Automate patient financial assistance screening to reduce bad debt

by Experian Health 5 min read April 17, 2024

dfgdfg

A recent Peterson-KFF brief found that around 20 million adults have unpaid medical bills, with 14 million owing at least $1,000. Data from the Survey of Income and Program Participation puts the total figure at more than $220 billion. Healthcare providers must find ways to streamline patient financial assistance screening, to help patients and prevent unpaid bills piling up from uncompensated care. Many patients who would be eligible for financial assistance miss out on much-needed discounts due to outdated screening processes, leaving their unpaid bills to linger in accounts receivable.

Automated presumptive charity screening offers a cost-effective solution for healthcare providers to modernize the process and reduce avoidable write-offs. Patient financial assistance software can also aid providers in fostering compassionate patient experiences, by identifying individuals in need of help and efficiently guiding them towards appropriate financial assistance pathways.

The hidden consequences of medical debt

Rising costs, unexpected medical emergencies and lack of insurance are the main culprits in the growing problem of medical debt. Though uninsured rates have dropped, millions of insured Americans remain without adequate coverage: high deductibles and co-payments leave many individuals “underinsured” with out-of-pocket costs they cannot afford. Providers end up shouldering the costs, leading to revenue loss, operational strain, and impaired capacity to deliver high-quality care.

In some cases, the burden of an individual’s medical debt may be initially concealed from the health system, papered over with credit card bills and loans. But it does not remain hidden for long: medical debt becomes simply “debt,” as families cut back on food and clothing, fall behind on other household bills, or even declare bankruptcy. The repercussions can escalate for patients and providers as patients opt out of further care, which eventually causes their medical needs – and costs – to spiral. Creating a more compassionate financial experience for patients will help avoid these ripple effects, with benefits for providers, too.

Who is eligible for patient financial assistance programs?

Patients who cannot afford to pay may be eligible for support via a patient financial assistance program. These programs, offered by providers, charities and government agencies, alleviate the financial pressures on patients by covering some or all of the cost of care in the form of partial or full discounts. Providers can offer patients information and support early in their healthcare journey to help them access such programs. The challenge is figuring out who is eligible.

Eligibility criteria for financial assistance is often complex, covering the individual’s income, household income and size, savings and medical need. Gathering and analyzing this data using manual processes can be time-consuming and often lead to gaps and inaccuracies. These inadequate screening processes result in missed opportunities to connect patients with the financial assistance they need, and risk falling foul of charity care regulations and policies.

On-demand webinar: Hear how Eskenazi Health boosted Medicaid charity approvals by 111% with financial aid automation.

How to use data to identify patients eligible for financial assistance

Instead of asking the patient to fill out a stack of forms and manually checking data against the Federal Poverty Level to determine eligibility for charity care, providers can get the answers they need using data analytics and automation.

Patient Financial Clearance automates eligibility checks prior to service to see if patients qualify for financial assistance programs. It uses Experian data and analytics to predict the patient’s ability to pay and calculate the best-fit payment plan based on individual needs and circumstances. It also generates scripts for staff to use when running the tool and helping patients find assistance, which makes for a more compassionate experience.

Alex Liao, Product Manager for Patient Financial Clearance at Experian Health, says, “Many patients are unaware that they’re even eligible for financial assistance and need help to navigate the process. Discussing personal finances can also be uncomfortable, so it’s not uncommon for patients to avoid sharing information that could actually lead to them getting support. Automating presumptive charity screening is more efficient and reliable. It’s also a lot more compassionate than the old way of collecting forms and documents. Patient Financial Clearance pulls together credit information and demographic data to determine whether the patient qualifies without long, drawn-out discussions. Patients get the help they need and providers can reduce bad debt without delay.”

Case study: Discover How UCHealth wrote off $26 million in charity care with Patient Financial Clearance.

Using patient financial assistance technology to create compassionate patient experiences

As Liao notes, many patients feel awkward or hesitant when discussing their financial situation with a stranger. Additionally, patients are increasingly looking for digital channels to handle their administrative tasks. Experian Health’s Self-Service Patient Financial Clearance option offers patients a simple and more private way to complete eligibility checks, whenever and wherever it suits them. Using a mobile and web-based platform, patients can fill out screening forms and upload supporting documents, then get real-time status updates without having to call up their providers. Information is stored securely so staff can check application status as needed.

self-service patient financial clearance

How Self-Service Patient Financial Clearance works

Self-Service Patient Financial Clearance puts patients in control, so more individuals complete their applications and find out if they’re eligible for financial assistance. This frees up staff to focus on other revenue-generating tasks that require their attention. With a cost-effective, compassionate and convenient option on the table, is it time to say goodbye to paper-based presumptive charity checks?

Find out more about how Patient Financial Clearance helps providers reduce bad debt and improve the patient experience by quickly and correctly checking eligibility for charity care.

Related Posts

Andy’s New WP Workflow Test Article Using Quick Edit

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.

October 2, 2026 by Andy.Monte@experian.com
Experian Health ranked #1 in Best in KLAS for 2025

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

February 5, 2025 by kelly.nguyen
How to increase patient engagement

Learn how providers can increase patient engagement, why it matters and key strategies that deliver improved end-to-end patient experiences.

January 30, 2025 by Experian Health

Spotlight test

Spotlight Description

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Sticky Subscribe Title

Sticky Subscribe Description
Sticky Subscribe

Testing Spotlight Paragraph block

Testing the spotlight block header

Archive Testing

Categories