AI in Medical Billing and Coding

The use of AI continues to grow in healthcare, both in clinical settings and in healthcare operations. On the operations side, one of the biggest opportunities for AI in healthcare is medical billing.

AI tools—with thoughtful use and oversight—can help staff improve the efficiency, accuracy, and consistency of billing workflows. And these improvements add up quickly: by improving and simplifying internal operations—like automating repetitive administrative functions—U.S. healthcare providers could save an estimated $175 billion per year, roughly 18% of admin spending.

Read on to learn more about AI in medical billing, including practical use cases and the future of AI-assisted revenue cycle management (RCM).

What is AI in Medical Billing?

AI in medical billing is the use of artificial intelligence (AI) technologies, like machine learning and natural language processing (NLP), to automate and enhance the medical billing process.

AI technologies are designed to assist and empower staff to do their best work. For example, AI can alert staff to potential errors in claims before submission, enabling proactive resolution of issues that would otherwise cause delays or denials. With AI handling routine work and reviewing data in the background, staff can focus on more complex tasks like negotiating with payers and handling appeals.

Automation vs. AI in Medical Billing

While automation is a foundational piece of AI, the two concepts are not quite the same. Automation in medical billing is the use of technology that follows predefined instructions to perform rule-based, repetitive tasks without human intervention. AI takes this a few steps further: AI-based systems can analyze data, learn from it, adapt, and make predictions or decisions accordingly.

For instance, a system that automatically sends appointment reminders based on a preset schedule is an example of automation. A system that analyzes patient data, identifies those most likely to miss their appointment, sends personalized reminders based on those patterns, and adjusts over time based on new data is an example of AI.

Examples of AI Technologies in Medical Billing and Coding

Several AI technologies play a role in medical billing and coding:

• Natural Language Processing (NLP) allows systems to understand and interpret human language in patient records, clinical notes, and other medical documents. AI-based systems can use that language data to assist with coding, claims processing, and fraud detection tasks.
• Machine Learning (ML) algorithms are trained on large medical billing datasets to identify patterns, predict outcomes, and make decisions based on past data. ML can help predict patient payments and claim denials, identify coding errors, and automate patient eligibility verification.
• Large Language Models (LLM) use machine learning to process and generate text. LLMs are trained on massive amounts of text and code to provide relevant, contextual answers to real-world questions.
• Computer Vision extracts information from images and visual data, like insurance cards, medical bills, and even medical imaging.
• Deep Neural Networks are a subset of ML algorithms that handle particularly complex data. This type of deep analysis is useful for tasks like spotting potentially fraudulent claims among massive amounts of data.
• Optical Character Recognition (OCR) converts scanned images of text into machine-readable text. OCR helps digitize paper-based medical records, enabling providers to transition from paper-based to digital workflows.

AI has incredible potential to simplify administrative functions—something that could save U.S. healthcare providers an estimated $175 billion annually, roughly 18% of admin spending.

AI has several practical applications in medical billing, including:

• Patient billing support — AI assistants can help answer common questions about medical billing terminology, payment options, understanding a bill, and more.
• Clinical notes — AI systems can summarize clinical encounters, recommend medical codes based on services provided, and flag missing data that could cause problems during claims submissions.
• Personalized insights — AI-enhanced patient portals offer personalized reminders based on the patient’s billing history, upcoming appointments, payment due, and other factors.
• Automated coding — AI tools can use NLP and machine learning to analyze clinical documentation and automatically generate accurate CPT codes for simple, high-confidence-level charts. This reduces the risk of coding errors and frees up coders’ time for complex work.
• Data analysis — AI systems process massive amounts of clinical, financial, and claims data and generate actionable insights faster for healthcare operations leaders. This includes detecting potential fraud, which helps finance teams minimize revenue leakage and compliance issues.
• Pattern recognition — AI can recognize important patterns in claim denial data, finance KPIs (e.g. days in A/R), and other medical data sources faster and more accurately than other reporting tools.
• Administrative tasks — AI-powered platforms can streamline or entirely automate certain administrative processes: eligibility verification, appointment reminders, billing follow-ups, charge entry, payment processing, and more. In some cases, AI makes a multi-step process simpler, like determining if prior authorization is truly required before contacting the insurer.
• Compliance — AI systems can review claims submission rules and regulations, alert relevant teams to changes, and review new claims appropriately according to the revised rules.

How AI Can Help Medical Billing Staff

Healthcare providers allocate approximately 25% to 31% of their budget to administrative costs—with medical billing and coding accounting for about two-thirds of those costs. The right AI tools, combined with oversight from skilled and experienced staff, can make billing workflows more efficient, accurate, and consistent.

With AI, A/R and finance teams:

• Get better insights from operational data
• Find and address outliers and negative trends faster
• Audit billing and coding data in real-time
• Reduce the number of claims denied due to billing or coding errors
• Monitor billing and compliance KPIs
• Improve revenue capture and decrease operating costs

Here are specific ways AI can make a difference:

Streamline Billing Workflows

AI tools make billing workflows easier by reducing the need for manual data entry, collecting and verifying data from multiple sources, and parsing patient records and clinical notes. A streamlined billing process is more accurate and captures revenue faster for healthcare providers—a must, especially as reimbursement rates change and payer models evolve.

AI tools can help ensure patient information and medical documentation are complete and up-to-date, which is essential for accurate billing. This helps improve the speed and amount of patient payments, especially during the busiest times of the year.

Reduce Billing Errors

From the patient’s perspective, errors in medical bills are a major source of frustration. Four in five consumers believe their insurer could have a better process for resolving billing errors, and 70% of people who attempted to resolve a billing error spent more than two hours on the process.

From the provider’s perspective, billing errors are costly—not only in terms of uncaptured revenue, but also the staff time spent resolving errors and resubmitting claims.

With sophisticated AI tools, providers can train algorithms based on rejected claims to predict and flag potential issues. By spotting errors before claims submission, providers improve their clean claim rate and improve administrative efficiency.

Improve Staff Experience

AI in medical billing can improve the staff experience in several ways:

• Train staff on important financial processes and review completed work for coaching purposes
• Answer billing questions with AI-powered chatbots that provide 24/7 patient billing support
• Automate recurring and simple tasks associated with everyday patient billing, like insurance verification and high-confidence-level coding
• Improve the patient experience with AI-enhanced outreach and communication tools, which improves interactions between patients and finance teams

The right AI system allows staff to spend more time on complex claims, managing appeals, patient financial counseling, and more. It can also reduce the need for manual reviews of billing and coding work, without negatively affecting the quality of claims submissions.

Improve Revenue Capture

Of the $4 trillion in medical expenses each year, providers only capture a percentage of patient services rendered. AI tools can help reduce billing errors, find and address sources of revenue leakage, and improve patient payment follow-ups.

AI-powered billing software can predict payment patterns and flag potential issues quickly. By analyzing historical data, AI systems can empower finance teams to proactively address potential problems and improve patient collection rates. For example, AI can identify patients who are likely to have difficulty paying (perhaps due to a high-cost treatment scheduled after the annual deductible reset) and proactively offer them payment plan options.

The Future of AI in Medical Billing

What does the future hold for AI in medical billing? Look out for some key trends:

Finance and A/R teams focus on complex, strategic, supervisory work

With the adoption of AI for medical billing, staff can redirect their time from repeatable, straightforward tasks into more complicated tasks. For example, revenue teams can spend more time on:

• Feedback - human review and feedback is essential for the AI system to learn and improve
• Complex code assignments - complex coding situations require human analysis when they fall below the confidence threshold
• Issue resolution - with AI flagging outliers and negative trends, staff can focus on investigating and resolving high-priority issues
• Patient relationships - emotional intelligence, fostering trust, and navigating billing concerns with sensitivity requires a human touch

More focus on integrated systems

Going forward, look for healthcare organizations to bring disparate systems together. This includes electronic health records (EHR and EMR systems), practice management (PM) software, billing systems, and more. By combining these sources into a unified workflow—and combining records from multiple health providers—finance departments can optimize the revenue cycle for more effective operations.

Increasing sophistication, trust, and usage

The continued adoption of AI requires an increased level of trust and familiarity with the technology. It also requires AI tools to continue to advance and demonstrate reliability in medical contexts—including but not limited to billing.

As A/R and finance teams get more comfortable with AI-enhanced tools, usage will increase in new areas: staff training and coaching, process optimization, and so much more. But all healthcare providers must continue to focus on the responsible and ethical use of AI and how to implement responsible human oversight to ensure the best results.

How Collectly Improves Medical Billing

With AI tools like Collectly, A/R and finance teams spot problems faster, find data-informed solutions, and offer greater personalization for patients’ unique situations.

Collectly is an AI-powered patient billing platform that drives greater billing accuracy, higher revenue, and more predictable cash flow. Collectly streamlines the digital check-in process, improves point-of-service payments, and streamlines post-service follow-ups.

Collectly works with any EHR or PM, making it easy to add powerful billing to any healthcare tech stack. On average, Collectly users see a 75-300% increase in patient payments with a 95% patient satisfaction rate.

To learn more about how AI can improve medical billing, see how Pyramid Healthcare increased timely payments by 75% with Collectly.

AI for Benefits Verification and Prior Authorization

AI-enhanced tools help ensure patient information is accurate and up-to-date, including patient details, communication preferences, and payment methods. They can also assist with verifying insurance coverage, policy status, and coverage terms, helping to avoid costly delays and errors later in the RCM workflow.

Providers can use AI tools to streamline the patient registration process by notifying patients to update their insurance details when coverage is set to expire or change. AI-powered RCM tools can also verify deductible amounts, copays, and remaining balances—and make them available in staff views and patient portals—so all parties are well-informed.

AI systems can also improve the prior authorization process by reviewing patient data and medical records, cross-checking with payer requirements, and verifying prior authorization details with fewer phone calls and faxes.

AI for RCM Operations

In addition to supporting the RCM workflow, AI can assist with Finance and Accounts Receivable (A/R) team operations. Leaders can use AI to:

• Reduce billing errors
• Improve and personalize the patient billing experience
• Reduce the number of claims denied due to billing errors
• Audit billing data in real-time and monitor billing KPIs

Leaders can use AI technologies to assist with the initial learning curve and ongoing development of workers. For example, a 2023 report found that a generative AI-based conversational assistant in a call center improved productivity by 34% among novice and low-skilled workers (and 14% on average). The right AI systems can enable all workers to benefit from the knowledge and strategies used by top-performing employees.

Collectly for Revenue Cycle Management

AI helps healthcare organizations improve cash flow due to accurate, timely, and comprehensible billing and patient billing support. AI can enhance staff capabilities with data analysis and pattern recognition, giving medical billers, coders, and finance and A/R teams more time for complex and strategic work.

Collectly is AI-powered RCM software that drives greater billing accuracy, higher revenue, and more predictable cash flow. Collectly offers:

• Patient-friendly billing with digital statements, integrated payments, and online self-service payment plans
• Automated billing workflows and reconciliation to fit your RCM process
• HIPAA-compliant patient messaging with unlimited text, email, and automated calls
• Easy payment options, like autopay, batch autocharge, and card on file
• Secure and compliant infrastructure, including HIPAA, SOC2, and HITRUST i1 Certification

Collectly works with any EHR or PM, making it easy to add powerful billing to any healthcare tech stack. More than 3,000 healthcare facilities use Collectly for revenue cycle management—with an average 75-300% increase in patient payments.

See how CleanSlate achieved a 650% ROI with Collectly and increased patient revenue by over 250% overall.