Leveling the Playing Field: The Provider's Playbook to Applying AI in RCM in 2025
6 tried-and-true ways that revenue cycle teams are leveraging AI to improve team efficiency and maximize revenue recovery from payers.
Start Reading
Table of Contents
Introduction: Current State
Chapter 1: Patient Scheduling and Registration
Chapter 2: Prior Authorization
Chapter 3: Charge Capture and Coding
Conclusion: Looking to the Future
Chapter 4: Claims Submission
Chapter 5: Payment Posting
Chapter 6: Trend Reporting & Analytics
It's not an easy time to be a healthcare provider. Staffing shortages, employee burnout, regulatory and compliance requirements, and inflationary pressures are just a few of the challenges facing providers each day. Compounding these everyday challenges are the strained relationships between providers and payers. Over the past few years, it has become increasingly difficult to collect revenue from payers. Claim denial rates are consistently on the rise, and for providers, responding to and taking action on denied claims is costly and time-consuming. More often than not, payers are using AI to efficiently detect issues and deny claims. In order to reduce denials, decrease days in AR, and maximize recoverable revenue, providers need to go head-to-head with payers by leveraging AI across the revenue cycle. In this eBook, we'll dive into 6 realistic ways that you can leverage AI across your revenue cycle to reclaim your revenue.
Let's Face It...
Patient Scheduling and Registration
Status quo: Typically, scheduling and registration are completed manually before the patient's appointment. This includes recording patient intake information like contact information, insurance details, and reason for scheduling. This is a manual process (completed either digitally or on paper) that is both time consuming and can leave room for errors or typos.
With the right technology: An AI-powered platform can review scheduling and registration information to ensure the data is complete and accurate and flag any potential coverage issues ahead of time. This gives teams the opportunity to address any typos, corrent information, or verify insurance to prevent any eligibility-related claim denials.
A better future: An AI-powered platform can drastically reduce the number of downstream denials by ensuring that information is accurate at the time of scheduling and registration. Getting ahead of eligibility and ensuring accurate data submission reduces the possibility of unexpected medical bills on the patient and ultimately improves the patient experience.
Denial Trends | Data suggests that 20-30% of claim denials are a result of missing patient information, like accurate name, date of birth, insurance member ID or policy information.
2. Pre-Certifications
Status quo: Revenue cycle teams need to stay on top of ever-changing payer requirements — which includes information around which procedures or services require prior authorization. If prior authorization is not obtained ahead of the appointment, the claim can be denied.
With the right technology: An AI-powered platform and monitor external data sources on the back-end to stay on top of payer policy changes and prior authorization requirements so that teams never miss a prior authorization. In some cases, AI can automate the prior authorization requests for upcoming appointments.
A better future: Teams can work more efficiently and reduce prior-authorization related denials. This improves the patient experience by ensuring that patients are authorized for procedures quickly and efficiently, reducing wait times for procedures and the chance of the patient receiving a bill for services that should otherwise be covered.
Efficiency Gains | "Adonis Intelligence has freed up at least one full day for me due to it's ability to present usable data. Typically, I spend a week manipulating data to try to get a handle on the AR backlog. This platform is the main reason why I am no longer playing catchup on my AR backlog." - CFO, 40+ Provider Orthopedics Practice
3. Charge Capture and Coding
Status quo: Providers document services and procedures using either paper-based or digital notes, which are then either submitted by the provider or reviewed by coding teams who assign the correct CPT code and input these into the billing system. RCM teams review these to identify errors or missing info ahead of submitting claims. This is labor-intensive and prone to errors or missing information that lead to denials.
With the right technology: The right AI platform can integrate with your EHR and analyze clinical notes to ensure that coding is accurate and services are being billed correctly. AI can flag when changes need to be made to claims ahead of submsision to correct information or to add missing requirements.
A better future: Teams don't need to worry about manually reviewing claims to ensure accurate coding. This drives team efficiency and ensures claims are submitted accurately and with all relevant or required information. Leveraging AI for charge capture and coding helps teams work quickly and effectively and ensures that a patient's record is as accurate and up-to-date as possible.
Proactive Identification | "Adonis Intelligence is allowing us to identify issues before they become monstrous. Before implementing AI, it would take us longer to identify not only what the issue was, but how impactful it would be on our entire book of business. With Adonis, if we have an issue, it will immediately identify it for us, and it will bubble up all of the impacted inventory associated to that particular denial or hold that we’re seeing." - EVP Revenue Cycle, ApolloMD Watch Webinar
4. Claims Submission
Status quo: As you can see from the processes outlined in chapters 1-3, everything that makes up the process of claim submission - from entering patient and billing information into systems, to verifying compliance with payer rules, to sending claims via clearinghouses or directly to payers - is a time intensive and often reactive process.
With the right technology: Not only can AI help in the ways we've outlined thus far, but the right AI-powered platform can take things one step further by proactively predicting denials. AI can consistently monitor industry data & trends to know when and why a claim or set of claims will get denied, and will alert you ahead of submission that you need to make changes.
A better future: RCM teams are able to see into the future and predict denials before they occur. This helps teams work more proactively, stay on top of payer policy changes or compliance regulations, and reduce overall denials.
Maximizing Revenue | By leveraging an AI platform for RCM, this emergency medicine provider reduced denials and improved their net collection rate by 10%.
5. Payment Posting
Status quo: RCM teams manually post payments by reviewing explanation of benefits (EOBs) or electronic remittance advice (ERA) documents, reconciling payments with claims, and entering data into billing systems, often matching payments line-by-line to services. This process is time consuming and can result in errors like misapplied payments or missed denials.
With the right technology: An AI-powered platform can automatically analyze remittance data to identify any discrepancies or errors and accelerate the reconciliation process by accurately allocating payments to the correct patient accounts
A better future: Automating the process of payment posting speeds up the process drastically, while also freeing up your revenue cycle teams to focus on mission-critical follow up tasks, like addressing high value denials that require immediate action. AI-driven payment posting decreases days in AR and ensures patient accounts are accurate and up-to-date.
Driving Speed-to-Cash | By leveraging an AI platform for RCM, this emergency medicine provider decreased their days in AR by 14 days.
6. Trend Reporting and Analyics
Historical reality: For RCM teams, pulling both high-level and drill-down reports can be incredibly time-consuming. Disparate systems and data sources, manual trend calculations, and a lack of available data can make performance reporting incredibly difficult.
With the right technology: An AI-powered platform can easily offer personalized dashboards and reports that track the core KPIs that are important to your team. AI can consistently monitor your revenue cycle for performance trends, team productivity, or other financial or operational KPIs that are important to you and alert you to trends or anomalies in real-time.
The result: Everyone at the provider group can quickly access both high-level and drill-down reports that matter most to them. Biller productivity, collection rates, denial trends, carrier behavior, and more, can all be monitored and available to inform strategic decision-making throughout the organization.
Advanced Insight | "We are excited to leverage Adonis Intelligence to modernize our revenue cycle operations, giving us enhanced visibility into claim statuses, underpayments, trends, and more. Bringing Adonis Intelligence on board will increase our team's bandwidth, allowing us to drive revenue growth." CEO, Tend Dental
There are countless ways that AI can streamline operations across your revenue cycle. Whether you're looking to maximize recoverable revenue by mitigating denials, drive team efficiency by enhancing manual workflows with AI, or increase visibility into performance trends and KPIs across your organization, 2025 might be the right time for you to start thinking about where you can implement an AI-driven platform. To see another real-world example, check out our recent webinar with the VP of RCM at Allied Digestive Health to learn how ADH is leveraging AI across their revenue cycle. If you're interested in learning more about Adonis Intelligence, an AI-powered platform that levels the playing field with payers and helps your practice reclaim the revenue you're owed, fill out the form to contact us or visit Adonis.io to learn more.
Reclaim Your Revenue in 2025
See Where AI Fits in Your Revenue Cycle:
