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Jul 28, 2022
Min Read

Medical Claims Processing is Complicated—Here's Why It Should Be Automated

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super.AI
Chief AI for Everyone Officer
SUMMARY

According to the Center for American Progress, US healthcare payers and providers spend around $496B annually on billing and insurance-related (BIR) costs, which includes an administrative excess of $248B. Put differently, the United States spends twice as much as is necessary on healthcare administrative expenses. Looking forward, national healthcare spending is projected to increase by 5.5% annually through 2027, at which point it will represent over 19% of GDP, up from 17.9% in 2017.

Unsurprisingly, the US spends about twice as much on healthcare per capita compared to other countries in the Organization for Economic Co-operation and Development (OECD), and the gap continues to grow. One of the primary drivers for high processing costs is paper-based processes. This article explains how advances in artificial intelligence (AI) make it possible to automate processing of any medical claims document at scale, improving processing accuracy, speed, and cost efficiency.

How are medical claims processed?

There are a number of steps involved in medical claims processing, and automation can save time and money for both healthcare providers and patients. Examining how medical claims are processed helps highlight both the costly complexity that breeds mistakes, and the opportunity to improve the the claims processing workflow through automation. Here’s what happens after a patient leaves a doctor’s office:

Step 1: Claim transmission

Claims are sent to the insurance company directly or via a clearinghouse. The clearinghouse, used in most cases, reviews and reformats medical claims before sending them to the payer.

  • Paper claims are either scanned or manually entered
  • Electronic claims enter the system directly

Step 2: Initial review

The claim is reviewed for errors such as duplicate charges, typos, and a submission date outside the filing deadline.

Step 3: Member lookup

The patient’s name and policy number are checked against the insurance company database to make sure the member has an active insurance policy.

Step 4: Network check

The patient’s doctor and clinic location are checked against the insurance company database to see if they are in the patient’s insurance network.

Step 5: Repricing

The prices services the doctor billed for are adjusted based on the negotiated rates for the patient’s insurance plan.

Step 6: Adjudication

The patient’s insurance plan benefits are compared to the services received to determine to determine if each service is covered and how much the insurance plan will pay.

Step 7: Medical necessity evaluation

The patient’s claim is reviewed to ensure each that each service provided is medically necessary, following industry best practices, and safe for the patient. This keeps the insurance company and patient from paying for unnecessary services.

Step 8: Risk assessment

The claim is then flagged as low- to high-risk for fraud. This is determined using a variety of factors, including the types of services, total charges on the claim, and individual charges.

Step 9: Payment

The insurance company sends payment to the doctor for the amount the patient’s insurance plan covers based on negotiated rates and plan coverage.

Step 10: Explanation of Benefits (EOB)

The insurance company creates an explanation of benefits that outlines how much the doctor billed, how much the insurance company paid, and how much the patient must cover as an out-of-pocket expense.

Step 11: Billing

If additional payment is due, the doctor’s office will send the patient a bill that should align with the total and services listed on the EOB.

This elaborate process involves a number of different organizations, people, and systems, presenting many opportunities for something to go wrong. Given the massive amount of money wasted on BIR costs annually, automation can save insurance companies huge sums by dramatically reducing processing times and dependency on manual effort, all while increasing the accuracy of information entered into claims processing systems.

Automating claims processing with IDP

Throughout the entire medical claims process, a number of different documents must be processed including:

  • ACORD Forms
  • CMS 1500 and 1450s/UB-04 Forms
  • ADA Dental Claim Forms
  • Supporting documentation such as doctors orders, patient records, receipts, identity documents, and income statements

Automating processing of these documents can dramatically lower costs, reduce errors, improve member satisfaction, and accelerate claims turnaround times. Healthcare payers and providers have used OCR, data capture, and, more recently, Intelligent Document Processing (IDP) solutions to automate document processing before. However, variations in claims document formats, and the variety of supporting documentation attached to them, makes medical claims document processing automation uniquely challenging.

Key benefits of next-generation IDP for claims processing automation

Next-generation IDP and Unstructured Data Processing (UDP) solutions can automate a greater percentage of documents to lower costs. These platforms achieve better results by breaking processing of each document into smaller tasks, then leveraging the best AI, human, or bot worker to process it. The results are then intelligently combined into a single, structured output. The system automatically learns from human workers to continuously train and deploy new AI, driving down costs and increasing automation rates over time.

Benefits of leveraging these modern solutions for automating claims document processing include:

Faster turnaround

Reducing the amount of manual effort involved in claims processing is the key to improving cost efficiency. This means both eliminating manual data entry, as well as minimizing the amount of time human workers spend correcting errors or resolving edge cases for data extracted automatically.

Next-generation IDP solutions quickly and accurately extract data from any document, and automatically flag low confidence extractions and outliers for human review. This human input is then used to train the AI models responsible for extracting data, further improving accuracy and automation rates while reducing reliance on human workers.

Fewer errors

As mentioned above, accelerating turnaround times it about both minimizing manual effort and maximizing the accuracy of automation. Automating insurance claims document processing removes the possibility for multiple common error-types including:

  • Wrongly entered patient insurance data
  • Invalid medical codes
  • Non-compliant submission formats

These are typically human errors that automated systems simply aren’t prone to because they execute tasks consistently, and validation built into the system ensures errors are identified and resolved. Additionally, automation frees up humans to focus on high-level tasks, reducing error caused by inattention or fatigue.

Happier humans

Manually transferring data from documents into claims processing systems is repetitive and arduous work that humans are poorly suited for. By automating claims processing, medical clinics and insurance providers can direct human innovation, creativity, and empathy toward more rewarding and impactful work. Letting intelligent machines handle uninteresting and tedious claims processing tasks will also improve employee satisfaction.

Looking to automate claims processing?

Super.AI Intelligent Document Processing (IDP) automates information capture from paper and digital medical claims, improving accuracy and cost efficiency while reducing processing time. The solution supports all the claims documents listed above, as well as any attachments. For more information about automating insurance claims document processing, check out the following resources:

Other Tags:
IDP
UDP
Document Automation
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