Exponential AI

From the initial request intake 📥 to the final authorization decision 🆗, 🧠 AI can transform or simplify every step of the prior auth process: 📠 Digitize PA requests. 🤖 Automate data checks. 🚫 Predict potential voids. ⏩ Flag cases for manual review. The result? Smarter, faster, and more efficient Prior Auth approvals! 🚀📈 #ExponentialAI #PriorAuthorization #RealtimeAI #Automation #PreAuthorization #UtilizationManagement #HealthcareAI

🌐 IBM Z Day is back! Mark your calendars for the 1-day virtual conference on Oct. 1st. Discover AI on a highly trustworthy and secure enterprise system and dive into the future of technology. Don’t wait, register now:  ibm.biz/ibmzday-2024 #ibmzday #ai #exponentialai #generativeAI #IBMHyperprotect

Join us at IBM Z Day on October 1st! Hear from industry leaders across the board — from startups to Fortune 500s. Follow the #StartupJourney to see how businesses are leveraging IBM Z and LinuxONE. We'll be presenting on #AI and how we're transforming healthcare claims. Don't miss it! Register now: https://lnkd.in/gHhF9AB5 Want to learn more about Exponential AI on LinuxONE? Reach out! #healthinsurance #IBMZ #IBMZDay #healthcare

Every fourth claim failing auto-adjudication is linked to errors in provider data. While provider data quality issues can arise from various sources, addressing specific areas like errors and delays in provider contract loading can have a significant impact. Our AI solution focuses on extracting accurate demographic information, including providers' fee schedules, services covered, locations, and license/credential status, ensuring no errors exist in provider information. This precision helps: •⁠ ⁠Reduce Claims Errors & Overpayments: Ensuring accurate provider information in claims, whether specialties or fees, minimizes errors and saves you money. •⁠ ⁠Enhance Compliance: Prevents costly penalties from CMS and state agencies for directory inaccuracies. •⁠ ⁠Improve Member Satisfaction: Reliable information on in-network providers avoids surprise billing and builds trust. Clean provider data also indirectly boosts risk adjustment revenue. It fosters better collaboration between your plan and providers, freeing up time for more accurate clinical documentation and coding. This ultimately leads to richer data for risk adjustment. Poor provider data costs you money. Leverage AI to improve your health plan efficiency, member experience, and ultimately, bottom line.

In today’s complex healthcare landscape, AI is transforming COB management by addressing some of the most persistent challenges. 3 COB Challenges AI can Solve  1. Subpar Yield More than 50% of COB issues are never identified leading to financial leakage and reactive processes leading to inefficient “pay-and-chase”. 2. High Cost of Recovery It takes 5x longer to settle a COB claim and vendor dependent model relies on contingency payments that make the cost of recovery exorbitant. 3. Lack of Automation Nearly 5% of claims need COB adjustments and the lack of integration between internal teams and systems lead to manual processes and handoffs with no visibility & traceability. By leveraging AI, health plans can overcome these challenges, enhancing efficiency, accuracy, and financial outcomes in COB management.

Prevent Claims Leakage with AI-driven Prepay Audits As #healthcare gets more complex, audit teams are getting bogged down investigating #falsepositives rather than focusing on actual #claims paid in error. AI audit can augment manual audit and help audit leaders run tighter #operations more focused on complex and emerging patterns of errors. 4 Key Ways AI Improves the Manual Audit Process: Increases efficiency and reduces false positives: Allowing #auditors to focus on what really matters. Uncovers deeper and broader payment issues: Detecting issues that existing systems may miss. Detects payment errors in prepayment: Reducing leakage and costly pay-and-chase efforts. Improves quality and speed of feedback: Enhancing communication with PI and claims processing units. #AI #Healthcare #Audit #ClaimsProcessing #Automation #HealthcareTechnology #Efficiency #Innovation #CostSavings

3 Key COB Decisions AI Can Automate  🔍 Accurately identifies coordination of benefits scenarios.  🔀 Automates the determination of primary versus secondary coverage.  💡 Assigns appropriate reason codes for claims adjustments. #benefitscoordination #PayerAI #healthcare #healthtech

🇮🇳 Exponential AI wishes everyone a #HappyIndependenceDay!

Denials impact nearly 20% of claims, and can lead to nearly 5% loss in Net Patient Revenue. Manual processes and constantly changing payer rules make it difficult to prevent them. AI can transform denial management by predicting denials and identifying root causes. It increases clean claim submissions, improving revenue cycle processes and financial performance for providers.

Current prior authorization (PA) processes are time-consuming and labor-intensive. The push for automating prior authorization is driven by the need to improve response times, reduce manual effort and costs for providers and patients, and lower overhead for payers. An AI-based prior authorization solution can significantly reduce the manual work involved in documentation gathering, data extraction, request adjudication, and status communication. This reduces avoidable denials, procedure cancellations, and care delays, leading to better patient outcomes and increased staff productivity.