Claims Adjudication Explained: Understand the Process, Its Importance, and the Growing Role of AI

Claims adjudication refers to the stage in a claims lifecycle where the payer or insurer conducts an in-depth evaluation of a claim submitted by a provider. The evaluation process requires the payer to affirm the relevancy of a claim and ensure that it does not contain any errors regarding a patient’s personal information and that there are no omissions. The payer also needs to check for coding appropriateness and accuracy under medical codes, such as the Current Procedural Terminology (CPT) and the Healthcare Common Procedure Coding System (HCPCS).

What is the Importance of Claims Adjudication for Payers?

For an insurance company, claims processing is vital, primarily because of the financial stakes involved. As a general principle, insurers are expected to follow the 80/20 rule, also known as the medical loss ratio (MLR), in claims management. The rule requires them to spend at least 80% of their income from premiums on healthcare costs and service quality improvements, whereas the remaining 20% can be used for other expenses, such as administrative and marketing costs.

Apart from financial considerations, accurately adjudicating medical claims is significant for insurance companies for various compliance and operational reasons:

• Determining payment. Claims processing fixes the financial responsibility of both the insurer and patient with absolute clarity, removing any possibility of ambiguity or confusion and maintaining transparency.
• Validating treatments. Adjudication sufficiently validates the medical necessity of the treatments provided to patients. This prevents providers from performing unnecessary procedures or recommending unnecessary treatments.
• Ensuring accuracy. Carefully conducted reviews enable insurance companies to identify errors, preventing overpayments or underpayments for the medical services rendered.
• Fraud detection. As insurance companies examine claims thoroughly, they can spot fraudulent activities or any discrepancies that may negatively affect the healthcare system.
• Data generation. Every step in the adjudication process generates valuable data points that payers can use to identify patterns, train AI models, and improve overall service quality.

Besides insurers, healthcare providers must also be well-versed with the claims adjudication process to submit more complete and accurate claims that are less likely to get rejected or their amount reduced.

What are the Key Steps in the Claims Adjudication Process?

Once submitted for review, a claim undergoes a series of steps before the payer can make a decision.

Step 1: Initial Payer Review

This is the first step in the review process, where the insurer performs preliminary checks to determine claim accuracy. The aim is to find basic errors in the information provided in the claim, which includes dates of service, provider credentials, and patient name and ID number. Surprisingly, it is at this stage itself that many claims get rejected due to simple mistakes. For example, a provider may fill in the wrong diagnosis codes. One way to avoid such errors is to use a clearinghouse before submission to decrease the probability of a rejection.

Step 2: Automated Review

The next layer is the automated review or the mass adjudication process. Once a claim enters this stage, if it clears the first step, it is subjected to even tighter scrutiny, with the payer checking whether:

• The claim was submitted within the stipulated timeframe
• The services rendered are covered under the patient’s plan
• The treatment matches the diagnosis

Automated reviews allow insurers to screen large volumes of claims data efficiently as well as flag complex claims for further review.

Step 3: Manual Review

In this stage, an expert, such as a claims adjuster, examines flagged claims more closely. Typically, these professionals may:

• Check whether the treatment and standard medical practices match
• Assess the medical necessity of the treatment provided
• Request for additional information from the provider

Step 4: Payment Determination

The penultimate step in the adjudication process is when the payer has thoroughly reviewed the claim and now needs to determine the quantum of the amount to be paid. At this stage, the insurer can make one of the following three decisions:

• Approve the claim and pay the amount in full
• Sanction payment of only a part of the claim
• Deny the claim entirely

An important document shared by the insurance company to healthcare providers during this process is an electronic remittance advice (ERA), which contains payment details, including claim adjustments and other payment-related information.

Step 5: Final Disbursement

This is the last stage, where once the amount to be paid has been determined, the insurer disburses the payment to the provider, either fully or partially. In addition to the payment, the payer has to also provide an explanation of benefits (EOB) to the patient. An EOB is a summary of the total charges for the patient’s visit; it is not a bill. The purpose is to help the patient understand what all and how much their health plan covers, and what they will have to pay when they get a bill from their provider.

How AI is Transforming Claims Adjudication

The entry of AI is reshaping the healthcare landscape by incorporating agentic intelligence into every stage of the adjudication process. This is happening because the power of AI goes beyond basic automation of routine, repetitive tasks. More specifically, AI can interpret complex data, apply policy and clinical rules in real time, identify anomalies, filter exceptions, and continuously improve decision-making through machine learning. The outcome is a more accurate and faster claims processing with fewer manual touchpoints, greater payment integrity, and enhanced transparency across every payer-provider transaction.

The benefits of employing advanced AI in healthcare operations are being steadily recognized by healthcare organizations. Even government bodies are actively planning on adopting AI to streamline healthcare workflows and reduce the burden on claim reviewers. As healthcare organizations undertake modernization drives with increasing intensity, claims adjudication will need to evolve from a largely manual, rules-driven process into one orchestrated by AI that makes it faster, more accurate, efficient, and transparent.

Why Modernizing Claims Adjudication Is No Longer Optional

Sitting at the heart of healthcare operations, claims adjudication is one of the industry's most complex and resource-intensive processes. Every claim review involves a comprehensive evaluation of several factors conducted across disconnected systems and multiple data sources. With healthcare insurers processing over 5 billion claims annually in the U.S., traditional rule-based and manual workflows are struggling to keep pace. Insurance companies are under tremendous pressure due to membership losses, rising medical costs, and regulatory changes. To maintain their bottomline, insurers will need to fast-track the adoption of AI-native platforms such as HealthAxis to orchestrate backend operations and optimized pricing models. In practice, this translates to automation of claims processing, predictive analytics for risk adjustment, and machine learning to detect fraud.

Frequently Asked Questions

Q: What is claims adjudication in healthcare?

Claims adjudication is a process conducted by a health insurance company to review a medical claim and determine whether the services rendered by the provider are covered under the member's health plan, validate the completeness and accuracy of the claim, and decide the quantum of amount to be reimbursed.

Q: What are the key steps involved in the claims adjudication process?

The process typically undergoes an initial review, followed by an automated review where exceptions are flagged for manual review, payment determination, and the final payment. The last step also involves the issuance of an electronic remittance advice (ERA) to the provider and an explanation of benefits (EOB) to the patient.

Q: Why are medical claims denied?

Common reasons why claims are denied include incorrect or incomplete patient information, coding errors, lack of medical necessity, missing prior authorization, duplicate submissions, non-covered services, or late filing.

Q: How does AI improve claims adjudication?

AI enhances claims adjudication by automating routine work, identifying coding errors and anomalies, and detecting fraudulent activities. It can also capture essential information from unstructured data and analyze it and filter claims that require manual review.

Q: How can AI-powered claims adjudication benefit payers?

AI can help payers optimize their operations by accelerating claims processing, improving payment accuracy, strengthening fraud detection, and enhancing regulatory compliance.