, RowGen, NextForm, and Voracity) support consistent data definitions and rules for masking. By applying the same masking functions to like data elements, data and referential integrity is maintained after masking; i.e., these elements can still join with similarly masked values in PDF and Office documents, relational and NoSQL databases, and files in semi-structured, sequential, text, Parquet and image formats.

According to IRI Software Engineer Tylor Quinley, these wizards enable DarkShield users to“quickly pick out the common PHI groups or individual PHI segments across all the EDI formats. This allows for minimal or no user input in order to discover, report on, and mask the data in one pass. Prior to these wizards, such jobs required manual pattern definition at design time, and slower pattern recognition at runtime, causing everything to take far longer.”

About DarkShield
DarkShield is a data classification, discovery and masking product that finds and protects sensitive information in structured, semi-structured, and unstructured sources of data on-premise and in the cloud. DarkShield can use multiple metadata and content matchers to locate data – including AI models for NER and signature detection – and includes a wide range of deterministic and random data masking (plus synthesis) functions. DarkShield is not SaaS; it runs in GUI, CLI, and API mode on customer hardware.

About IRI
Founded 1978, IRI is a Florida-based ISV providing fast data manipulation and granular data protection for private and public sector enterprises of all sizes. Represented in more than 40 cities worldwide, IRI is not only a recognized leader in the data masking market, but is also well known for its CoSort big data transformation and migration engine, and the versatile Voracity data management platform it powers.

Contact: Alyssa Ardhya, IRI
..., 321.777.8889, ext 211

Alyssa Ardhya
IRI, The CoSort Company
+1 321-777-8889
...
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EIN Presswire provides this news content "as is" without warranty of any kind. We do not accept any responsibility or liability for the accuracy, content, images, videos, licenses, completeness, legality, or reliability of the information contained in this article. If you have any complaints or copyright issues related to this article, kindly contact the author above.

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Legal Disclaimer:
MENAFN provides the information “as is” without warranty of any kind. We do not accept any responsibility or liability for the accuracy, content, images, videos, licenses, completeness, legality, or reliability of the information contained in this article. If you have any complaints or copyright issues related to this article, kindly contact the provider above.