The journey to coding automation is unique for each healthcare organization, and every organization is at a different stage
Despite its cyclical portrayal, the healthcare revenue cycle is constantly evolving based on economic conditions, government regulations, payer policies, and patient expectations. This continuous evolution is especially evident in medical coding.
And a 2023 AHIMA report found that
48%
of respondents experienced decreased reimbursement and slower claims processing due to understaffing.
Meanwhile, a survey by Harmony Healthcare found that
32%
of hospital executives cited coding as their top concern regarding denials.
Despite these challenges, just
45%
of respondents to a 2023 AHIMA survey reported the adoption of artificial intelligent (AI) and machine learning (ML) in their departments.
and only
11%
of respondents to a KLAS Research survey said their organizations had embraced coding automation.
However, among those KLAS Research survey respondents,
40%
said they plan to invest in autonomous coding over the next 12 to 24 months.
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The journey to coding automation is unique for each healthcare organization, and every organization is at a different stage
The size of your organization, the complexity of your current systems, your financial resources, and many other factors can play a role in your progress. Furthermore, your specific needs and strategic priorities can influence the pace and approach you take to automate.
While many hospitals and health systems are just beginning to explore coding automation opportunities, others are already integrating advanced AI-powered solutions into their coding processes.
| Rule-Based CAC Systems | NLP-Based CAC Systems | |
|---|---|---|
 | Utilizes predefined rules, templates, and logic to interpret and code medical documentation. | Uses advanced algorithms to understand and interpret language, identifying relevant medical terms and context within documentation. |
 | Reliable only in stable, well-defined scenarios where the rules are clear and comprehensive. | Can handle a wider variety of languages and contexts through ML to achieve high accuracy. |
 | Requires significant manual effort to update rules and templates for new codes, guidelines, or practices. | Easier to adapt to new information and changes in medical terminology or coding guidelines. |
 | Limited in handling complex language and context, often struggling with ambiguous or nuanced medical terminology. | More adept at managing complex, unstructured data and ambiguous terms, offering better understanding of context and intent. |
Many organizations start their coding automation journey with a computer-assisted coding (CAC) platform. However, not all CAC systems are created equal.
There are two primary types of CACs: those that utilize rule-based logic and those that employ natural language processing (NLP), an artificial intelligence technology that interprets, analyzes, and responds to text.
While each type can offer improvements in productivity and efficiency, rule-based systems have inherent limitations that hinder their effectiveness.
Another factor to consider when exploring coding automation systems is the platform’s ability to suggest codes for professional coding services.
While most coding automation software supports facility coding, only a few are properly equipped to handle professional-fee coding. At AGS Health, we refer to these as computer-assisted professional coding (CAPC) platforms.
CAPC systems ensure precise coding across all professional specialties, encompassing ICD-10 CM, CPT, HCPCS, modifiers, and professional E&M levels. In some cases, these systems can also support the coding of Merit-based Incentive Payment System (MIPS) Quality Incentives, consolidating your traditional coding and MIPS coding processes into one streamlined and efficient workflow.
Another factor to consider when exploring coding automation systems is the platform’s ability to suggest codes for professional coding services.
While most coding automation software supports facility coding, only a few are properly equipped to handle professional-fee coding. At AGS Health, we refer to these as computer-assisted professional coding (CAPC) platforms.
CAPC systems ensure precise coding across all professional specialties, encompassing ICD-10 CM, CPT, HCPCS, modifiers, and professional E&M levels. In some cases, these systems can also support the coding of Merit-based Incentive Payment System (MIPS) Quality Incentives, consolidating your traditional coding and MIPS coding processes into one streamlined and efficient workflow.
Coding automation provides greater flexibility and scalability to coding operations by enhancing the accuracy, efficiency, and productivity of health information (HI) professionals. This technology provides a cost-effective approach to addressing labor shortages while mitigating coding-related denials, enhancing regulatory compliance, and streamlining billing processes.
Even with coding automation, your coding accuracy will depend on the clarity and completeness of your clinical documentation. As part of your coding automation strategy, it's essential that you evaluate medical coding and clinical documentation improvement (CDI) together.
To translate a patient's condition into precise codes, CDI requires a comprehensive, multidisciplinary, enterprise-wide effort. Intelligent automation is key.
On the road to coding automation, CDI software is a logical next step for many organizations. Using NLP and ML technologies, it analyzes digital patient charts automatically, identifies missing and incorrect diagnoses in clinical documentation, and suggests potential queries based on clinical data.
Even with coding automation, your coding accuracy will depend on the clarity and completeness of your clinical documentation. As part of your coding automation strategy, it's essential that you evaluate medical coding and clinical documentation improvement (CDI) together.
To translate a patient's condition into precise codes, CDI requires a comprehensive, multidisciplinary, enterprise-wide effort. Intelligent automation is key.
On the road to coding automation, CDI software is a logical next step for many organizations. Using NLP and ML technologies, it analyzes digital patient charts automatically, identifies missing and incorrect diagnoses in clinical documentation, and suggests potential queries based on clinical data.
Incorporating CDI software with coding automation systems enables you to gain a comprehensive view of unstructured data, addressing issues such as length of stay (LOS), mortality risk (ROM), severity of illness (SOI), compliance, and other strategic priorities. By structuring this data, you can improve clinical analysis, code accuracy, compliance, and revenue.
With increased regulatory scrutiny and the continuously shifting landscape of rules and regulations, code auditing has become another key factor for coding automation.
Despite the abundance of code auditing technologies available today, interoperability across CAC, CAPC, and CDI remains a shortcoming for most auditing platforms. A fully integrated auditing solution led by advanced AI can help you enhance compliance and protect your hard-earned revenue.
Advanced capabilities, such as audit case selections, integrated encoders, automated audit reports, and a centralized feedback center, can help transform the code auditing process from a retrospective, stand-alone process into an automated, real-time, and collaborative revenue cycle compliance solution.
With increased regulatory scrutiny and the continuously shifting landscape of rules and regulations, code auditing has become another key factor for coding automation.
Despite the abundance of code auditing technologies available today, interoperability across CAC, CAPC, and CDI remains a shortcoming for most auditing platforms. A fully integrated auditing solution led by advanced AI can help you enhance compliance and protect your hard-earned revenue.
Advanced capabilities, such as audit case selections, integrated encoders, automated audit reports, and a centralized feedback center, can help transform the code auditing process from a retrospective, stand-alone process into an automated, real-time, and collaborative revenue cycle compliance solution.
A combination of advanced search and rules engines allows users to create meaningful audit populations based on various parameters, such as diagnosis codes, CPT E&M/HCPCS codes, principal/secondary diagnoses, procedures, modifiers, and more. Users can easily create pre-bill and retrospective audits using an interactive audit worklist interface.
This feature incorporates a fully integrated, proprietary encoder that includes codebook, groupers and pricers, and compliance edits, such as Medicare Code Editor (MCE), Medicare National Correct Coding Initiative (NCCI), and Local Coverage Determinations (LCDs)/National Coverage Determinations (NCDs). The module also integrates and interfaces with other leading encoders.
Automated audit reports are generated for audited cases with a code-by-code comparison of the coder and auditor versions. The comparison includes detailed changes for POA, code ranks, CCs/MCCs, discharge dispositions, DRG, weight, SOI, and ROM. Missed query opportunities and physician documentation issues are also quantified for all audited cases.
The feedback center displays each audited case to HI professionals. They get a detailed comparison of the original and auditor versions. A commenting feature allows HI professionals to respond in real time to auditor feedback and ensures a complete end-to-end communication trail.
Among the most recent developments in coding automation is the emergence of autonomous coding tools. This emerging technology uses advanced AI tools, including ML, NLP, clinical language understanding (CLU), computational linguistics, knowledge graphs, and large language models (LLMs), to make coding processes more efficient and accurate by analyzing large amounts of medical data and assigning codes without human input.
While current autonomous coding platforms are effective based on simpler, high-volume medical visits, they are not yet capable of fully automating 100% of an organization’s coding workflows based on medical complexity.
Depending on the complexity and specialty of the coding tasks, you can expect approximately 40-50% of codes to be generated autonomously at the outset. Environments with repetitive data and lower variability, such as emergency departments and radiology, are particularly well-suited for autonomous coding.
Despite performance variations, this level of automation can offer significant benefits to understaffed organizations. However, it's crucial for HIM and RCM leaders to prepare for any potential issues that may arise with incomplete or incorrect charts.
With human input and feedback, autonomous technologies can grow and evolve. As autonomous coding technologies analyze how human coders resolve fallout charts, they'll start identifying trends and coming up with new logic to reach autonomous ranges of 70-80% in the future. With enough time and data, autonomous coding can significantly improve your speed and accuracy.
Unlike most other autonomous coding solutions, AGS Autonomous Coding offers true coding autonomy by combining advanced artificial intelligence with award-winning coding services into one solution. In this way, hospitals and health systems can fix staff shortages, coding-denial issues, compliance problems, and more right away while AI models get trained to be more efficient. Additionally, this human oversight offers an extra degree of confidence as you move to more advanced coding automation.
With human input and feedback, autonomous technologies can grow and evolve. As autonomous coding technologies analyze how human coders resolve fallout charts, they'll start identifying trends and coming up with new logic to reach autonomous ranges of 70-80% in the future. With enough time and data, autonomous coding can significantly improve your speed and accuracy.
Unlike most other autonomous coding solutions, AGS Autonomous Coding offers true coding autonomy by combining advanced artificial intelligence with award-winning coding services into one solution. In this way, hospitals and health systems can fix staff shortages, coding-denial issues, compliance problems, and more right away while AI models get trained to be more efficient. Additionally, this human oversight offers an extra degree of confidence as you move to more advanced coding automation.
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It's natural for HI professionals to feel concerned about the impact of coding automation. After all, these features were designed to transform the way coding processes are managed. But embracing these tools can help elevate HI professionals' roles.
Coding automation not only eliminates tedious and repetitive tasks but also allows HI professionals to transition into higher-level responsibilities, such as auditing, compliance, or specialized coding. It's a great opportunity to learn new skills and stay on top of changes. Additional benefits include:
It's natural for HI professionals to feel concerned about the impact of coding automation. After all, these features were designed to transform the way coding processes are managed. But embracing these tools can help elevate HI professionals' roles.
Coding automation not only eliminates tedious and repetitive tasks but also allows HI professionals to transition into higher-level responsibilities, such as auditing, compliance, or specialized coding. It's a great opportunity to learn new skills and stay on top of changes. Additional benefits include:
HI professionals can avoid tedious tasks and complete their work more quickly, preventing stress and anxiety caused by large backlogs and extended work hours.
Automating routine tasks allows HI professionals to focus on more complex cases, which challenges them to think more critically when solving problems.
By taking on more responsibilities, they can better demonstrate their skills, which opens the door to new opportunities for career growth and higher salaries.
Coding automation tools enable team members to collaborate more effectively and act as learning resources to stay current with coding changes and best practices.
Coding automation is a complex journey that requires substantial planning, dedication, and perseverance. As such, healthcare leaders must understand that this journey isn’t just about adopting new technology—it’s about making thoughtful, strategic decisions that impact every facet of their operations. It demands careful consideration of where, when, and how to apply these tools.
To navigate this process effectively, healthcare organizations need expert partners who not only understand the technology but also have deep experience in the healthcare operations these technologies support. Revenue cycle management is a delicate web of interconnected processes, and even slight changes can have significant consequences. Therefore, choosing a partner who can identify the most impactful automation opportunities and provide comprehensive technology and service solutions is essential for success.
At AGS Health, we believe in the promise of AI with a human touch. We work closely with customers to engineer solutions that meet their unique needs and goals. Our highly acclaimed technologies and deep expertise in coding services enable us to support healthcare organizations at every stage of automation maturity.
Whether you are starting your coding automation journey or seeking advanced capabilities like autonomous coding, AGS Health is here to help!
Contact us today to schedule a free consultation with one of our coding automation experts. Discover how our unique blend of intelligent automation and award-winning services can help streamline your organization’s mid-cycle operations and improve your long-term financial health.
