Every Code Matters—Get It Right the First Time

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Two Models, One Goal—Efficient Diagnostic Coding

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API Plan

Ideal for organizations that want to integrate diagnostic code mapping into existing workflows without a complete software overhaul.

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Quick Deployment: Start integrating in minutes, not months.
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Scalable Infrastructure: Adjust usage as your business grows.
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Cost-Effective: Low upfront costs.
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Ease of Integration: Works effortlessly with your EHRs, billing software, or custom tools.
API

ROI

In healthcare, precision isn’t just a goal—it’s a necessity. Accurate coding is the first step to better operations, stronger compliance, and improved patient care.

Why It Matters

Easier Compliance with Standards

Whether it’s ICD-10, ICD-11, or SNOMED CT, staying compliant is easier with a standardized tool. Avoid the fines or delays caused by incorrect or outdated codes.

Reduced Billing Errors

Accurate coding leads to fewer rejected claims, improving your revenue cycle by as much as 30%. This ensures quicker reimbursements and less back-and-forth with payers.

Time Savings That Count

Manual coding takes time. By automating these processes, organizations typically reduce coding time by 40-60%, freeing up staff to focus on patient care instead.
Features

Key Features

Whether you’re a healthcare provider, researcher, or insurer, our Diagnostic Code Mapping Tool helps you achieve greater accuracy, efficiency, and compliance. Get in touch to see how we can help streamline your coding processes and improve patient outcomes.
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Diagnostic Code Mapping

Effortlessly map existing diagnoses to ICD-10/11 or procedures to SNOMED codes using advanced machine learning models.

Diagnostic Code Interpretation

Decode unstructured clinical notes or summaries into standardized ICD or SNOMED codes using Generative AI.

Seamless Integration

Integrate the tool with your Electronic Health Records (EHR) system for real-time updates.
How it works

Workflow

Our diagnostic code mapping tool is designed to ensure accuracy, efficiency, and seamless integration. We work closely with your team to streamline the conversion of medical terms into standardized codes, enhancing interoperability, improving billing accuracy, and ensuring compliance with local and international healthcare regulations.

Uploading Clinical Documents

Users can drag and drop or browse to upload clinical summaries in various formats (PDF, TXT, CSV, etc.)

Automatic Extraction of Diagnoses & Procedures

Prepare and standardize data by cleaning, formatting, and structuring it for analysis.

Code Mapping

Leverage matching algorithms to map extracted entities to diagnostic codes (e.g., ICD-10, CPT) with ranked suggestions and human oversight for validation.

Validation and Quality Assurance

Conduct error checks, implement feedback loops, and ensure compliance with regulatory standards for high-quality diagnostic coding.

Delivering Usable Results

Export structured data in formats like XML, JSON, or CSV and enable interoperability with EHRs, billing systems, and reporting tools.
Latest STORY

Success Stories: Case study

Data Warehousing Solution for a Small and Medium Enterprise (SME)

A growing SME healthcare provider faced challenges managing fragmented data, ensuring compliance, and generating actionable insights. Inginit implemented a robust, secure, and scalable on-premise data warehousing solution, enabling seamless integration of systems, automated workflows, and real-time reporting while adhering to stringent compliance standards like HIPAA and GDPR.

Cloud-Based Data Warehousing with Snowflake for a Healthcare SME

A healthcare SME in the UAE faced challenges with fragmented data systems, compliance requirements, and real-time reporting. BIOTEKNIKA implemented a secure and scalable Snowflake-based data warehousing solution, streamlining operations, enabling seamless integration, and ensuring compliance with UAE healthcare regulations and HIPAA.

Data Warehousing for a Research-Focused Healthcare Institution

A leading clinical research institution specializing in oncology partnered with BIOTEKNIKA to overcome challenges in managing and analyzing fragmented data across clinical trials and patient studies. Using a Snowflake-powered data warehouse, BIOTEKNIKA enabled seamless data integration, enhanced collaboration, and compliance with global and regional regulations, all while adhering to the client’s on-premise preferences for secure operations.

Centralized Data Warehouse for a Multi-Site Hospital

A multi-site hospital system in the Middle East faced challenges with fragmented data systems, inefficient reporting, and compliance with regional healthcare regulations. BIOTEKNIKA designed and implemented a robust, secure data warehousing solution using PostgreSQL and Superset, enabling seamless data integration, improved decision-making, and faster reporting.

Latest posts

Blog

Interviews, tips, guides, industry best practices, and news.

From Notes to Codes: A Simple Walkthrough of Diagnostic Code Mapping with Bioteknika

This blog explores Bioteknika’s diagnostic code mapping interface, which uses a hybrid AI approach to suggest ICD-10 codes based on confidence scoring. Includes real input/output examples and a breakdown of both upload-based and manual entry workflows.
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ICD-10, ICD-11, SNOMED CT, and Code Mapping: Everything You Need to Know

ICD-10, ICD-11, and SNOMED CT are essential coding systems in healthcare, each serving different purposes—from billing and public health tracking to detailed clinical documentation. To bridge these systems, diagnostic code mapping translates clinical terms between terminologies like SNOMED and ICD. This ensures accurate data exchange, faster reimbursement, and better decision support. Understanding and implementing proper mapping strategies is key to building interoperable, efficient healthcare systems.
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How to Simplify ICD and SNOMED Interoperability Across Systems

ICD and SNOMED serve different roles in healthcare—one for billing and reporting, the other for clinical documentation and decision support. Bridging these systems is essential for accurate data exchange, consistent coding, and reliable analytics. This blog outlines five key strategies for simplifying interoperability: defining use-case-driven mapping, implementing real-time bidirectional translation, validating mappings with real clinical data, accounting for diagnostic context and hierarchy, and maintaining versioned, regularly updated maps. A thoughtful, tech-enabled mapping approach ensures diagnostic data is understood the same way across systems—supporting better care, compliance, and collaboration.
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