OpenEvidence Launches AI-Powered Medical Coding Feature to Automate Clinical Billing
OpenEvidence Launches AI-Powered Medical Coding Feature to Automate Clinical Billing
OpenEvidence has introduced a new artificial intelligence-powered medical coding feature called Coding Intelligence, integrated into its clinical AI assistant platform. The new feature automatically generates medical billing codes at the end of a doctor-patient visit, helping physicians reduce administrative workload and improve billing accuracy.
The Coding Intelligence feature provides automatic Current Procedural Terminology (CPT) code suggestions, ICD-10 diagnosis codes, and Evaluation and Management (E/M) level recommendations. It also generates the medical decision-making rationale directly within the clinical note, ensuring proper documentation for billing and compliance.
Automating a Complex Billing Process
Medical billing is a complex and time-consuming process due to the large number of billing codes and the different ways a single patient visit can be coded. Many healthcare providers still perform coding manually or outsource it to third-party agencies, which can be expensive and time-consuming.
OpenEvidence’s AI coding tool analyzes the full transcript of the patient visit and the final clinical documentation to understand what procedures were performed, what diagnoses were made, and what treatments or tests were ordered. Based on this analysis, the system automatically generates a complete and accurate set of billing codes.
According to OpenEvidence executives, the system can identify both common and uncommon procedure codes that may otherwise be missed, especially in complex medical cases.
Built for Accuracy and Compliance
The Coding Intelligence system also includes features designed to improve billing accuracy and reduce claim denials. The platform automatically sequences CPT codes to maximize reimbursement based on Medicare’s Multiple Procedure Payment Reduction policy, where additional procedures are reimbursed at a reduced rate. By sequencing codes correctly, healthcare providers can improve reimbursement outcomes.
The system also applies CMS Correct Coding Initiative (CCI) rules to validate code combinations before submitting claims. Incorrect code combinations are a common reason for claim denials and compliance issues, so automatic validation helps reduce billing errors.
In addition, the system displays Relative Value Unit (RVU) values alongside CPT code suggestions, helping healthcare providers understand reimbursement value before submitting claims.
Expanding Clinical AI Capabilities
OpenEvidence, originally known for its AI-powered medical search engine, has been expanding into broader clinical workflows. The company previously launched its Visits feature, which transcribes doctor-patient visits, and recently introduced an AI-integrated doctor dialer feature.
The company reports that its platform supports millions of clinical consultations and is used by physicians across thousands of hospitals and medical centers in the United States. With the addition of AI-powered coding, OpenEvidence is positioning itself as a comprehensive clinical AI workflow platform.
Industry Impact
AI-powered medical coding tools like Coding Intelligence could significantly reduce the administrative burden on healthcare providers, allowing doctors to spend more time on patient care instead of paperwork. Accurate coding also helps healthcare providers avoid claim denials and improve revenue cycle management.
As healthcare organizations continue to adopt AI technologies, automated medical coding is expected to become an important part of digital healthcare systems, improving efficiency, accuracy, and financial performance for healthcare providers.
