Introduction

You know the drill: hiring, training, and managing staff in your RCM department is an endless cycle. Each new hire brings months of reviewing applications, conducting interviews, and onboarding, followed by additional months of training. Just as they start to get up to speed, they leave, and you're back to square one after having spent thousands on hiring. This turnover is a perpetual drain on your resources, time, and energy.

But what if there was a way to escape this cycle? You've heard of AI deploying a workforce that learns once and performs flawlessly, without the need for breaks, vacations, or retraining. AI doesn't quit, doesn't need retraining, and can immediately take over repetitive tasks, handle large volumes of data, and continuously improve its performance. This isn't just an upgrade; it's a strategic shift that can propel your RCM operations into a new era of efficiency and reliability.

By the end of this article, you'll understand why hiring AI agents is less burdensome than hiring new real-life employees. The future of RCM lies in embracing AI, not avoiding it. Let's explore how AI can be the game-changer your department needs.

Understanding the Fear around AI Implementations

When it comes to implementing AI in RCM, here are the most common fears:

• Fear of the Unknown: AI is new territory, and with that, comes unknowns that require time to get acquainted with.
• Uncertainty About ROI: Many RCM managers are unsure about the return on investment that AI can deliver, fearing that the costs may outweigh the benefits.
• Initial High Costs: The upfront investment for AI technology can be intimidating, covering software, integration, and potential infrastructure upgrades.
• Fear of Implementation Expenses: The perceived complexity of integrating AI into existing systems, along with ongoing maintenance costs, can be daunting.

Statistics and industry reports often highlight these fears, reinforcing the hesitation to adopt AI solutions. However, these concerns, while valid, overlook the long-term productivity gains and operational efficiencies that AI can bring to RCM.

Time and Cost of Onboarding New RCM Employees

On the flip side is the difficulty of hiring qualified medical coders. According to a survey by the Medical Group Management Association (MGMA), 34% of medical group leaders report difficulties in finding qualified coders. This adds to the burden of the already lengthy and costly hiring process.

Additionally, larger organizations typically have more structured and formal hiring processes, which can prolong the hiring timeline. They often have dedicated human resources departments that handle recruitment, screening, interviewing, and onboarding new employees.

Here's a breakdown of the typical hiring and onboarding timeline:

Prehire:

• Month 1: Application Window & Review (1 month): Applications are screened by HR for minimum qualifications.
• Month 2: Initial Screening (1 month): Hiring teams review qualified applicants and conduct screening calls/emails.
• Month 3: Interviews (1 month): Candidates go through multiple rounds of interviews with the hiring team, including skills assessments.

Hiring:

• Month 4-5: Offer and Background Checks (1-2 months): Selected candidates receive an offer, and background checks are conducted, often starting 1 month later.

Healthcare has one of the longest average times-to-hire compared to other industries. A LinkedIn study found the average time-to-fill a role in healthcare is 49 days. While the hiring process for RCM and other healthcare roles can vary, it typically takes 2-3 months from application to start date, with specialized clinical roles often taking longer due to extensive credentialing requirements.

First 90 Days:

• Month 6-7: Start Date (1-2 months after offer): The new hire's start date depends on the notice period required for their current role and the employer's onboarding process.
• Month 7-9: Training and Full Operation (2-3 months):
  • Entry-level RCM roles may take several months to become proficient in medical coding, billing, and other RCM processes.
  • Experienced RCM professionals may require less extensive training, focusing more on organization-specific policies and systems.
• Employee Turnover: If an employee quits, the hiring and training cycle starts again, adding more time and costs to the process.

The lengthy and costly process of hiring and training new RCM employees can be a significant drain on resources. Not only does it take months to get a new hire fully operational, but the constant turnover means that this cycle is often repeated multiple times a year. This is where AI can offer a transformative solution, providing immediate operational efficiency and reducing the burden of ongoing training and turnover.

Time to Implement AI Agents in Cloud-Based RCM

Implementing AI agents in a cloud-based RCM system is significantly more efficient compared to traditional hiring processes.

‍Here’s a breakdown of the timeline for deploying AI agents:

Prebuild:

• Month 1: Vendor Selection & Initial Screening via Discovery Call (1 month): Identifying the right AI solution providers and assessing their capabilities.
• Month 2: Process Review (1 month): Reviewing and mapping out current RCM processes to determine integration points for AI. Custom Map Designed for each AI Agent.
• Month 3: Proposal Review (1 month)
• Month 4: Contract Sign (1 month)

First 90 Days:

• Month 5: Onboarding (1 month): Setting up initial configurations and integrations with existing systems, Custom Map Delivered - Engineering team prototypes and develops your solution.
• Month 6-7: Minimum Viable Product Launched: Testing and validating AI systems to ensure smooth operation and full deployment. Live in production with continuous improvement. Training AI models using historical data to ensure accuracy and reliability.
  • Once integrated, AI systems learn and adapt quickly compared to human employees.
  • AI can handle large volumes of data and tasks immediately after deployment.
  • Continuous improvement through machine learning algorithms without the need for retraining like human employees.
  • AI agents begin to work immediately after deployment, handling large volumes of data and tasks efficiently.
  • No downtime for training and no learning curve, unlike human employees.
• Month 8: Fully Human Capable AI Agent Launched
• Ongoing Months: Hypercare & Scale
  • Once the first AI agent is implemented, adding more is as simple as pressing a button, avoiding the need for repeated training and onboarding processes. This is a huge win for growing RCM teams.

By streamlining the implementation process, AI agents can be deployed and fully operational within a few months, providing immediate productivity gains and allowing RCM departments to scale efficiently without the constant need for hiring and training new employees.

Productivity Gains with AI in RCM

The implementation of AI agents in RCM is not about replacing human workers — it's about significantly enhancing productivity and operational efficiency. Here are some of the key productivity gains that AI can bring to RCM:

Immediate Operational Efficiency:

• Immediate Task Handling: AI agents can begin processing large volumes of data immediately after deployment, reducing the time spent on repetitive tasks such as medical coding, billing, and data entry.
• Error Reduction: By minimizing human error, AI improves the accuracy of data processing, leading to more reliable and compliant RCM operations.
• Continuous Improvement: AI systems continuously learn and improve from historical data and ongoing operations, enhancing their performance without the need for additional training.

Scalability and Consistency:

• Effortless Scaling: AI systems can be scaled up quickly and efficiently, allowing RCM departments to handle increasing workloads without the need for extensive retraining or additional hiring.
• Consistent Performance: Unlike human employees, AI agents provide consistent performance without variability, ensuring reliable and predictable outcomes.

Reduced Turnover Impact:

• No Turnover: AI agents do not quit, reducing the disruption and costs associated with employee turnover. This ensures that your RCM operations remain stable and efficient over time.
• Unlimited Expansion: AI agents can handle nearly unlimited amounts of work, enabling one AI agent to be ramped up to do the job of 50 people.
• Easy Expansion: Adding more AI agents is straightforward and quick, avoiding the repetitive cycle of hiring and training new staff, which is a significant win for growing RCM teams.

Enhanced Data Handling and Analysis:

• Superior Data Processing: AI can analyze and process data at speeds unmatched by human employees, providing real-time insights and improvements that enhance decision-making capabilities.
• Improved Compliance and Reporting: Automated data handling and analysis through AI lead to better compliance with regulations and more accurate reporting, ensuring that your RCM operations meet all necessary standards.

By integrating AI into your RCM processes, you can achieve significant productivity gains that go beyond what is possible with human employees alone. The ability to scale operations efficiently, reduce errors, and maintain consistent performance makes AI an invaluable tool for any RCM department looking to improve its productivity and operational efficiency.

Next Steps

As an RCM manager, it's time to consider how AI can revolutionize your department. Here are some actionable steps to get started:

1. Assess Current Processes: Take a close look at your current RCM hiring and operational processes. Identify areas where AI can provide the most significant impact, such as reducing manual tasks, improving data accuracy, and increasing overall efficiency.
2. Seek Expert Consultations: Reach out to AI consultants and vendors who specialize in RCM. These experts can provide insights and help you understand the potential benefits and ROI of integrating AI into your processes. Consider piloting AI projects to see firsthand how AI can enhance your operations.
3. Evaluate for Efficiency: Continuously evaluate your RCM processes to pinpoint areas where efficiency can be improved. Implementing AI solutions can streamline your workflows, reduce errors, and ensure consistent performance, helping your department operate more smoothly and effectively.

Closing Thoughts

The endless cycle of hiring, training, and managing staff in RCM departments is a well-known challenge, draining resources, time, and energy. However, the implementation of AI technology offers a transformative solution that can break this cycle and bring about significant productivity gains.

Hiring AI agents is less burdensome than hiring new real-life employees. AI doesn't quit, doesn't need retraining, and can immediately take over repetitive tasks, handle large volumes of data, and continuously improve its performance. By embracing AI, RCM departments can achieve immediate operational efficiency, reduce the impact of turnover, and enhance data handling and analysis.