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Thanks to the global pandemic, providers were forced to re-imagine how healthcare is delivered beyond the four walls of a physical care setting. As they closed their doors to non-emergency and elective care, a massive shift in innovation, acceleration and adoption of patient engagement technology occurred, serving as a much-needed catalyst for digital transformation.     As industries like retail, banking, food, and airlines embrace digital experiences, healthcare should be no exception. The renewed focus on a digital front door strategy allows patients the flexibility, personalization and convenience they’ve grown accustomed to. It’s the beginning of a new age in healthcare where quality patient information is fundamental to delivering and exceeding patient expectations.   The New Age of Patient Information Patient identity is the backbone of everything in healthcare, providing the fuel for healthcare consumerization and the keys to the digital front door. As organizations focus on improving the patient experience, enabling patient access, and measuring and reporting performance, a patient identity strategy is core to enabling these enterprise-wide initiatives.   As patients seek care across multiple settings, both in-person and virtual, care coordination challenges increase without a single view of the same patient. Enter patient identification—paramount to ensuring patients receive safe, accurate, and personalized care. According to one estimate, matching within facilities can be as low as 80% — meaning that 1 out of every 5 patients may not be matched to all his or her records when seeking care at a location they’ve already received care from in the past.   The vision of an integrated, interoperable healthcare ecosystem starts with consistently and correctly linking disparate clinical and non-clinical data across silos to generate the single best, most accurate patient record. Having and maintaining a single, accurate view of the patient — the “golden record” — is critical to close gaps in care at the individual level, address patient safety concerns and revenue leakage associated with incorrect patient matching.   The vision of an integrated, interoperable healthcare ecosystem starts with consistently and correctly linking disparate clinical and non-clinical data to a single person. In AHIMA’s 2020 Patient Identification Survey, 22% of respondents reported they achieved a 1% or less duplicate error rate in their electronic health record (EHR). How does an organization successfully get there? It starts with resolution, enrichment and protection — the three pillars of identity management that are foundational to achieve the most accurate, comprehensive and secure view of today’s healthcare consumer.   Resolution – Confidently identify and match patient records & ensure accurate patient demographic data Enrichment – Update and enhance patient information for the most current, accurate, holistic patient view Protection – Authenticate a patient identity before sharing sensitive information     Enabling Digital Transformation Patient identity management can prevent medical identity theft, optimize the revenue cycle, reduce denied claims, prevent duplicate record creation and enhance patient safety – leading to improved financials and boosting bottom lines in the process. In today’s vastly connected world, consumers expect a seamless patient experience based on accurate and secure data. If other industries have long accomplished this undertaking, why not healthcare? In the New Age of Patient Information — a single, best patient view is required. Download our latest guide to understand where your organization stands within the three pillars of patient identity management and how to develop a roadmap for ensuring you have the most accurate, comprehensive and secure view of today’s healthcare consumer.  

Collections were tough even before COVID-19 hit. Provider’s bottom lines were already strained, and the high-deductible trend continued, putting patients on the hook for a bigger chunk of their medical bills.   A highly volatile – but improving – employment environment hasn’t helped, and some patients’ ability to pay hasn’t kept pace with their growing financial responsibilities. Many have new health plans, lapsed coverage or are more focused on other debts, making collections even less predictable. Providers may also feel that payer policy changes haven’t made recouping lost pandemic revenue any easier, with some losing two whole business days per week to completing prior authorizations. It’s no wonder that nearly one in five providers have overhauled their patient collections strategy in the last year.   Now, after a year of the pandemic’s impact on revenue, three dominant trends continue in this space: rising patient balances, an accelerated move toward innovative payment experiences that are moving toward digital engagement as a preferred option to paper or “payment at the counter,” and a realization that compassion is a key factor in solving this challenge.   Avoiding new pitfalls in patient collections   Go-to strategies for improving patient collections before the pandemic might have only included offering more patient payment options, doing more to check for missing coverage, or focusing efforts on patients who are most likely to pay. These are sensible options but, if implemented poorly, they’re more of a band-aid than a cure. Some shortcomings include:   Models relying on historical payment data don’t show the full picture Providers know that focusing their collections efforts on patients who are most likely to pay is the most efficient approach. But determining a patient’s ability to pay on historical payment data alone is likely to be unreliable.   Experian Health’s research suggests that when a collections model relies on historical data alone, around 50% of accounts end up being worked on the basis of no data at all. New accounts are assigned to a “highly likely to pay” segment, whether or not that reflects the reality of their situation. This model costs four times more than utilizing Experian Health’s Collections Optimization Manager, which can predict the ability of patients to pay, even without historical payment, by using multiple data sources.   Collections based on limited data will require more resources to work more accounts, but which ultimately will collect the same as collections based on multiple data sources.   Beware of artificial claims about artificial intelligence To streamline workflows and avoid losing staff hours to inefficient processes, many providers are turning to automated patient collection solutions. Artificial intelligence in healthcare is an exciting prospect, but not all solutions are what they seem.   Matt Baltzer, Product Director at Experian Health, says:   “Many collections tools claim to use artificial intelligence when they’re really using basic automations based on incomplete data. Since the quality of the output is only as good as the data that’s put in, the insights generated by these tools will be severely limited.”   To solve the collections workflow challenge, providers need an end-to-end strategy that integrates multiple high quality data sources, intelligent analytics and a responsive platform that learns and adapts in order to prioritize patients and communicate with them in a way that makes collections easier. Cash payments and price transparency can be part of, but not all of, the solution One way to smooth out a bumpy revenue cycle is to offer discounts to patients who pay in cash. It saves on admin costs and guarantees at least some of the bill will be paid. While this makes sense for minor ailments, admin and treatment costs for chronic conditions and major medical events remain persistently high. A resilient collections strategy needs to work across the board, addressing the many treatments, procedures and care plans that providers deliver and manage every day.   Requirements for improved collections, post-COVID-19 The cohesive, integrated model that providers need has the following key elements:   Multi-data sources for comprehensive analysis Optimal collections modeling uses different sources of data to build a more reliable prediction about a patient’s ability to pay. Combining credit data, behavioral modeling and socio-economic insights can help providers better understand their patients’ financial situation and group them accordingly – quickly and accurately.   Convenience and clarity for patients and staff Automated workflows with easy-to-use interfaces will make collections easier for staff, and eliminate time-wasting manual tasks. At the same time, a smoother, more targeted collections process means staff can engage with patients on the basis of accurate information, with fewer (and less stressful) calls and emails.   Advanced data analytics and automation for fewer errors and denials In-depth data analytics allow providers to screen and segment patients quickly to help prioritize accounts by payment probability, to achieve a higher rate of collections. A tool such as Collections Optimization Manager will evaluate collection performance in real-time, to help providers forecast patient payments and avoid bad debt. Expert consultancy support to stay on top of industry trends With the payments landscape in constant flux, having an expert on hand to help navigate the changes and advise on industry trends is a major asset. Experian Health’s team stands ready to help providers monitor and improve collections with industry insights and best practice strategies.   Find out how Collections Optimization Manger can help your organization avoid patient collections pitfalls and reduce lost revenue in the wake of the pandemic.

Product featured in this article: Coverage Discovery As of the end of March 2021, more than 53 million Americans have been fully vaccinated, allowing for cautious optimism as we prepare for the next phase of the COVID-19 journey. Unfortunately for pharmacists, the vaccination program has compounded many of the challenges of the last 12 months. Shots may be free to patients, but someone has to pay for them – and getting reimbursed is proving to be a major pain. Complicated billing processes, extra billing audits and mountains of extra paperwork, rejected claims and slow payments are not exclusive to pharmacies helping vaccinate America. With the coronavirus pandemic continuing to muddy the insurance landscape, getting hold of missing dollars is challenging. Healthcare reimbursements haven’t been straightforward for other providers either: widespread coverage loss and uncompensated care is putting extra strain on hospital revenue cycles. With the coronavirus pandemic continuing to muddy the insurance landscape, getting hold of missing dollars is challenging. Providers must find ways to quickly and accurately determine each patient’s coverage status to minimize bad debt. Navigating the complex world of post-COVID healthcare coverage What does the reimbursement landscape look like, one year on? After a long wait, elective procedures are back. But the surge in patient volumes means providers must be on their toes to keep track of coverage. The process for doing so must be streamlined and precise. Ramping up capacity to verify and check coverage without burdensome paperwork is a must. Patient intake is under pressure. More patients are coming through the doors as a result of elective services and vaccination programs (though not always to their usual facility). COVID-19 hasn’t gone away, and with pockets of infection spikes, safety remains a top priority. Capturing adequate insurance information in this context is no mean feat. Running automated coverage checks as soon as the patient arrives will minimize face-to-face contact during admissions and avoid delays. Patient access and collections staff are overburdened. Manual checks are difficult when staff are operating remotely or in a socially distanced environment, and patient information might be incomplete. Automated self-pay scrubbing can help handle the volume. A tool with built-in reporting can also offer insights on workflow and productivity, to help spot opportunities for quicker claims processing. New digital healthcare technologies aren’t always covered by insurers. Telehealth, a life raft during COVID-19, tends to be covered less often by private insurers, compared to Medicare and Medicaid. Coverage checks must factor this in to avoid errors and wasted time. Providers should opt for tools that sweep for payer updates to telehealth coverage to avoid unnecessary delays or denials. Employment levels may be inching upwards again, but tracking coverage remains a challenge as patients start new jobs with new health plans. In addition, checking for Medicare coverage in the midst of changing codes and protocols is time consuming and confusing. A third-party resource such as Coverage Discovery can look for all coverage options and make sure the right bill goes to the right payer. Find missing dollars with Coverage Discovery Hospitals, pharmacists and other healthcare providers can’t afford to continue losing money at a time when every dollar is needed to prepare for “after COVID-19.” Experian Health’s Coverage Discovery is a proven system for tracking down missing coverage quickly and easily, to avoid unnecessary revenue loss. Using billions of data assets and intelligent confidence scoring, it combs through multiple government and commercial payer accounts to maximize actionable coverage. Staff can trust the outputs and focus their attention where it’s really needed. By making coverage identification more efficient and accurate, it’s a shot in the arm for providers in need of faster reimbursements. Contact us to see how Coverage Discovery can be easily integrated into your revenue cycle, so you can maximize reimbursements over the coming weeks and months.

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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