Evaluation and Management (E&M) Coding: How AI Augments the Entire Workflow

Evaluation and Management (E&M) Coding: How AI Augments the Entire Workflow

Since their introduction in 1995, E/M codes served as the only reliable source of information for doctor-patient interactions. These codes are essential to simplifying billing because they succinctly encode the interaction's information in numeric codes. Therefore, accurate and compliant E&M coding is essential for physicians and clinicians.

However, the E/M coding procedure has encountered conflicting responses from the medical community over the years. The value of the process cannot be disputed, but neither can the mounting burden it places on doctors.

A growing number of metrics are being applied to physicians to improve quality, satisfaction, and effectiveness. Electronic health records (EHRs) and the burden of documentation create an excess of E/M documentation

requirements, leading to errors, "note bloat," and physicians taking time away from caring for patients.

The primary goal of the revised CPT E/M coding guidelines, which took effect on January 1, 2021, was to ease the administrative burden on doctors.

But even before the new AMA recommendations took effect, the healthcare sector found ways to ease those burdens. The use of AI-powered computerassisted coding (CAC) is one such method. A Markets and Markets report estimates the value of AI in medical coding automation will reach $14 billion by 2026, providing a clear illustration of the value and demand for this technology.

The Need for AI-powered CAC in E/M Coding Complex revenue cycle management is a problem that many hospitals nationwide must deal with. The revenue for outpatient visits directly results from how accurately E/M coding is done. Healthcare organizations must adopt more efficient coding tools because legacy infrastructure can't boost revenue through enhanced E/M documentation.

Introducing Computer-Assisted Coding (CAC) The term computer-assisted coding or CAC refers to a technology that combines various aspects of NLP and AI. Unstructured medical notes can be examined and analyzed using CAC software that is NLP-powered. The software can extract clinical facts and assign proper E/M codes using specialized linguistic algorithms. Therefore, physicians are no longer required to perform the laborious task of locating, extracting, and recording data into the system from the documents.

Voice-based NLP enhances the process even more. Dictation being one of the primary sources of unstructured medical data, CAC software can use speech recognition provided by voice-based NLP to extrapolate the appropriate E/M codes. This dramatically minimizes the amount of coding that physicians must do while also improving process accuracy. This makes it possible to align payer reporting systems and E/M coding standards more closely, greatly enhancing the billing process and lowering denials and audit discrepancies.

Additionally, CAC gives physicians and the healthcare system real-time feedback about the accuracy of E/M codes used to evaluate patients during outpatient visits.

The AGS Health Advantage The advantages of computer-assisted coding are clear, as are its requirements.

But even so, using CAC software alone does not produce the desired results.

Consider the Richmond University Medical Center (RUMC) in Staten Island, New York, which encountered a widespread problem among its hospitals.

RUMC’s current encoder technology was unable to offer sufficient workflow capabilities. RUMC required a thorough CAC framework to ensure regulatory and payer compliance, in addition to increasing productivity and accuracy of the coding process.

When RUMC and AGS collaborated to achieve this goal, notable outcomes were achieved. Complex denials dropped by 13%, while coder productivity increased by 33%.

AGS Health's CAC solution automates the assignment of E/M codes and suggests case history codes by fusing the abilities of natural language processing (NLP) and machine learning (ML) with the E/M logic algorithm.

The outpatient evaluation's examination types and complexity levels can be assigned using more advanced automation techniques. Additionally, the included E/M calculator aids coders in selecting the appropriate E/M code level.

AGS partnership entails more than just having technology at your disposal to streamline the E/M coding process. We are with you every step of the way.

Within weeks, we can implement an end-to-end process you fully own.

To learn more about AGS’s AI-based mid-revenue cycle management solutions, check out the AGS AI Platform.

Source of content: https://www.agshealth.com/blog/evaluation-and-management-em-coding-how-ai-augments-the-entire-workflow/