System for automated pricing and claims assessment in the healthcare sector

Abstract

System for automated pricing and claims assessment in the healthcare sector, consisting of: a module for capturing claim data that receives electronic claims with patient, provider, diagnosis, procedure and billing details; a data validation module that checks claims based on standardized coding systems and rules of the cost bearers; a module for pricing and decision-making that applies reimbursement policies, contracts and legal regulations; a fraud detection module that uses AI and ML to identify duplicate claims, billing anomalies, and fraud risks; an interoperability layer that ensures seamless integration with EHR, payer systems and regulatory databases; a claims tracking system that provides real-time status updates and notifications about the decision; a payment processing module that automates invoicing, generates EOBs and facilitates dispute resolution.

Description

[0001] The present invention relates to a field of automated healthcare claims processing, and more particularly to a system for automated healthcare claims pricing and assessment.

[0002] Healthcare claims processing is a critical function in the healthcare industry, ensuring that medical services provided to patients are accurately billed and reimbursed by insurance companies. Traditionally, pricing and claims processing involve multiple manual steps, including data review, coding validation, policy compliance verification, and payment calculation. These manual processes are often time-consuming, error-prone, and prone to fraud, leading to reimbursement delays and financial inefficiencies for healthcare providers and payers.

[0003] One of the biggest challenges in traditional claims management is the complexity of medical billing systems. Healthcare claims must adhere to various industry standards, including the International Classification of Diseases (ICD), Current Procedural Terminology (CPT), and the Healthcare Common Procedure Coding System (HCPCS). Furthermore, different payers have different contract terms, pricing models, and reimbursement policies, making it difficult for healthcare providers to accurately predict the outcomes of their claims.

[0004] Another key issue in claims processing is the detection of fraudulent claims and billing errors. Fraudulent or inaccurate claims can result in financial losses for insurance companies and higher costs for patients. Current fraud detection methods rely on after-the-fact audits and manual reviews, which are inefficient and may not detect fraudulent activity in real time. With advances in automation, artificial intelligence (AI), and machine learning, there is an opportunity to improve pricing and claims assessment through the use of technology. An automated system can analyze claims data in real time, apply insurer-specific rules, and detect discrepancies or fraudulent claims before payments are processed.

[0005] To solve this problem, the present invention provides a system for automated healthcare pricing and claims assessment.

[0006] The system streamlines medical claims evaluation by applying predefined rules, payer policies, and pricing models to ensure accurate and efficient claims processing.

[0007] The system minimizes human involvement, reduces administrative costs, and improves lead times in claims processing.

[0008] The system integrates with various healthcare coding standards such as ICD, CPT, and HCPCS, while aligning with payer-specific policies, legal requirements, and contract terms to ensure compliance with industry standards.

[0009] The system uses real-time data validation, historical claim analysis, and machine learning algorithms to eliminate pricing errors and discrepancies, preventing overpayments and underpayments.

[0010] The system identifies anomalies, potential fraud and billing discrepancies, improves financial integrity and reduces losses for insurance providers.

[0011] The system is designed to integrate seamlessly with electronic health records (EHR), medical billing software, and payer networks, ensuring seamless data exchange and reducing information silos.

[0012] The system ensures timely reimbursements to healthcare providers and improves financial stability and cash flow management.

[0013] In one embodiment, a system for automated healthcare claims pricing and adjudication is provided. The system automates the evaluation, pricing, and adjudication of medical claims by integrating rule-based engines, artificial intelligence (AI), machine learning (ML), and real-time data validation to ensure accuracy, efficiency, and compliance with payer policies. The system is designed to receive claims data from healthcare providers, validate the information against industry-standard coding systems such as ICD, CPT, and HCPCS, and apply predefined pricing models and plan-specific rules to determine reimbursement eligibility. It performs a real-time assessment by analyzing medical necessity, benefit coverage, contractual agreements, and potential fraud or billing discrepancies.

[0014] In one embodiment, the system increases operational efficiency, reduces administrative costs, minimizes errors, accelerates reimbursements, and improves overall transparency in healthcare claims processing.

[0015] In one embodiment, the system offers a scalable and intelligent solution for healthcare payers and providers that ultimately optimizes financial outcomes and ensures fair and accurate claims assessment.

[0016] The invention is explained again below with reference to the figure. It shows: Fig. : a block diagram of a system for automated healthcare pricing and claims assessment.

[0017] Fig.shows a block diagram of a system for automated healthcare claims pricing and adjudication. The system consists of several interconnected modules that work seamlessly together to process healthcare claims. The Claims Data Intake module receives claims submitted by providers, clearinghouses, or electronic health records (EHRs). This data includes patient demographics, provider information, diagnosis codes, procedure codes, and cost breakdowns. Once received, claims are processed by the data validation engine, which ensures completeness and accuracy by verifying the information against standard coding systems such as ICD, CPT, and HCPCS. This validation step is critical to preventing claims from being rejected due to missing or inaccurate information.

[0018] After validation, claims are processed by the Pricing and Adjudication Engine, which applies predefined pricing models, insurer-specific policies, contract terms, and reimbursement guidelines. The AI-driven engine decides whether a claim should be approved, rejected, or modified based on the evaluation rules. Furthermore, the Fraud Detection and Anomaly Identification module uses predictive analytics and machine learning to identify suspicious billing patterns, duplicate claims, and potentially fraudulent activity before payment is approved. This proactive approach reduces financial losses for payers while ensuring that legitimate claims are processed expeditiously.

[0019] The system includes an interoperability and integration layer that enables communication with EHR systems, medical billing platforms, insurance databases, and government healthcare portals. This integration ensures real-time updates and regulatory compliance. The Claims Status Tracking and Notification System increases transparency by enabling providers and payers to monitor claim status in real time, receive automatic notifications, and quickly resolve disputes. The system follows a structured claims processing workflow that includes several automated steps. Providers submit their claims through an integrated interface, after which the system validates the data, applies appropriate pricing models, and assesses the claim based on plan-specific rules.The AI-controlled fraud detection mechanism checks the claim for irregularities before approval. After processing, the claim is either approved and forwarded for payment or rejected with detailed explanations for any necessary corrections. Real-time status tracking ensures that providers remain informed throughout the process, enabling timely resubmission or appeals if necessary.

[0020] The system includes real-time assessment, which significantly reduces processing times and improves reimbursement cycles. AI-based accuracy enhancements ensure that pricing models remain up-to-date and error-free, minimizing claim rejections due to incorrect calculations. Furthermore, fraud detection and cost containment mechanisms protect against financial loss while promoting regulatory compliance. The system's seamless integration and interoperability with existing healthcare IT infrastructures enables efficient data exchange, eliminating redundancies and streamlining processes. By automating healthcare claims pricing and assessment, this system minimizes administrative burden, improves financial transparency, and ensures accurate and timely claims billing.It provides a scalable and intelligent solution for healthcare payers and providers, optimizing financial and operational efficiency across the entire ecosystem. List of reference symbols 100 systems

Claims

[1] System for automated pricing and assessment of healthcare claims, consisting of: a claims data capture module that receives electronic claims containing patient, provider, diagnosis, procedure, and billing details; a data validation module that checks claims against standardized coding systems and payer rules; a pricing and decision-making module that applies reimbursement policies, contracts, and regulatory requirements; a fraud detection module that uses AI and ML to identify duplicate claims, billing anomalies, and fraud risks; an interoperability layer that ensures seamless integration with EHR, payer systems, and regulatory databases; a claims tracking system that provides real-time status updates and decision notifications; a payment processing module that automates billing, generates EOBs, and facilitates dispute resolution. [2] The system (100) of claim 1, wherein the pricing and decision-making module dynamically adjusts pricing for claims based on provider contracts, negotiated rates, and government reimbursement plans. [3] The system (100) of claim 1, wherein the interoperability layer supports secure data exchange via FHIR (Fast Healthcare Interoperability Resources) and HL7 (Health Level 7) standards [4] The system (100) of claim 1, wherein the claim tracking system generates automatic notifications for claim status updates, denial reasons, and required corrections. [5] The system (100) of claim 1, wherein the payment processing module is integrated with banking networks and electronic funds transfer (EFT) systems to automate the payment of claims [6] The system (100) of claim 1, wherein the fraud detection module flags high-risk claims for manual review prior to final decision. [7] The system (100) of claim 1, wherein the pricing and adjudication module considers medical necessity, prior authorization requirements, and bundled payment models in determining claim outcomes. [8] The system (100) of claim 1, wherein the data validation engine verifies authorization in real time by querying insurance databases. [9] The system (100) of claim 1, wherein the data validation engine compares claims with historical claim data and payer-specific policies to identify missing or inconsistent information.

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