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The MongoDB Innovation Awards celebrate organizations building the world’s most innovative applications, recognizing those with a transformative impact on their respective sectors. Recently, Experian Health was recognized for our innovation in healthcare. Our Universal Identity Manager (UIM), which integrates with MongoDB to accurately sequence patient data, can accurately match, manage and protect patient identity. Drawing on more than 40 years of experience managing identities across various industries, Experian Health’s interoperable patient identification solution leverages consumer credit data to improve record quality. Our UIM creates a unique, universal patient identifier to identify patients and link their records to allow entities (pharmacy, lab, payer, and provider) with disparate databases, systems, and data formats to share a single view of the same patient. Accurate and complete information is securely exchanged, minimizing medical and billing errors, and fraud. “We leverage MongoDB to deliver UIM information in real-time – and that makes performance critical,” said Michael Ochs, chief technology officer of Experian Health. “If patient data is delivered out of sequence, it can create multiple issues in the delivery and accuracy of patient information. This technology makes the interoperability and exchange of information across the healthcare ecosystem is an achievable goal. With UIM, it is possible to successfully address problems caused by data integration challenges and fluid patient data.” Our consumer demographic information combined with reference data and referential matching methodologies allow the UIM to achieve higher matching rates and mitigate matching challenges associated with data quality. “We encourage health organizations to adopt universal patient identifiers because there is a well-documented need for it – the absence of which poses both business and safety issues,” said Jennifer Schulz, group president of Experian Health. “Our UIM batch product is being offered to organizations at no charge* to provide a universal patient identifier that will help address the complexities of managing patient identification by identifying consumers in the healthcare ecosystem more accurately.” Michael accepted the award on behalf of Experian Health at the annual MongoDB World event in Chicago on June 21, where he joined 13 other innovative companies being awarded in different categories. This award for Experian Health comes shortly after being recognized in the healthcare industry by Healthcare Informatics as no. 45 on the list of “Top 100 Companies by Revenue.” *Offer is limited to Experian Health’s UIM Batch Process product and shall remain open for such time as Experian Health may decide.

Reimbursement pressures and the real potential of changing regulations require that revenue cycle leaders leverage data and technology to be as efficient and nimble as possible to maximize net revenue, reduce denials, and lower operating costs. Shifting reimbursement models, complex benefit designs and limitations, increased patient responsibility, and growing regulatory pressures are driving near-constant change in the healthcare revenue cycle. Healthcare organizations that used to be paid by the encounter are adapting to emerging trends of also being selected, measured, and paid for how they perform and collaborate with other providers to improve outcomes. This value versus volume movement has forced hospitals, physicians, and other providers to focus on delivering high-quality, collaborative care at a lower cost while enhancing the patient experience, including efficiency and patient sensitivity in the revenue cycle. Experian Health’s Revenue Cycle Analytics provides visibility across the revenue cycle continuum, transforming operational and financial information into actionable insights. By tapping into Experian Health’s vast product workflow data and revenue cycle transactions, you can hone in to optimize specific workflows and compare your facility’s operations and processes against industry peers to make more informed business outcomes. Relevant data is presented for users based on responsibilities. With your internal data, we can Improve your workflows, operational performance, and financial results by leveraging your data across the revenue cycle, matching it, and analyzing the account across the various revenue cycle workflows and transactions Ensure accurate reimbursement by analyzing workflows and optimizing activities Create and monitor revenue cycle KPIs around pre-service, point-of-service, post service, denials, etc. to provide data points needed for process and financial optimization Provide comparative analysis and benchmarking that scores payer performance based on claim, rejections, denials, and exceptions Identify trends by drilling down to the staff, department, and service levels to uncover insightful details Maximize return on investment in Experian Health revenue cycle management products Enable the calculations of HFMA Map Keys and NAHAM Access keys for true peer-to-peer benchmarking With decades of Big Data experience, and as experts in gathering and securely managing huge quantities of data, Experian Health’s Revenue Cycle Analytics manages an unrivalled breadth and depth of data to help clients gain a deep understanding of people, businesses, places, economics, and health.  

Yale New Haven Health (YNHH) established a goal to elevate the patient financial experience by compassionately educating patients about the finances surrounding their care, and educating staff on the tools and methods for delivering that message. YNHH embarked on a two-year patient financial advisory initiative, including patient and family advisors, to hear opinions and learn valuable information directly from consumers. According to Sharlene Seidman, Executive Director Corporate Business Services, with Yale New Haven Health: “We needed a consumer-focused price transparency strategy that would bring us on par with other industries, like retail. Our goal was that when patients discuss their overall YNHH experience, it is not just reflective of their clinical care, but their financial care as well.” Since going live with Eligibility and the Epic integration in May 2016, YNHH has made major strides toward meeting its pre-service excellence goals in four key areas 1) the right technology, 2) best practices, 3) patient interaction/engagement, and 4) employee culture and education. Read the full case study here

Key takeaways: Revenue cycle teams can use automation to reduce repetitive work and apply AI where data-driven prediction, matching or prioritization can improve a workflow. Experian Health’s 2025 State of Claims survey found that 41% of providers now face denial rates of 10% or higher, while 68% say submitting clean claims is more challenging than a year ago. Patient Access Curator™ (PAC) uses AI to support front-end data validation and insurance discovery, while AI Advantage™ helps teams predict denial risk and prioritize denial follow-up. Artificial intelligence (AI) and automation can support administrative work in healthcare. In the revenue cycle, teams depend on accurate information, timely decisions and efficient follow-up to keep claims moving. In revenue cycle management, AI and automation can help organizations reduce manual checks, find data gaps, predict denial risk and prioritize work queues. These tools are most useful when they support staff judgment, payer expertise and compliance oversight. They can handle repetitive, data-heavy tasks so staff can focus on exceptions and decisions that need human review. In 2023, McKinsey & Company reported that research suggests effectively deploying automation and analytics could eliminate $200 billion to $360 billion of spending in U.S. healthcare. For revenue cycle leaders, the practical question is where to apply those capabilities first. The case for applying AI and automation in healthcare Revenue cycle teams juggle many daily tasks. Staff collect and verify patient information, confirm eligibility, identify the right payer, submit clean claims, monitor status, work denials and manage collections. Small data gaps at the beginning of the process can create downstream rework and delays. Rework also consumes staff time, adding to these operational pressures. As costs rise and revenue cycles tighten, there is increasing pressure to do more with less. Experian Health’s 2025 State of Claims survey found that 54% of providers say claim errors are increasing and 90% of claim denials are reworked with at least some human review before resubmission. Providers are also managing broader financial and administrative pressures. The American Hospital Association has reported that prior authorization requirements, claim audits, denials and other payer policies add administrative burden and cost for hospitals and health systems. These requirements also consume staff time to appeal denials and manage payer processes. AI and automation are different but complementary. Automation follows defined rules to complete repeatable work. AI models can identify patterns in data, predict risk and help teams decide where to focus attention. When used together, they can support more consistent revenue cycle workflows. How AI and automation can support revenue cycle workflows Revenue cycle management automation and AI are most useful when tied to a specific workflow and a measurable operational problem. The goal is to help teams act earlier, reduce avoidable rework and focus staff time where judgment is needed most. For example, automation can complete rule-based eligibility checks. AI can help identify claims with a higher likelihood of denial. In insurance discovery workflows, AI can also help identify coverage that wasn’t captured at registration. When these tools fit into existing workflows, they can support more consistent decisions and reduce manual work. Three practical applications include: 1. Improving front-end data quality with Patient Access Curator Patient and coverage information collected early in the revenue cycle can affect downstream claim outcomes. Incomplete or outdated demographic details, eligibility responses, coordination of benefits or Medicare Beneficiary Identifier information can create problems that lead to claim delays or denials later in the cycle. Experian Health’s Patient Access Curator helps prevent claim denials by validating demographics, eligibility, insurance discovery, coordination of benefits and Medicare Beneficiary Identifier data in seconds. PAC’s AI and machine learning capabilities help improve match accuracy, coverage sequencing and data confidence by writing the validated data back into the host system and sequencing payers before the claim is created. This automates work that would otherwise require manual coverage checks. 2. Using insurance discovery to find coverage not captured at registration When active coverage isn’t identified during registration, claims may be delayed or submitted with incomplete insurance information. Insurance discovery looks for coverage that may not have been captured during registration. Patient Access Curator includes insurance discovery as part of its front-end validation workflow. It can help identify and correct missing or incorrect insurance information so claims can be submitted with more complete coverage data. 3. Using AI to prevent and prioritize denials Even with strong front-end processes, some claims still require additional attention. AI can help claims teams decide which claims to review before submission and which denials to work first after payer response. Experian Health’s AI Advantage supports two denial management use cases:1. AI Advantage – Predictive Denials uses a client’s historical claims data and Experian’s knowledge of payer rules to identify claims with a high likelihood of denial before submission so teams can take corrective action.2. AI Advantage – Denial Triage uses AI to segment denials and identify those with the highest potential for reimbursement. This approach can help teams prioritize with more confidence. Rather than treating every claim or denial the same way, teams can use predictive models to focus on the work that needs the most attention. Potential benefits of AI and automation in the revenue cycle A high-performing revenue cycle depends on timely, accurate and consistent work. AI and automation can help providers modernize that work without losing the expertise of the people who manage complex payer and patient situations every day. When applied to the right workflows, these tools can help organizations: Reduce manual data searches that take staff away from higher-value work Improve front-end data quality before claims are created Identify missing or incorrect coverage information earlier Spot claims that may be at higher risk of denial Prioritize denied claims by potential reimbursement Reduce rework caused by inaccurate or incomplete information Give staff more consistent information for follow-up decisions A focused AI strategy starts with the workflow problem, uses data that is relevant to that problem and keeps staff in control of judgment-based decisions. A more proactive approach to revenue cycle management Revenue cycle teams can move from reactive work toward a more proactive approach: catch errors earlier, validate coverage before claims are created and prioritize the claims and denials that need the most attention. Experian Health offers revenue cycle solutions that use AI and automation in targeted ways to support front-end data quality, reduce rework and manage denials. Patient Access Curator supports registration and coverage validation, while AI Advantage supports denial prediction and triage. Learn more about Experian Health’s Patient Access Curator and AI Advantage.

Experian Health is very pleased to announce that we’ve ranked #1 in the 2025 Best in KLAS: Software & Services report, for our Contract Manager and Contract Analysis product, for the third consecutive year. Contract Manager, when paired with Contract Analysis, empowers healthcare providers by ensuring payers comply with contract terms, identifying and recovering underpayments, and arming them with real claims data to negotiate contracts. This enables providers to negotiate more favorable terms and maintain financial stability.  Clarissa Riggins, Chief Product Officer at Experian Health, says, “In the ever-evolving healthcare landscape, our Contract Manager solution has once again been recognized as the #1 Revenue Cycle Management tool by KLAS for the third consecutive year. This prestigious ranking underscores the significant value our solution delivers to our clients by identifying underpayments and facilitating revenue recovery. We are honored to continue supporting our clients with innovative solutions that drive financial success and operational efficiency.”  Learn more about how Contract Manager and Contract Analysis can help your healthcare organization validate reimbursement accuracy, recover underpayments and boost revenue.   Learn more Contact us

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