The healthcare industry is always on the move, and nowhere is that more evident than in revenue cycle management (RCM). As we navigate towards 2025 and beyond, healthcare leaders and RCM teams are diligently adapting their strategies to maintain financial stability, accelerate revenue, reduce denials, and deliver quality patient care. Staying on top of the latest trends in RCM, from innovative advancements in AI to shifts in patient expectations, is key to staying competitive.
One of the most talked-about advancements is the rise of AI and automation in healthcare, especially within RCM. About 80% of healthcare executives are already increasing spending on IT and software due to the rise of AI technologies. These powerful tools help healthcare providers improve efficiency, optimize workflows, and minimize errors in crucial RCM areas like patient registration, eligibility verification, claims processing, denials management, and payment posting.
However, the world of AI and automation comes with its own set of buzzwords and bold claims. When it comes to something as critical as autonomous coding, it’s essential to approach vendor claims with a healthy dose of skepticism and a clear understanding of what a truly robust solution entails. This isn't just about being smart; it's about safeguarding your organization's financial health, compliance, and even patient care.
Let’s dive into what you need to know and the critical questions you must ask to choose an autonomous coding solution that genuinely delivers value.
Why Skepticism is Your Best Asset in Vendor Selection
In the fast-paced world of healthcare technology, it's easy to get swept up in the excitement of new solutions. Yet, when a vendor promises "100% autonomous. There's no humans involved. It's only AI," you should immediately raise an eyebrow and ask for proof. Unrealistic promises can lead to significant headaches down the road, and it’s your responsibility as a buyer to perform thorough due diligence. You "need to be skeptical" and "be an advocate, really look into understand" what you're getting into.
Physicians, in particular, often harbor a healthy skepticism towards new technologies, and for good reason. They’ve seen many "technical runs that didn't work" and been forced to use "algorithms that were supposed to identify by substances earlier" but ultimately "don't" deliver. When an algorithm dictates patient treatment without transparency, it creates discomfort because at the end of the day, physicians are responsible for the patient.
This skepticism extends to coding as well. As Dr. Greg Hobbs, an emergency physician and co-founder of Milagro, highlights: "Most people don't understand that physicians are legally responsible for how their cases were coded. This is why a lot of physicians continue to do their own coding. We're legally responsible for the coding of something. If you're trusting an algorithm, in a algorithm, to do it for you, that's a whole nother level of trust that you're asking for."
On the revenue cycle side, there's also significant "liability" due to regulations like the False Claims Act, making compliance absolutely crucial. So, when evaluating solutions, ask yourself: where is the human involvement? What auditing is in place? What steps are they taking to ensure compliance and protect your organization?
Defining the Solution: Autonomous vs. Automated
Before you can ask the right questions, you need to understand the terminology. The terms "automated" and "autonomous" are often used interchangeably, but they represent very different levels of AI capability.
What is "Automated Coding"? This refers to software that "assists the coder in doing their job more efficiently, more accurately," and is already widely adopted in the industry. Think of it as a sophisticated co-pilot, enhancing human performance.
What is "Autonomous Coding"? This is a more advanced concept, referring to software that has "the ability to code cases with no coder involvement," passing them directly for billing without any human review. This is where the trust, transparency, and accuracy demands become incredibly high.
Magical’s Agentic AI, for instance, aims for fully autonomous, fully agentic AI, transforming repetitive workflows into scalable automations that can run without human involvement. Unlike traditional Robotic Process Automation (RPA) tools that can be difficult to set up, expensive to maintain, and prone to breaking when encountering anything outside their predefined rules, Agentic AI adapts to nuance. It makes decisions "just like a human" using reasoning models, real-time data, and goal-based execution, making automations more reliable. This type of AI understands context, adapts to changing situations, and makes judgments based on available data, making it suitable for complex, unstructured tasks.
Performance and Accuracy Metrics: The Non-Negotiables
When considering an autonomous coding solution, performance and accuracy are paramount. Don't settle for vague assurances; demand concrete metrics and proof.
What Percentage of Cases Can Be Covered? An effective autonomous solution "need[s] to be able to do about 85% of all the cases". It's not enough for it to handle only the "easy ones" that aren't problematic anyway. You need a solution that can tackle the "hard cases, the common-clutch cases". The remaining 15% might include rare cases or those with documentation issues that still require human intervention.
What is the Proven Accuracy Rate? Demand "95% accurate". Anything less introduces significant risk and potential for denials or compliance issues.
How is Accuracy Proven? Insist on proof "in a head-to-head" comparison, using your own data and your own people to validate the results.
What is the Role of AI vs. Other Technologies? This is crucial. As Dr. Hobbs notes, "AI by itself cannot get you to 95%" accuracy. So, if a vendor promises high accuracy, "ask what else are you using" to achieve this level. True high accuracy often comes from combining AI with other technologies and approaches, creating a hybrid solution that knows when human oversight is still needed. Magical's Agentic AI, for example, is designed for reliability with features like smart data transformation, intelligent PDF processing, AI-powered resilience, daily automated testing, automation logs, and adaptive intelligence.
Transparency, Compliance, and Trust
For a system to be truly trustworthy, especially in a heavily regulated industry like healthcare, it "has to be fully transparent". This transparency is essential for auditing and compliance.
Auditing and Compliance: You need to know "what is being done to CYA on our end as well?" and "what are they doing on their end for auditing?". This proactive approach helps avoid costly penalties and maintains financial health.
Upcoding or Undercoding Issues: Physicians often worry about "systematic upcoding," which can lead to legal issues. Conversely, many physicians feel their cases are "consistently undercoded". A robust solution should be built to remove undercoding while ensuring accurate, compliant coding.
Human Involvement: If your belief is that "humans need to be involved in this," then "ask where in the process is a human about?". A smart solution can incorporate rules that direct complex or high-value cases for human review, such as "all cases above this dollar amount go to review, all cases for a new doctor for the first month," or any other criteria you define. This blend of automation and human expertise offers the best of both worlds.
Magical’s approach to Agentic AI allows for fully autonomous operations while still providing "comprehensive logs, recordings, and dashboards" for full monitoring of each automation run, offering the transparency needed for auditing and compliance. Furthermore, Magical is SOC2 & HIPAA Compliant, addressing crucial security and data handling concerns.
Integration and Workflow Fit
A cutting-edge solution is only valuable if it can seamlessly integrate into your existing workflows without causing major disruptions. The reality of IT bandwidth in healthcare organizations often means that complex, time-consuming integrations are non-starters.
Integration Timeline: Ask, "How long is this going to take?". If a solution requires "three months of IT time, you're not going to get live" because IT teams are already stretched thin.
Required IT Resources: Be specific: "What specific people do you need from us to do it and how much is there time where you going to need?". Ideally, the vendor should "do 90% of the work," minimizing the burden on your internal team.
Fitting Existing Workflows: Consider if the solution offers capabilities that enhance your current processes, such as "real time" coding for pre-authorization benefits. This is a game-changer. For example, if a patient is pre-authorized for a routine colonoscopy but a polyp is removed during the procedure, a new CPT code is required. Many payers will deny such cases if not reauthorized quickly. With true autonomous coding, the case can be coded "as soon as that operator note is done," allowing the CPT code to be identified and the information pushed to the pre-authorization team for reauthorization, avoiding denials. Some large teaching hospitals have seen a "95 percent" elimination of their pre-authorization denials using this capability.
Implementation Process: Inquire about running the solution "side by side for a while" in test mode before full implementation to build comfort and trust. Also, understand the "coder time" required for validation during this phase, ensuring your coders are involved in verifying accuracy.
Magical is designed to address these concerns, making it easy for anyone to set up RPA workflows "in a matter of minutes vs. months". Magical allows you to "start automating within days (not months) with one-click automations," and can even observe your team's workflows to "automatically flag automation opportunities". It's integrated with over 100,000 sites and used by 950,000 users across 100,000 companies.
Ready to see how fast and easy it is to automate your RCM workflows? Book a demo with Magical today to learn more about our Agentic AI solutions.
Data Security and Vendor Partnership
In a digital world where healthcare handles "mountains of sensitive patient data," cybersecurity is a top priority. A data breach can severely disrupt your revenue cycle, damage your reputation, and expose you to lawsuits and hefty fines.
Data Location and Handling: Ask directly: "Where does our data go? How long is it going to be there? What are you doing with it?". Ideally, your data should stay "inside your firewall". Security concerns are heightened following incidents like the "Jane catastrophe," making robust data handling policies non-negotiable. Magical emphasizes security, stating it "doesn't store keystrokes or store any patient data," minimizing the risk of data breaches.
Post-Implementation Support: A good vendor isn't just a technology provider; they're a partner. Ask for "specific examples" of support, such as being assigned a dedicated contact person, and what happens "when we find something different".
Adapting to Changing Rules: Healthcare regulations and coding rules "change all the time". In 2025, new developments around AI use in healthcare RCM are expected. Inquire: "How is the vendor going to know about local changes" and "communicate them"? Your partner should be proactive in keeping up with evolving compliance requirements.
Openness to Feedback: Look for companies that are "open to the back [feedback]" and "enhancements suggestions". This collaborative approach ensures the solution evolves with your needs and the industry's changes.
Conclusion: Partnering for Problem-Solving, Not Just Technology
Choosing an autonomous coding solution isn't merely about adopting new technology; it's about finding a partner dedicated to solving your problems and anticipating future challenges. The goal is to make tasks disappear, like magic.
The healthcare industry faces persistent staffing shortages and rising labor costs, which put a strain on health systems. Contract labor costs have spiked nearly 258% over the past four years, forcing many to seek external help from RCM providers. While there's a fear that automation might lead to job losses, the reality is that it addresses workforce gaps and allows your best coders to focus on complex, challenging cases where their unique skills are truly necessary. An autonomous solution can address the "30 percent of the workforce that is currently vacant," helping to backfill roles and manage staffing as people retire.
By embracing a proactive approach and investing in innovation, revenue cycle leaders can steer their organizations through challenging times and help patients understand their financial responsibility. Magical helps healthcare companies put their RCM workflows on autopilot with AI employees, transforming repetitive healthcare workflows into scalable automations that can run entirely on their own.
Ready to empower your team, reduce denials, and accelerate your revenue cycle? Install Magical for Chrome—it's free—or book a demo to explore how our Agentic AI can revolutionize your RCM processes.
