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AI and Algorithms: An Effective Approach to Medical Claims Processing

Authored by Corliss Collins, BSHIM, RHIT, CRCR, CSM, CCA, CBCS, CPDC   

Founder. Principal and Managing Consultant   


This is Part 7 in a series of articles providing a general overview of Artificial Intelligence (AI) impacting the healthcare industry.  This information is an overview of very basic suggestions on Standard Operating Procedures (SOP), Policies and Best Practices for smaller hospitals and provider organizations. This information is not designed to be all-inclusive. and is not intended as consulting or legal advice.


Introduction

The Health Leaders Media Report, Final Denial Rate Increase, states that denials increased by 51% in 2021 and 2023 despite significant investments in Artificial Intelligence (AI) Automation and Revenue Cycle Management (RCM) Operations utilizing AI-Powered Medical Coding and Medical Claims Processing Software. This pressing issue demands our attention!


About the TechnologyOptical Character Recognition (OCR) and Natural Language Processing (NLP) are powered by AI Machine Learning (ML) and deep learning large language models (LLM). These technologies have become a core function in RCM Operations and have also been adopted by the Health Insurance, Health System, and Provider communities across the United States. Nonetheless, claim denials continue to show an alarming increase year over year. 

So, why aren't the numbers of healthcare claim denials and rejections declining with all the automation and technology advancements?


Are Automated Coding Models Powered by AI Not Accurate Enough for Medical Coding?

This article delves into this complex and sometimes very confusing topic, briefly recapping Part 6, AI and Algorithms: The Other Side of Medical Claims Processing, and then providing a general synopsis in Part 7AI and Algorithms: An Effective Approach to Medical Claims Processing. 


Advancing RCM Operations

Every year, more than five billion medical claims are processed by Payers in the United States for reimbursement, according to the Centers for Medicare & Medicaid Service, CMS.gov.  Many of these claims are processed using the Healthcare Common Procedure Coding System (HCPCS) and the Current Procedural Terminology (CPT®) coding systems. These two coding systems are the backbone of our billing process. It is essential to comprehend the underlying causes of AI, algorithms, and Rule-Based Automation in order to reduce risks:


There are Three Primary Claim Edit Types to Pay Attention to:

  1. Technical Edits are triggered by missing or incomplete claim information

  2. Clinical Edits are directly associated with care or services rendered

  3. Underpayments Claim amounts aren't being paid as the Contract Agrees to pay


Artificial Intelligence (AI) in the Medical Claims Process

AI leverages cutting-edge technology, including robotic process automation and AI machine learning, to improve the different medical claims adjudication activities that enable accurate billing for provided healthcare services.


These AI systems also use LLMs, which are machine learning models with the capacity to communicate in normal language with claim managers to evaluate substantial amounts of data. Complex patient data management, medical record administration, processing medical claims, collecting payments, and financial reporting are among the duties covered by CMS AI Resources.

There are hundreds of HIPAA-Compliant Medical Coding Software Applications on the market (see CMS for more on HIPAA-Compliant Code Sets.) Using automation more and manual intervention less is supposed to lead to the reduction of errors and inefficiencies. If this is the case, why do claim rejection and denial rates seem to not be declining annually?


On another note, unautomated accounts are processed differently. Claims are routed to manual review work queues (WQs) to be analyzed, corrected and billed. 



About the Author

Corliss Collins, BSHIM, RHIT, CRCR, CSM, CCA, CBCS, CPDC


Corliss is the Founder. Principal and Managing Consultant of P3 Quality LLC. She serves as a subject matter expert and volunteer on the Education Committee for the American Institute of Healthcare Compliance.



Copyright © 2024 American Institute of Healthcare Compliance All Rights Reserved 



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