AI RCM

AI Clinical Documentation Integrity (CDI) products leverage artificial intelligence to review and evaluate clinical documentation in support of appropriate patient care, billing, and compliance with regulatory requirements.  These solutions can operate at the point of care, ensuring the documentation reflects the patient-clinician conversation and available clinical data, and supports the assigned medical codes. They can also operate post-encounter, between the medical coding and billing steps, to review the documentation against what has been coded and surface suggestions for revenue and quality opportunities. Many of these solutions include built-in functionality to suggest potential diagnoses that may have been missed based on information in the patient record. While similar in concept to risk adjustment solutions, AI CDI products are predominantly used in a fee-for-service context to ensure more accurate and complete billing and improve care quality.

AI Denials Management involves the identification, analysis, and resolution of denied claims to ensure that providers receive reimbursement for services rendered. Products in this category perform functions including: - Recognizing claims that have been denied by the payer. This can be due to various reasons such as coding errors, incomplete information, or issues with patient eligibility. - Investigating or understanding the reasons for denial. This often involves using AI to review claim details, patient records, and communications with the payer. - Making necessary corrections to the denied claims and resubmitting them for approval. This might involve updating coding, providing additional documentation, or correcting patient information. Given the need to interpret claims responses and automate them in many cases, there are strong connections between this category and products in Revenue Cycle Automation. Additionally, given that the goal of denial management is ultimately to reduce denials, many products in End-to-End Revenue Cycle Management also offer denials management workflows.

These are products that use AI to automate the patient billing process for healthcare providers, increasing their ability to responsibly collect patient payments. Some of the applications for these products include: - AI-Generated Patient Bills for minimizing errors and better explanations to patients - Billing Inquiry Chatbots available for handling routine billing questions - Optimized Payments for improved scheduling of payment reminders and timetables, as well as finding the right channels and messaging for patients - Ability to integrate relevant data and predict ability to pay in order to provide discounts, payment schedules, and other financial support for patients

These are prior authorization platforms for health plans and other entities that do utilization management. They use AI to automate UM decisions and improve efficiency of UM nurses / clinicians. Functions usually include: - Ingestion of clinical policies and translation into decision trees - Automatic population of prior auth decisions for approval - Automatic approval of auths that meet certain criteria - Documentation of decision reasons, i.e. traceable decisions Prior authorization vendors vary meaningfully in their service coverage, with some specialized for pharmacy and others focused on certain types of medical services.

These are tools that use AI to streamline the provider end of the prior authorization process. Functions usually include: - Identification of prior authorization requirements and processes - Automatic population of prior authorization forms - Submission of prior authorization requests - Reporting and checks on prior authorization status - Support with appealing prior auth denials Prior authorization vendors vary meaningfully in their service coverage, with some specialized for pharmacy and others focused on certain types of medical services.

Autonomous Coding refers to AI-driven systems that independently convert clinical documentation into billing codes with minimal human involvement. These platforms go beyond traditional computer-assisted coding (CAC) by automating the full coding process—scanning clinical notes, identifying relevant diagnoses and procedures, and assigning billing codes with high accuracy and speed. Leveraging technologies like natural language processing (NLP), deep learning, and large language models (LLMs), these systems apply contextual understanding to unstructured clinical text, continually learning from audits and evolving coding guidelines. Human coders are still involved in edge cases, triggered by low confidence scores or ambiguous documentation, but for the majority of encounters, autonomous systems operate without manual oversight. Architecturally, autonomous coding solutions range from end-to-end deep learning models to hybrid systems that combine machine learning with rules-based engines. Their benefits include faster turnaround times, consistent and accurate code generation, scalability during volume surges, and reduced labor costs. Adoption has been strongest in specialties with predictable documentation patterns—like radiology and pathology—but the technology is expanding into more complex areas, including emergency and inpatient professional coding. However, full automation of inpatient facility coding remains aspirational. Implementation challenges include EHR integration, maintaining regulatory compliance, and ensuring transparency in coding decisions. When evaluating vendors, provider organizations should assess specialty fit, automation rates, technical design, throughput, and audit tools.

Revenue Cycle Automation products use AI and elements of RPA to automate key workflows in revenue cycle management, including claims processing, prior authorization, patient payment collection, eligibility verification, and denials management. These platforms generally integrate with EHRs, practice management systems, and other RCM tools, and provide agents that can accomplish key workflows. Core capabilities include: - Integration with existing systems through APIs or advanced web browsing capabilities - Ability to define key workflows for automation, with well-defined inputs and outputs - Tracking and analytics to understand effectiveness of workflow automations and identify key issues While there are many RPA platforms, our focus with this category is on vendors who specialize in healthcare and RCM, or who have the scale to have deep expertise on healthcare workflows.