5 Ways Automation Is Transforming Medical Claims Processing

5 Ways Automation Is Transforming Medical Claims Processing

As a result of the pandemic, healthcare providers are actively looking to deliver more and better care at lower costs in 2022. Strategies to accomplish this—and reduce unnecessary human contact at the same time—include remote work, cloud technology, and process automation.

Process automation has a host of benefits, especially when it comes to claims processing. Claims processing is a time-consuming and tedious process; it’s also one that directly impacts the financial health of your business. Read on to learn about the top challenges of this crucial task, and why providers are turning to automation in claims processing to solve them.

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Top Challenges To (Manual) Medical Claims Processing

Medical claims processing requires multiple steps, all of which must take place whenever a patient visits an in-network healthcare provider:

  • Data extraction—the provider must collect the patient’s insurance information
  • Verification—the provider must confirm benefits or eligibility
  • Submission—the provider must submit an accurate claim

This iterative process is complicated by several challenges:

Insurer systems vary.

In the United States alone, there are hundreds of health insurance companies, public and private, and no single standardized process for medical claim submission. Some insurers accept claims using a web portal or form, others rely on email. Submission requirements also vary—some insurance companies require a PDF attachment, for example. Since most medical offices accept multiple insurance types, human workers processing claims are forced to toggle between systems and customize the claim submission format for every patient.

Providers submit a high volume of claims.

Most medical providers serve a large number of patients every day, which means dedicating significant time and effort to claims processing. Such high volumes can generate a sizable backlog of claims, impacting patients’ timely care and creating a backlog on payments.

Errors are inevitable and costly.

Some degree of human error is a given in every industry. And in the case of repetitive, manual tasks that require unstructured data transfer at high volume, the likelihood for fatigue and mistakes increases. Unfortunately, the submission of claims that are inaccurate, incomplete, or noncompliant can result in delays or even in an insurance company’s refusal to pay a claim. When you factor in the time and effort required to resubmit, these mistakes can be highly expensive.

Cash flow hinges on timely, accurate claims.

Simply put, a medical office won’t get paid for the service they’ve provided until a claim is successfully processed. In this way, providers are reliant on claims processing to secure and augment their cash flow. Slowness and errors can endanger a provider’s bottom line—they can also lead to more challenging bookkeeping and additional stress for patients if a mistake triggers an insurance company to bill the patient.

5 Key Benefits Of Automation In Claims Processing

Fortunately, automated claims processing is prepared to address these challenges.

For medical claims processing, RPA (or robot process automation) is an ideal solution:

A rules-based RPA bot can be configured to extract patient insurance information, format claim submissions appropriately, and submit claims. The result is a faster, more accurate process that frees up valuable human resources, allows healthcare providers to expand, and offers continual return on investment.

Here’s how automation improves claims processing:

1. Claims can be processed faster.

RPA bots are capable of processing higher volumes of data faster than human workers. Bots can also work continuously without needing a break over a 24-hour period.

Training and deploying a single bot to handle claims allows a healthcare provider to determine how many claims each individual bot can turn around within a day. The provider could then add on bots (each one doubling the initial bot’s output) until the desired number of claims is processed every 24 hours. Nividous platform enabled intelligent automation for one leading specialty healthcare company to reduce process handling time by 70%.

2. Errors are greatly minimized.

Automation removes the possibility for multiple error-types: wrongly entered patient insurance data, invalid medical codes, and non-compliant submission formats to start.

RPA bots for claims process automation mitigate human error because (1) they perform consistently (each task is executed with the exact same level of accuracy, from first to last), (2) validation is built into the process (an RPA bot will not perform a task outside of established parameters), and (3) bots conserve human attention and focus for higher-level work (thus reducing human error due to inattention or fatigue).

3. Human workers can better serve their organizations.

Given the human capacity for innovation, creativity, empathy, and insight, employing workers to manually move data between systems for hours on end isn’t the best use of their time. Especially when you consider that most healthcare providers are ultimately focused on improving health, lowering costs, and providing better patient care.

By automating claims processing—a task that’s a perfect fit for RPA—clinics and providers can dedicate human talent to furthering their mission. Employee satisfaction and productivity are also likely to increase as a result.

4. Providers can scale their offerings.

Consider the case of a leading vision care group where manual tasks like claims processing consumed 30% of key staff members’ time. Automated claims processing can help organizations keep pace with rapid growth: in the example, Nividous RPA bots enabled AEG Vision to continue scaling at 35% growth year-over-year. Freeing up team members to focus on higher-value responsibilities can help businesses meet increasing demand and attract greater numbers of patients. By adding on bots, the number of claims a provider can process is nearly unlimited—for AEG, Nividous Bots post and reconcile 40K claims per month.

The only bounds to scaling a practice or service wind up being the limited human capacity to provide quality care to each individual.

5. ROI is substantial and sustained.

The initial investment in developing, deploying, and purchasing bot licenses to automate claims processing using RPA is well worth the returns, for two main reasons:

First, each of the benefits listed above directly impacts your bottom line—faster and more accurate claims processing means payments are received more quickly and consistently, without the need to backtrack and correct errors or push through a backlog. Increased human productivity means employee wages yield higher returns and retention is greater. And the potential to scale because automation in claims processing enables higher claim volumes is a lucrative prospect.

Secondly, RPA offers lasting value. Once a bot is “trained,” it’s set up to work for the long haul, versus each new human worker who requires onboarding to learn the ins and outs of a complicated process.

Looking to automate your claims processing?

If you’re interested in automating claims processing, there’s one additional benefit of RPA to consider. RPA pairs well with AI (artificial intelligence) and BPM (business process management) to streamline back-office processes from end-to-end through intelligent automation. Making a start with RPA can prepare your organization to increase efficiency across the board. Returning to the aforementioned eye care group, using Nividous platform to combine automated claims processing with a suite of other automations across revenue cycle management (including patient scheduling, benefits verification, patient statements, and more) saved them 250K hours in staff time and $4 million dollars.

Automation in healthcare affords big gains, especially for claims processing. Nividous specializes in comprehensive automations to help your medical practice team enhance patient care and outcomes.

Robotic Process Automation (RPA)

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