How Can Robotic Process Automation Speed Up Payer Claims Processing

Robotic Process Automation

Healthcare is a data intensive industry.

According to the CDC, there are nearly one billion patient visits yearly. This only goes to show the large volumes of data healthcare providers have to cope with. This includes intake forms, bills, and insurance claims.

When it comes to the medical billing process, medical claims are processed after services are rendered. Sometimes, this can take up to months due to multiple steps involved to ensure claims are received and paid out correctly.

Traditionally, managing the claims process involved hiring more manpower to increase efficiency.

Robotic Process Automation

However, this has been unsuccessful due to the errors involved in data entry, leading to higher costs and prolonged turnaround time.

Recently, more attention is being paid to automation in healthcare claims processing like Robotic Process Automation (RPA) software that enhances overall efficiency.

In this article, we will discuss how robotic process automation can speed up payer claims processing.

Let’s get started.

1. Automating Data Entry

When a patient calls to book an appointment with a healthcare provider, they need to provide their insurance information to ensure they are eligible for services as covered under the insurance plan.

In addition to that, during check-in or check-out, the patient must fill particular forms to confirm the services rendered by the doctor for appropriate billing.

The challenge with manual data entry processes is their repetitive nature due to large volumes of data and proneness to errors because of outdated technology, inconsistent documents, and illegible handwritten text.

Automation in healthcare claims processing through RPA is changing how work gets done.

Together with computer vision for image recognition and AI natural language processing, you can automate the data entry process.

Software robots take on repetitive tasks such as Data Extraction from documents like identity cards, move files, and fill in forms. This frees healthcare providers and payers from repetitive tasks, allowing them to focus on other endeavors like interacting with patients.

According to a survey by Forrester Consulting, nearly 70% of respondents get more value from personnel because they are able to focus on more strategic work.

Max Healthcare Institute needed to streamline claims processing and data recording to reduce turnaround time and enhance accuracy. Through UiPath, they adopted an RPA software and were able to reduce claims processing turnaround time by 50%.

2. Eliminating Process Errors

Health insurance claims processing is deeply reliant on speed and accuracy to meet the customer demand and ensure payment in a timely fashion.

Although many insurance payers already have some level of automation, for example data extraction by scanning PDF documents, they still require human intervention to process and navigate data across various systems.

This makes the claims process tedious and lengthy, leaving it exposed to errors, which leads to additional costs.

Automation in healthcare claims processing with RPA software can overcome such obstacles because it is a fully integrated end-to-end solution.

RPA is more preferred over other forms of automation because of its minimal disruption.  With its precision data extraction technology, RPA automatically validates rules to ensure patients’ billing and claims processing are accurate.

According to Uipath, RPA is entirely scalable and has up to 100% accuracy in medical claims processing by payers.

It leverages natural language processing and computer vision for Content Transformation, which helps in understanding unstructured and semi-structured data, enabling it to track complex errors.

A major healthcare product and service organization was experiencing errors due to a manual claim audit process. On partnering with SDLC, the team designed an RPA solution to perform the audit process, therefore, eliminating defects.

Robotic Process Automation

3. Monitoring Adjudication

When an insurance payer receives a claim, it undergoes a process known as adjudication.

This is where the payer evaluates the medical claim to determine if it’s valid and how much should be reimbursed.

However, the claim can either be accepted, rejected, or denied.

This contributes to the lengthy process because the payer has to evaluate every claim and when one is rejected, they have to communicate to the provider using remittance advice codes for an explanation.

Medical claims processing automation relieves the payer of the lengthy validation process which requires them to go back and forth with healthcare providers about the accuracy of claims. According to Deloitte, by leveraging RPA, payers can speed up labour intensive tasks by 60%.

Advanced robots have the ability to perform cognitive processes, such as routine analyses through data extraction and content transformation to interpret text.

By applying machine learning models, RPA software can make complex decisions, such as rejecting or accepting a claim.

In addition to that, they can engage in conversations and chats, which makes it easier to communicate with healthcare providers about insurance claims.

A major U.S healthcare coverage administrator needed to review cases whenever members submitted a policy.

However, they did so through email, fax, or web form which was time-consuming.He was able to cut the manual work by 85% across the process by adopting an RPA solution.

4. Compliance Management

Health insurance is one of the most regulated sectors.

However, insurance payers often fall behind in particular compliance obligations because they have to hire employees to analyze complex legal mandates and ensure the insurance company conforms to claim policies.

From a personnel and infrastructure standpoint, regulatory compliance can be costly.

In addition to that, when an insurance payer fails to observe regulatory compliance mandates, such as patient data protection, they risk facing repercussions like monetary fines.

Leveraging RPA in compliance management by insurance payers has numerous benefits including reduced remediation efforts and expanded resource capacity, leading to lower costs.

According to a survey by Deloitte, over 90% of the respondents agree that RPA has met or exceeded their expectations for better compliance.

RPA software for compliance uses machine learning and allows you to create trigger-driven and rule-based workflows for medical claims processing automation.

Because RPA has the ability to pull and aggregate data from many sources, it enhances the efficiency of regulatory reporting. This way, billing teams don’t have to rush to double-check each claim only to find that a mistaken portion doesn’t comply with the regulations.

American Fidelity Insurance wanted to automate a number of tasks such as reading emails which were dependent on human intervention. This led to compliance and regulatory challenges such as claim fraud.

Upon partnering with UiPath, through RPA and machine learning, they were able to classify, categorize and analyze over 10,000 emails with the correct routine rules.

5. Payment Reimbursement

The final stage of the health insurance billing process is ensuring payment is correctly reimbursed to the healthcare provider.

However, medical claims are among the major causes of dissatisfaction among patients. According to a study by the American Medical Association, nearly one in five patients across America receive surprise bills months after treatment.

The sub-process of claims status checking may appear simple but considering that one payer could be providing service to thousands of patients, it goes without saying that the process takes long.

Where manpower is mainly relied on, claims may go unattended. Errors in the claims may also go unnoticed.

However, through medical claims processing automation, RPA speeds up the payer claims.

Through it’s complex rule-based workflows, RPA software through the use of bots is able to make quick analysis on medical claims and make rule-based decisions without human intervention.

According to Healthcare Finance, automated transactions could save the average payer around 40 minutes of medical processing claims.

If a patient is delinquent in making payments, follow-up requests can be electronically parsed through bots.

An eyecare practice was experiencing challenges like conducting eligibility checks due to manual processes. This was time-consuming and caused delayed cash flows. The Nividous RPA platform automated a series of cross functional operations and was able to save time on claims processing.

Conclusion

Medical claims processing is clearly a concern for many individuals.

This is evident from the 10-year low that was currently hit in health insurance satisfaction by a survey from the American Customer Satisfaction Index.

However, Robotic Process Automation can speed up payer claims from the first stage of the medical billing process where patients give their information to the last stage when payment is reimbursed.

Incorporate RPA as an end-to-end solution to automate your healthcare claims processing and ultimately speed up your payment process.

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