WhiteSpace Health Blogs

6 AI Benefits for the Back-office

by Carrie Bauman

Introduction

Back-offices are increasingly harnessing the power of Artificial Intelligence (AI). These technologies are not merely buzzwords. They introduce essential changes that fundamentally enhance Revenue Cycle Management (RCM), practice management automation, and medical billing automation. Let’s dive deep into the transformative effects of revenue cycle AI on back-office billing operations, providing data-driven healthcare solutions that streamline processes and boost efficiency.

AI Use for Revenue Cycle Processes

The integration of AI within Revenue Cycle Management processes is revolutionizing the dynamics of healthcare billing. These advanced technologies automate repetitive tasks and analyze vast amounts of data to improve financial outcomes and operational efficiencies. By automating complex processes, AI allows billing staff to focus on more strategic tasks that require human intervention, thus optimizing the overall workflow and reducing errors.

Benefits of Using AI in the Back-Office

AI offers a plethora of benefits to back-office billing companies such as streamlining operations and enhancing the accuracy of financial transactions. Here’s how these technologies are supporting the front-office with data from patient access operations to make a significant impact

Identify Eligibility Verification Data

AI platforms quickly verify eligibility, enhancing patient satisfaction and reducing claim denials. They automate the verification process, pulling data from multiple sources to ensure accuracy and completeness.

Percent of Copay Collections

By predicting patient payment behaviors, AI platforms improve copay collections, thereby increasing revenue upfront. This predictive capability allows practices to tailor their financial conversations with patients, based on likely payment behaviors.

Measure Follow-up Scheduling at Check-out

AI-driven scheduling platforms ensure timely follow-ups, enhancing patient care continuity. They can predict the optimal times for follow-ups and streamline appointment scheduling, reducing no-show rates

Analyze Patient Collections Versus Balance

AI platforms provide detailed insights into patient financial responsibilities and collection rates. They analyze trends over time to identify areas where collections can be improved.

Know the Prior Authorization Count

Helps in efficiently tracking and managing prior authorizations to expedite service delivery. AI systems streamline prior authorization by detecting cases that require prior authorization and initiating requests.

Avoid Front Office-related Denials

By predicting denial risk factors, AI systems inform staff which accounts to double check and verify the specific reasons the claim may be denied prior to releasing to the payer. By ensuring the claim meets specific payer requirements, the likelihood of errors leading to denials is reduced and claims have a higher probability of being paid timely, creating a predictable revenue cycle.

Billing and Charge Optimization Using Data from AI

AI powerfully impacts the optimization of billing and charge capture:

Track Daily Encounters with Charges Created

Ensures that all services rendered are captured and billed accurately. AI platforms monitor patient encounters in real time to guarantee no billable service goes unbilled.

Identify Daily Bills Submitted

Tracks the efficiency and timeliness of the billing process. AI systems can flag delays in submission and provide alerts to prevent revenue loss.

Measure Daily Encounters and Charges Created by Date of Service

Helps in forecasting revenue by analyzing data trends. AI platforms provide predictive analytics to forecast future billing, based on historical data.

Understand Bill and Submission Lag

AI identifies delays in the billing process, providing actionable insights into areas needing improvement.

List Unbilled Charge Amounts

AI platforms systematically highlight unbilled services, capturing all potential revenue and minimizing leakage.

Prevent Denials and Roots Causes Using ML Guided Steps

Machine Learning identifies and mitigates patterns leading to denials:

Segregate Denials Value and Volume

Helps prioritize which denials to address based on their financial impact, enabling more strategic denial management.

Identify Denial Recovery Volume

Tracks the volume of successfully overturned denials, providing insights into the effectiveness of denial management strategies.

Know the First Submission Claim Denial Volume

By reducing rework and identifying issues in initial submissions, ML reduces the time and resources spent on reprocessing claims.

Stop Revenue Leaks by Leveraging Accounts Receivable Data

Effective management of accounts receivable (A/R) is crucial for maintaining healthy cash flow and ensuring the financial stability of healthcare practices. By leveraging AI, back-office billing companies can transform their approach to monitoring and managing A/R, thereby preventing revenue leaks that can negatively impact a practice’s financial health.

Rolling A/R

This metric provides a continuous snapshot of outstanding patient balances and insurance reimbursements.

A/R Days

This is a critical measure of the average number of days it takes for a practice to collect payments.

A/R by Insurance by Patient Excluding Bad Debts

AI can disaggregate A/R data to provide detailed insights on receivables, excluding accounts classified as bad debts.

A/R Aging

AI-enhanced platforms analyze the age of accounts receivable to pinpoint how long bills have been outstanding.

A/R by Original Financial Classification

AI platforms can maintain and analyze data based on the original financial classifications assigned to different accounts.

Reduce Bad Debts with Unwanted Write-Offs

AI systems provide a comprehensive analysis of payer trends, which is essential for streamlined billing and negotiation:

Analyze Write-off Percentage

AI platforms can analyze the overall percentage of write-offs in relation to the total billing amount, giving a clearer picture of how much revenue is being lost to write-offs.

Monitor Write-offs by CPT Codes

AI platform can monitor write-offs at the level of specific Current Procedural Terminology (CPT) codes. This granular approach allows billing companies to see exactly which services are most frequently written off and why.

Prevent Double Adjustments

Double adjustments occur when a bill is adjusted more than once, often due to errors in processing or miscommunication.

Analyze Payer Trends to Resolve Major Reimbursement Issues

AI systems provide a comprehensive analysis of payer trends, which is essential for streamlined billing and negotiation:

Check Bills Submitted Payer-wise

Healthcare analytics AI platforms can categorize and analyze bills based on the payer, providing a clear overview of billing activity for each insurance company.

View New and Established E&M Frequencies.

AI systems track and analyze the frequency of both new and established E and M claims.

Identify Claims Paid Less than the Contracted Value

One of the most critical aspects of payer trend analysis is identifying discrepancies between the amount billed and the amount paid.

Generate Payer Mix Reports

These insights assist in negotiating better rates and understanding payer behaviors, ultimately leading to improved reimbursement.

How Can Back-Offices Leverage AI in Their RCM Processes?

To fully benefit from AI, back-offices should integrate these technologies with their existing systems, train staff on their benefits, and continuously monitor and adjust algorithms to suit the changing healthcare landscape.

Conclusion

The integration of AI into back-office operations signifies a significant advancement in Automated Medical Billing and AI in RCM Processes. By adopting these technologies, back offices can not only improve accuracy and efficiency but also enhance their overall financial performance. According to MGMA statistics, practices that have embraced these technologies have seen a reduction in denials by up to 20% and an improvement in cash flow by approximately 30%. The future of healthcare billing lies in the effective use of AI, making them not just beneficial but essential for modern revenue cycle management.

About Carrie Bauman