The transformative power of artificial intelligence (AI) is evident across various sectors, indicating a paradigm shift in how businesses operate and compete. However, the healthcare industry is lagging when it comes to AI adoption. This is because most healthcare departments are still accustomed to a manual approach. Especially in healthcare revenue cycle departments, the manual process is leading to revenue loss and causing a huge burden on the admins.

The overall administrative costs in the US is skyrocketing accounting  for 30% of the US healthcare costs. In addition, the interpretation of complex medical information from patient medical reports has made healthcare administrators skeptical about adopting AI tools. While healthcare organizations look to improving their financial success, MediCodio’s AI medical coding solution emerges as a life saver for healthcare companies.

MediCodio’s AI Medical Coding Engine solves the existing medical coding challenges by automating the medical coding process using advanced technologies such as OCR, RPA, API, & LLM. The company has automated the medical code search process. For the last decade, the medical coding process in the healthcare facilities was done manually and was prone to errors.

With the help of CODIO, medical coders get the medical codes instantly without having to go through large manuals. CODIO, the promising AI-powered medical coding tool translates patient charts from medical reports into medical codes in seconds with over 85% accuracy. This allows RCM companies and healthcare providers to enhance coding quality and improve turnaround time and reduce medical coding costs by up to 35%.

The Barrier to Technology Adoption in Medical Coding

Healthcare revenue cycle management (RCM) involves managing and optimizing the financial operations of a healthcare organization, from patient registration and appointment scheduling to insurance claims processing and payment collection. Despite its critical role, many RCM processes are inefficient and costly. A major inefficiency lies in medical coding, a mid-revenue cycle process where medical codes are assigned to patient records for reimbursement. Traditionally, certified medical coders manually review patient records and select appropriate codes, a method that is time-consuming and expensive, especially for complex cases like surgeries or inpatient visits. Medical coding significantly contributes to the $256.6 billion spent annually on administrative complexity.

Currently, challenges such as a shortage of medical coders, narrow operating margins, and frequent updates to coding guidelines have led revenue cycle leaders to seek technological solutions. However, creating technology that can meaningfully improve medical coding efficiency, cost, and accuracy is difficult due to the complexity of clinical language. Physicians use nuanced language, medical terminology, abbreviations, context-dependent information, and duplicate content in their documentation, posing challenges for traditional natural language processing (NLP) technology.

Computer-assisted coding (CAC) software uses traditional NLP to identify key terms in medical documentation and suggest codes, which certified medical coders must then validate. Although CAC is an improvement over manual coding, its reliance on simple approaches like synonym search and dictionaries limits its ability to understand context, negation, and temporality, leading to inaccuracies in suggested codes and reducing efficiency gains.

Recent advancements in AI, particularly large language models (LLMs), offer potential for enhancing medical coding automation.

MediCodio’s AI Medical Coding solutions use various AI subfields, such as LLM, machine learning, RPA, and deep learning, to instantly and accurately assign codes to patient encounters, eliminating the need of sifting through manuals and PDFs. Automated medical coding has been well-received by RCM companies, hospitals, and other healthcare organizations, with a recent survey showing that around 60 percent either use or plan to use AI medical coding tools. By fully automating medical coding, healthcare organizations can significantly improve coding speed, quality, cost, and operational efficiency.

How MediCodio’s AI Medical Coding tool works?

To begin with, we get permission from clients to access their EMR/EHR system. We use RPA import to collect all the patient charts from clients’ EMR/EHR system and store it in a well-defined structured manner in the Dataverse. In the next step, the patient charts are uploaded to CODIO.

This is when MediCodio’s AI medical coding engine plays its part. CODIO analyzes the patient charts and instantly suggests relevant medical codes. A Coder then has to pick the codes and link it with the CPT and modifiers. Once the codes are finalized, the report is sent back to the EHR/EMR and then forwarded to the billing module.

Benefits of Automated Coding with MediCodio

The technology behind MediCodio’s automated medical coding engine delivers exceptional coding quality and compliance, customizable internal coding guidelines, transparency in every coding decision, and numerous operational and financial benefits.

Coding Accuracy: MediCodio’s AI Medical coding software ensures an accuracy rate of 95% or higher for all charts coded by our engine. This high level of accuracy ensures that healthcare providers receive appropriate reimbursement for services provided, reducing the risk of coding-related denials and associated revenue loss. Accurate coding also ensures correct reporting of clinical metrics such as severity of illness, risk of mortality, risk adjustment factor scores, and quality measures.

Configurability: MediCodio customizes a unique version of our engine for each customer to align with their internal guidelines and standard operating procedures (SOPs). This ensures consistency in coding output during the transition from manual to automated coding. Unlike other automated coding solutions that rely heavily on machine learning and may struggle to explain code selections, MediCodio’s AI medical coding engine uses rules-based ontologies, providing complete transparency into the coding rationale.

Maximizes Audit Readiness: MediCodio produces audit trails for every patient encounter coded by the engine. These trails include supporting documentation for each code assigned and links to specific guidelines referenced during code selection. These comprehensive and actionable resources help customers in the event of an audit, denial, or other compliance-related matters.

Continuous Compliance: When new coding guidelines are released, MediCodio’s team quickly assesses the updates and makes necessary technical adjustments to the engine’s components to reflect those changes. This ensures ongoing compliance with the latest guidelines, reducing the risk of denials, payer takebacks post-audit, and concerns related to fraud, waste, or abuse of coding practices.

Accelerates Payment Cycles: MediCodio’s AI medical coding engine codes patient encounters in seconds, compared to the minutes it takes for manual coding (e.g., an average of 32 minutes for discharged emergency department visits). By using MediCodio’s engine, customers can significantly reduce accounts receivable (A/R) time by an average of 5 days and resolve coding backlogs overnight.

Cost Reduction and Scalability with MediCodio

Cost Reduction: MediCodio’s AI medical coding engine can reduce coding-related costs for our customers by up to 35%. This cost-saving is achieved through several mechanisms:

• • Reduction in Full-Time Equivalent (FTE) Hours: The need for full-time medical coders is significantly reduced.

• • Lowered Risk of Denials and Revenue Loss: Accurate coding minimizes the risk of claim denials, preventing associated revenue loss.

• • Decreased Days in Accounts Receivable (A/R): Faster coding reduces the time accounts receivable remain outstanding, avoiding accumulated interest.

Enables Scalability: MediCodio’s AI medical coding engine can easily handle increases in patient volume, whether due to seasonal changes or the expansion of facilities, by simply increasing computing power. This offers a significant improvement over previous solutions, such as computer-assisted coding (CAC), which provide limited scalability as they still require human coders to validate each code before billing.

Read More: Best AI Medical Coding tools! How to choose the best AI medical coding company?

Learn how MediCodio’s innovative AI-driven medical coding engine can optimize your revenue cycle. Contact us for a detailed overview of benefits for healthcare facilities, RCM companies, and provider groups.

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FAQs

1. What is AI medical coding, and why is it important?
AI medical coding leverages artificial intelligence to automate the assignment of medical codes from clinical data. It boosts accuracy, reduces workload, and enhances healthcare documentation efficiency.

2. How does MediCodio’s AI medical coding engine work?
MediCodio uses advanced AI and natural language processing (NLP) to analyze patient records, extract key data, and suggest precise codes based on ICD, CPT, and HCPCS standards.

3. What sets MediCodio’s AI medical coding engine apart from others?
MediCodio stands out with its real-time suggestions, error-checking capabilities, seamless EHR integration, and customizable workflows tailored to healthcare organizations’ needs.

4. Can MediCodio’s engine adapt to different medical specialties?
Yes, MediCodio’s AI engine is designed to handle various specialties, ensuring accurate coding regardless of the complexity or specificity of the medical field.

5. How does AI medical coding improve compliance?
By analyzing records for compliance with regulations, MediCodio’s engine minimizes coding errors, flags inconsistencies, and helps organizations stay up to date with coding standards.