November 24, 2022

How to Optimize Revenue Cycle Management with Artificial intelligence

The main challenges experienced in revenue cycle management are errors in billing and collections. Organizations must deal with the challenge of manually processing bills and monitoring claims. Artificial intelligence can be used to optimize revenue cycle management, prevent leaks, and boost production.

It provides organizations with a robust and long-lasting RCM automation solution. AI in RCM can handle complex tasks such as determining patient eligibility or denials. Using AI to optimize revenue cycle management can be achieved in different ways.

Reducing the risks of claims denial

The main causes of claims denial are missing or incorrect information, late submissions, lack of premium payment, and delays in communication response. It is necessary that organizations submit claims in time but also ensure they are error-free. If more denials are made, it increases losses to organizations.

Using artificial intelligence helps pinpoint potential denials so that the claims team can correct them before submission. Some claims are denied due to missing charges. AI can help detect such anomalies for correction before sending claims. To improve performance, organizations also need to implement revenue intelligence in their systems.

Revenue intelligence tools are crucial in providing organizations with an all-rounded customer satisfaction cycle. The tool collects and analyzes important sales data to generate key insights that can improve productivity. The revenue intelligence software by revenue Grid is a reliable solution for organizations in all business sectors. It gives organizations 3600 visibility into company performance, opportunities, revenue streams, and risks.

Improving billing accuracy

Transcription errors often occur during data entry. These errors cost organizations a lot of money because they demand correction when it is too late. Due to this, claims take longer to be paid, which can affect cash flow. RCM experts use AI to streamline workflows and improve billing. Errors are easily identified during validation checks which eliminate delays during claim submissions. AI helps reduce human errors, which improves the entire revenue cycle management.

Improving data quality

When AI is used for data entry and validation checks, it speeds up the entire revenue cycle management process. It eliminates human errors, and the revenue management team achieves greater data quality. Automated AI data capture can help improve data quality in different ways.

  • Identifying duplicates: Duplicates can cause double claims and denials. AI helps identify duplicates which is harder in manual entries.
  • Automated data capture: Poor data capture leads to losses. Automation helps capture what is important and helps organizations focus on customer satisfaction.
  • Identify human errors: Manual entries do not lack anomalies, but the use of AI helps identify them.
  • Reduce time and costs: Manual data entries take a lot of time and thus increase costs. AI reduces time, which eventually reduces data entry costs.

AI provides real-time analytics

Sometimes organizations delay providing services because they are waiting for an insurance company to confirm if the client is eligible for coverage. At other times, a patient in a health facility may want to know the amount they can claim from insurance coverage. This information is necessary to help them decide the treatment options to choose.

AI-powered revenue cycle management helps the practitioner and the patient in real-time decision-making.

Optimization of workflows for improved outcomes

Organizations today are adopting digitization in their business processes. The revenue cycle management teams need to be keener and capture all revenue flowing from multiple channels. Efficient workflow management is necessary to ensure streamlined and collaborative efforts in the entire RCM process. AI helps create optimized workflows for improved outcomes without demanding bigger investments.

Redirect staff efforts to areas of greater value

Highly manual processes require more staff and hours to complete. The use of AI-automated processes could save organizations millions in revenue. Through automation, the staff can be redirected to do activities that produce greater value for the organization. AI helps in the analysis of customer demographics to help the RCM team predict the best billing approach to use for each.

Final thoughts

AI will continue to play a crucial role in revenue cycle management. The RCM vendors provide AI-powered tools that help organizations reduce costs, streamline operations, and improve quality and profitability through enhanced RCM processes.

About the author 

Peter Hatch

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