Navigating the Evolution of Medical Coding
Autonomous Medical Coding (AMC) vs. Computer-Assisted Coding (CAC)
What is Computer-Assisted Coding?
Computer-Assisted Coding (CAC) is a software system that assists coders in the process of assigning appropriate diagnostic and procedural codes to patient records. CAC helps suggest potential codes based on the provided medical information such as physician notes, electronic health records (EHRs), and other clinical documents. Although it is a popular solution within the medical coding industry, Computer-Assisted Coding is typically rule-based and does not adapt to unstructured clinical documentation, ultimately requiring 100% human review and intervention. These manual interventions slow down cost-to-collect performance and negatively impact revenue cycle metrics.
Unfortunately, the variability in clinical documentation coupled with natural language processing (NLP) presents high levels of inaccuracy that result in time-consuming rework, denials, and misrepresentation of patient acuity.
What is Autonomous Medical Coding (AMC) and How is it Different from CAC?
Autonomous Medical Coding (AMC) is an automated process of assigning diagnostic and procedural codes to patient records using Artificial Intelligence (AI) and Machine Learning (ML) technologies, without the need for significant human intervention. Continuously self-learning algorithms analyze clinical documentation to generate accurate medical codes for billing and data management.
The key difference between Computer-Assisted Coding and Autonomous Medical Coding lies in the degree of automation and human intervention. While CAC coding acts as a supplement or tool for human coders, AMC aims to automate the majority of the coding process, greatly reducing the need for human intervention in routine coding tasks.
aiH.Automate™: A Helpful Co-Worker
aiHealth’s autonomous medical coding platform, aiH.Automate™, is supported by innovative AI-ML technologies that are capable of automating up to 90%+ of multi-specialty CPT® coding tasks. Acting as a helpful co-worker, aiH.Automate™ takes on the burden of mundane workqueues, substantially reducing administrative workload, and increasing coding throughput by 50%. In addition, the platform actively addresses labor shortages by automating revenue cycle processes and effectively reducing charge lag, offering tangible operational improvements in healthcare facilities.
Unlike other platforms utilizing autonomous medical coding, aiH.Automate™ goes beyond just diagnosis codes by automatically coding everything from ICD-10 and CPT® codes to Modifiers, Units, and Assists. Successfully and compliantly coded patient encounters are directly routed to billing workflows while complex exceptions are sent to human coders’ workqueues for further review. QA sample rates can be fully customized depending on the organization, provider, and specialty. In addition, aiHealth provides a personalized robust analysis dashboard that offers complete audit trailing, providing detailed insight into the auto-coding process. Stakeholders can efficiently and transparently track the system’s performance every step of the way.
Learn more about how aiH.Automate™ can be a helpful co-worker to you: