The Total Economic Impact™ Of Experian Health Patient Access Curator

Reduced Revenue Leakage Due To Decreased COB, Eligibility, And Registration Denials

Evidence and data. Interviewees said that before implementing PAC, eligibility, COB, and registration-related denials were a significant source of revenue leakage because denied claims often required extensive rework and, in some cases, were ultimately written off rather than collected. Interviewees identified coverage, missing insurance coverage, incorrect payer selection, and COB errors as common root causes. They explained that their legacy eligibility platforms primarily validated the insurance information submitted by registrars and provided limited ability to identify inactive coverage, uncover additional insurance, or determine the correct payer order.

With PAC, their organizations automatically identified active and additional coverage, established payer primacy, and updated coverage information before claims were submitted. As a result, interviewees reported fewer eligibility denials related to inactive or incorrect coverage, fewer COB denials caused by inaccurate payer primacy, and fewer registration-related denials stemming from incomplete coverage information. In turn, this reduced preventable denials, improved billing accuracy, and protected revenue at the front end of the revenue cycle rather than relying on downstream denial recovery activities.

• The senior director of revenue cycle at a multiregional health system said: “We knew we had a lot of denials related to terminated insurance, incorrect payers, and COB issues. We needed a way to automatically identify inactive coverage, find the correct payer, and establish the right payer order before claims were submitted. Since implementing PAC and refining our workflows, we’ve achieved a significant reduction across those denial categories.”
  The senior director continued: “Once coverage and payer primacy were being updated automatically, changes made by registrars became the exception and no longer the norm. Previously, staff were more likely to manually update coverage information, but with the correct information already loaded into the system, there was less need to make changes. As teams became more comfortable relying on the automated process, we started to see a decrease in denials.”

• The cash applications supervisor at a regional health system said: “Staff have told me that it’s better at locating coverage, identifying more accurate coverage, and finding information they wouldn’t have found on their own. The messages that come back help them make good decisions and understand what action needs to be taken, which improves the accuracy of coverage information before claims are submitted.”

• The director of system patient access and financial clearance at a regional health system said: “Our COB denials have definitely trended down across both professional and hospital billing. Some denial activity is outside of our control because payers occasionally deny claims for reasons that don’t always make sense, but overall we’ve seen a clear improvement and less rework associated with those claims.”
  The director continued: “A big part of that improvement comes from insurance discovery. We may enter one insurance plan, but PAC can identify additional coverage, including secondary insurance and other billable coverage that we didn’t previously have visibility into. For self-pay accounts, it searches for coverage automatically, and we’ve also configured it to perform additional discovery before accounts move to collections to identify coverage that may have been missed earlier. That helps ensure we’re billing the right payer and reducing avoidable denials.”

Modeling and assumptions. Based on the interviews, Forrester assumes the following about the composite organization:

• The composite organization experiences 30,000 COB denials annually and reduces these denials by 40% with PAC.

• The composite organization experiences 15,000 eligibility denials annually and reduces these denials by 35% with PAC.

• The composite organization experiences 7,000 registration-related denials annually and reduces these denials by 20% with PAC.

• The average denied claim value is $3,000.

• Thirty percent of denied claim value would otherwise result in revenue leakage because not all denied claims are successfully corrected, appealed, and reimbursed.

• The composite organization’s operating margin is 6.3%.

Risks. Forrester recognizes that these results may not be representative of all experiences. The following factors may impact this benefit:

• Volume of COB, eligibility, and registration-related denials before PAC.

• Average value of denied claims.

• Percentage of denied claims that ultimately result in revenue leakage.

• Operating margin.

Results. To account for these risks, Forrester adjusted this benefit downward by 15%, yielding a three-year, risk-adjusted total PV (discounted at 10%) of $2.2 million.

Increased Preservice Collections Due To Enhanced Insurance Discovery

Evidence and data. Interviewees reported that PAC helped their organizations improve preservice collections by providing earlier and more complete visibility into patients’ coverage status. Through enhanced insurance discovery capabilities, PAC automatically searched for active and previously unidentified coverage, allowing organizations to distinguish between patients who were truly self-pay and those with billable insurance that had not yet been identified. Interviewees explained that replacing manual insurance investigation activities with PAC’s automated insurance discovery, which uses AI, reduced uncertainty surrounding coverage status and enabled financial clearance teams to act with greater confidence. As a result, their organizations were able to engage self-pay patients earlier; collect copays, deductibles, and self-pay balances before service was rendered; and route patients into appropriate preservice collection workflows without delaying action due to uncertainty about whether coverage existed.

• The senior director of revenue cycle at a multiregional health system said: “As more patients used self-registration, e-check-in, and kiosk-based check-in, we no longer had to worry as much about insurance information being incorrect or needing to be confirmed later because it had already been verified before the patient arrived. Having accurate coverage information upfront allowed us to move forward with the right registration, financial clearance, and patient responsibility discussions much earlier in the process.”
  The senior director continued: “PAC helps us determine whether a patient truly is self-pay. Once we know exactly what coverage a patient has, or doesn’t have, we can take the next step, whether that’s another insurance option, Medicaid, financial assistance, or a payment plan. That allows us to engage patients earlier and start the right financial process before balances move downstream.”

Modeling and assumptions. Based on the interviews, Forrester assumes the following about the composite organization:

• The composite organization serves 700,000 patients annually.

• Five percent of patients are classified as self-pay before PAC.

• With PAC, the composite increases confirmed self-pay patient identification by 20% in Year 1, 25% in Year 2, and 30% in Year 3.

• The average preservice collection value per self-pay patient is $55. This represents copays, deductibles, self-pay balances, and other patient responsibility amounts collected before service.

• The composite organization’s operating margin is 6.3%.

Risks. Forrester recognizes that these results may not be representative of all experiences. The following factors may impact this benefit:

• Annual patient volume.

• Percentage of patients classified as self-pay before PAC.

• Average preservice collection value.

• Operating margin.

Results. To account for these risks, Forrester adjusted this benefit downward by 10%, yielding a three-year, risk-adjusted total PV (discounted at 10%) of $67,000.

Improved Cash Flow

Evidence and data. Interviewees reported that PAC helped accelerate reimbursement by improving the accuracy, completeness, and primacy of insurance information before claims entered the revenue cycle. By identifying active coverage, establishing payer primacy, and resolving coverage issues at patient intake, PAC enabled their organizations to submit cleaner claims and reduce reimbursement delays associated with coverage discrepancies and claim corrections. Interviewees explained that claims moved through billing and adjudication processes more efficiently, reducing the time between service delivery and payment. As a result, their organizations accelerated cash collections, reduced AR days, and strengthened cash flow performance.

• The senior director of revenue cycle at a multiregional health system said: “We weren’t getting many of the capabilities that we’re getting from PAC today. The return has come from reducing denials, reducing the time spent on claim follow-up, and ultimately getting paid sooner on those claims through higher clean-claim rates. Those are the metrics we use to demonstrate the ROI of the investment to the business.”
  The senior director continued: “The value isn’t just the time savings; it’s also the speed of receiving the dollars. When we reduce denials, we reduce claim follow-up and get paid sooner on those claims. Whether payment arrives in one month versus much later makes a difference because every delay creates additional work to track, follow up on, and resubmit claims.”
  This interviewee added: “We’ve made significant progress on our AR days. Having cleaner insurance information and fewer eligibility-related denials help claims move through the process with fewer delays. When we reduce denials, we naturally see the impact reflected in our AR performance.”

Modeling and assumptions. Based on the interviews, Forrester assumes the following about the composite organization:

• The composite organization generates $5 billion in annual revenue.

• The composite maintains an average AR balance equivalent to 40 days of revenue.

• With PAC, the composite reduces average AR days by 5%.

• The composite organization’s cost of capital is 6.2%.

Risks. Forrester recognizes that these results may not be representative of all experiences. The following factors may impact this benefit:

• Annual revenue.

• Average AR days in the prior environment.

• Cost of capital.

Results. To account for these risks, Forrester adjusted this benefit downward by 15%, yielding a three-year, risk-adjusted total PV (discounted at 10%) of $3.6 million.

Improved Front-End And Revenue Cycle Staff Productivity

Evidence and data. Interviewees said that before implementing PAC, front-end staff regularly worked in insurance-related queues and corrected registration issues after the fact because coverage problems were often identified only after accounts had moved downstream in the revenue cycle. With PAC, eligibility and coverage information was identified and populated into the registration system automatically, in some cases running in the background ahead of a patient’s scheduled visit, so that registrars could confirm coverage rather than manually research and enter it themselves. Interviewees said this reduced the volume in insurance-related work queues, minimized manual coverage corrections, and enabled front-end teams to spend less time resolving routine coverage issues and more time addressing exceptions and patient-facing activities.

Interviewees also described productivity gains for back-end revenue cycle teams. Before PAC, staff often conducted manual coverage searches across multiple payer websites to verify insurance information and identify billable coverage. With PAC’s insurance discovery capabilities returning coverage information automatically, staff spent less time performing manual searches and could redirect that time toward higher-value follow-up and analysis activities. Interviewees further noted that PAC simplified coverage intelligence workflows by reducing the need for manual payer research and interpretation. As a result, new revenue cycle hires learned insurance discovery processes faster and reached full productivity sooner than with prior manual approaches.

• The senior director of revenue cycle at a multiregional health system shared: “We started running automated batches against Medicaid pending, bad debt, and charity accounts to identify insurance coverage and update those accounts when coverage was found. After proving that process worked, we expanded it to scheduled visits by running eligibility checks 24 hours before the appointment. If a patient’s coverage had changed since scheduling, the information was updated automatically. The process runs in the background without staff involvement, which takes the burden off registrars. By the time the patient arrives, the coverage information is already populated in the registration system, and the registrar simply confirms that it is correct.”
  The senior director continued: “As registration and insurance quality improved, we saw a reduction in insurance-related work queues. Instead of spending time correcting registration and coverage issues after the fact, our teams were able to focus on identifying root causes and fixing problems upstream. Team members who had been working insurance-related queues could be redirected to resolving more complex issues.”

• The director of revenue cycle operations at a regional health system said: “PAC creates the coverage for us and adds it into our registration system when coverage is found. A lot of this is handled before the patient even arrives, so it can be fixed ahead of time. When the patient is registered, the coverage is already filled in, which takes work off our front-end staff.”
  The director continued: “Before PAC, back-end staff often had to conduct manual coverage searches through payer websites, which usually took several minutes per account. With [PAC], the information is returned in less than 30 seconds. That eliminates a significant amount of manual search time for the team over the course of a week.”

• The cash applications supervisor at a regional health system shared: “[In the prior environment], the workflow was very different and staff often had to search multiple websites to verify coverage information. With [PAC], much of that information can be located automatically, which saves time and makes the process easier to learn.”
  This interviewee continued: “PAC is easier to understand than the way we used to do it. As new team members have come into the back-end function, we’ve found they can learn the process more quickly and become productive sooner.”

• The senior director of patient finance at a multiregional health system said: “If the correct COB information is identified upfront, you’re filing the claim in the proper order and it becomes a clean claim. The team doesn’t have to touch it. For high-confidence accounts, PAC automatically uploads the insurance information into the system instead of creating a work queue for someone to review and update manually.”
  The senior director continued: “From a registration standpoint, the correct insurance information is automatically populated so we don’t have to review and resolve coverage work queues. On the back end, we’re identifying the correct coverage and payer order upfront instead of filing a claim only to learn later that the wrong insurer was billed.”
  This interviewee concluded: “We’ve seen benefits from fewer denials because there is less work for team members to perform. With a clean claim, you don’t have a second touch, you don’t have additional follow-up, and you don’t have to send multiple claims or supporting documentation. It gets paid the first time.”

• The director of system patient access and financial clearance at a regional health system said: “We’re spending much less time going into payer portals to look up coverage information because responses come back quickly through PAC. Front-end staff no longer have to stop what they’re doing, navigate to a separate system, and then return to the registration workflow. While we had some initial alert-fatigue challenges, we’ve addressed them over time, and the process is now much more efficient.”
  The director continued: “We expanded PAC to support registration, central scheduling, preregistration, and check-in workflows. The solution is easy to use from a functionality standpoint, which helped us train staff quickly. Insurance determination is often complex, but PAC simplified the process and reduced the learning curve for new team members.”

Modeling and assumptions. Based on the interviews, Forrester assumes the following about the composite organization:

• The composite organization employs 800 front-end staff.

• With PAC, front-end staff productivity improves by 5% in Year 1, 7% in Year 2, and 10% in Year 3.

• The average fully burdened annual salary for a front-end staff member is $62,000.

• The composite organization employs 80 revenue cycle staff.

• Before PAC, each revenue cycle staff member performed 10 insurance discovery searches per day, with each insurance discovery search requiring 3 minutes.

• With PAC, time spent on insurance discovery activities decreases by 70% in Year 1, 75% in Year 2, and 80% in Year 3.

• The average fully burdened hourly rate for a revenue cycle staff member is $36.

• The composite organization hires 12 revenue cycle staff annually.

• Before PAC, onboarding each new revenue cycle hire took eight weeks.

• With PAC, the composite reduces onboarding time by 50%.

• For this benefit, the composite has a productivity recapture rate of 50%, which means resources spend half of the saved time on activities that generate business value, but not all reclaimed time is dedicated to value-added work.

Risks. Forrester recognizes that these results may not be representative of all experiences. The following factors may impact this benefit:

• Number of front-end and revenue cycle staff.

• Time spent performing eligibility verification, insurance discovery, and onboarding activities in the prior environment before PAC.

• Fully burdened compensation for front-end and revenue cycle staff.

Results. To account for these risks, Forrester adjusted this benefit downward by 15%, yielding a three-year, risk-adjusted total PV (discounted at 10%) of $4.7 million.

Reduced Third-Party Revenue Cycle Costs

Evidence and data. Before implementing PAC, interviewees said their organizations relied on a combination of outsourced claims, denial management resources, and contingency-based insurance discovery vendors to identify missing coverage and resolve insurance-related issues after patient encounters occurred. These third-party partners often performed functions such as insurance discovery, coverage verification, eligibility follow-up, COB resolution, and denial recovery that internal teams were unable to complete efficiently using legacy tools and manual workflows.

Following PAC deployment, interviewees described a shift toward identifying and correcting coverage issues earlier in the patient journey. By automating insurance discovery with AI-based decisioning, identifying active insurance before claims were submitted, determining payer COB, and creating coverage automatically within registration workflows, PAC reduced the volume of accounts requiring manual downstream intervention. As a result, interviewees’ organizations reduced the eligibility, insurance discovery, and claim follow-up work they routed to external partners and, in some cases, eliminated specialized insurance discovery vendors altogether. Interviewees explained that these improvements reduced outsourced revenue cycle labor costs and third-party insurance discovery expenses while increasing organizations’ ability to manage coverage-related activities internally.

• The director of revenue cycle operations at a regional health system said: “We’re always looking to reduce the amount of work that has to be sent to external vendors. Since implementing PAC, the volume of eligibility and insurance discovery work handled by our vendor has decreased pretty significantly. We’re continuing to improve our autocreated coverage rates because the more coverage we can identify and create upfront, the less work has to be routed to a vendor. [...] Autocreation of coverage with PAC is really the best way to eliminate what would otherwise have to go out for manual review and resolution.”

• The senior director of revenue cycle at a multiregional health system shared: “The volume of eligibility and insurance-related claims requiring follow-up has gone down, so there are fewer issues falling into the work queues. That has reduced the amount of follow-up work that needs to be performed, which means we rely less on third-party resources supporting those activities because there’s simply less work for them to handle.”

• The senior director of patient finance at a multiregional health system explained: “Before PAC, we relied on multiple vendor partners for eligibility verification and insurance discovery. Different vendors were performing insurance discovery at various stages of the revenue cycle, including identifying Medicaid coverage and resolving COB-related issues before claims were submitted. Since implementing PAC, we’ve been able to eliminate one of those vendor relationships.”

Modeling and assumptions. Based on the interviews, Forrester assumes the following about the composite organization:

• Before PAC, the composite spends $600,000 annually on third-party claims and denial management services.

• With PAC, the composite reduces outsourced claims and denial management costs by 30% in Year 1, 40% in Year 2, and 45% in Year 3.

• Before PAC, the composite spends $250,000 annually on contingency-based insurance discovery vendor services.

• With PAC, the composite reduces contingency-based insurance discovery vendor spend by 75% in Year 1 and 100% in Years 2 and 3.

Risks. Forrester recognizes that these results may not be representative of all experiences. The following factors may impact this benefit:

• Outsourced claims and denial management spend before PAC.

• Contingency-based insurance discovery vendor spend before PAC.

Results. To account for these risks, Forrester adjusted this benefit downward by 15%, yielding a three-year, risk-adjusted total PV (discounted at 10%) of $960,000.

Unquantified Benefits

Benefits that provide value for the composite organization but are not quantified for this study include:

• Strong operational and optimization support from the Experian Health team. Interviewees described Experian Health as a collaborative partner that worked closely with their organizations to optimize workflows, troubleshoot issues, and improve operational performance after deployment. Rather than limiting interactions to support requests, interviewees said Experian Health regularly participated in operational reviews, denial analysis discussions, and payer investigations to help identify root causes and recommend corrective actions. Interviewees also noted that Experian Health worked directly with payers and electronic health record stakeholders when issues arose to help accelerate issue resolution and reduce the burden placed on internal teams. Several interviewees emphasized that this level of engagement differed significantly from their experiences with other technology vendors.
  The director of system patient access and financial clearance at a regional health system said: “The difference with PAC, and Experian Health in general, is that it feels much more like a partnership. We meet regularly to review operational performance and denials, and Experian Health helps us identify trends, investigate unusual activity, and determine whether issues are isolated incidents or broader patterns. It’s a completely different approach.”
  The director continued: “What I also appreciate is that they engage directly with our operational teams, not just leadership. Coordinators, leads, and managers are all part of the discussions, which allows us to identify issues, evaluate potential changes, and continuously improve workflows. Their involvement extends beyond eligibility to COB, Medicare-related processes, and the entire coverage intelligence workflow.”
  This interviewee also shared: “One thing I appreciated was that Experian Health included our electronic health record stakeholders in discussions when issues arose. If we needed to determine whether a problem originated with the payer, Experian Health, or another system, they helped bring the right parties together. When we encountered payer-related issues, Experian Health would join calls with us, help analyze how the information was being transmitted, and work directly with the payer to drive resolution. That level of technical engagement created a strong partnership and helped us solve problems more efficiently.”
  The senior director of revenue cycle at a multiregional health system said: “We identified an issue where a payer’s third-party verification process was returning an incorrect subscriber ID. Because we were using automated filing, that information was populated into our system, claims were submitted with the wrong subscriber ID, and we received eligibility denials. We brought the issue to Experian Health, and they were able to trace the transactions, validate the issue with the payer, and help drive a resolution. That was significant because it eliminated a major source of denials and rework. More importantly, Experian Health’s ability to identify the root cause helped the payer recognize that the issue wasn’t isolated to our organization. Their visibility into the data helped drive a resolution that benefited multiple organizations.”

• Improved employee satisfaction. Interviewees reported that PAC simplified many of the registration and coverage verification activities that front-end staff previously performed manually. By consolidating eligibility verification, insurance discovery, COB determination, and other coverage-related activities into a single workflow, PAC reduced administrative burden and made registration activities easier to perform. PAC also reduced the manual decision-making required of registrars by automatically identifying coverage, determining payer primacy, and guiding the appropriate next action. As a result, employees spent less time researching coverage information and navigating multiple systems, improving the day-to-day experience for patient access teams.
  The director of revenue cycle operations at a regional health system said: “A lot of the work is done before it gets to the front end. PAC gives us capabilities like coverage verification, MBI lookup, COB and primacy determination, and demographic updates all in one query. When I’ve talked to people on the front end, they find it so much easier and better for registration. That’s a big deal when you have hundreds of people using it. Having people happier with the process really helps with employee engagement.”

• Improved patient satisfaction. Interviewees noted that PAC helped create a better patient experience by improving the accuracy of insurance information before services were rendered and claims were billed. By identifying coverage earlier and ensuring claims were submitted to the appropriate payer, organizations reduced billing discrepancies and minimized situations that required patients to clarify insurance information after the fact. Interviewees explained that more accurate billing helped reduce confusion and improve the overall financial experience for patients. Some organizations also observed reductions in billing-related complaints after implementing PAC.
  The director of system patient access and financial clearance at a regional health system said: “If we mark someone as self-pay and then find active coverage and feel confident in that information, that’s one less phone call we have to make. I definitely think that helps the patient experience.”
  The director of revenue cycle operations at a regional health system shared: “Overall, our patient complaints have gone down since implementing PAC. Through our customer service teams, we’ve continued to see the percentage of complaints that are billing-related decrease over time.”

• Improved collaboration across front-end and back-end teams. Interviewees reported that PAC helped improve coordination between patient access, registration, training, and revenue cycle teams by creating more standardized coverage intelligence processes and improving visibility into insurance-related issues. Because coverage intelligence activities became more automated and consistent, interviewees’ organizations found it easier to communicate workflow changes, address operational issues, and align staff around common processes. Interviewees also noted that front-end and back-end teams worked more closely together to monitor performance, manage updates, and improve registration quality.
  The director of revenue cycle operations at a regional health system said: “We work closely with the team responsible for front-end training. When there are updates, new information, or messages that we want the front end to look at, we communicate those changes across teams. If they need to make a change, they let us know, and vice versa. There’s ongoing communication between the front end and back end.”

• Reduced human error in coverage selection and registration processes. Interviewees explained that before PAC, coverage identification and insurance selection often depended on manual review and interpretation by registrars. Staff were required to evaluate insurance information, determine the appropriate coverage selection, and make decisions that could vary based on individual experience and judgment. PAC reduced these challenges by automatically identifying and returning the appropriate coverage information within registration workflows. As a result, organizations improved consistency in coverage intelligence, reduced avoidable registration errors, and increased confidence in the accuracy of insurance information used throughout the revenue cycle.
  The senior director of patient finance at a multiregional health system said: “The team doesn’t have to determine which insurance plan to select because PAC automatically pulls that information back. It’s not just about time savings; it’s about reducing human error in the decision-making process. Instead of staff having to look at an insurance card and decide which coverage to choose, PAC returns the correct information for them. It helps with compliance risk because you don’t have that human intervention where someone has to interpret the information and decide which coverage to select.”

Flexibility

The value of flexibility is unique to each customer. There are multiple scenarios in which a customer might implement PAC and later realize additional uses and business opportunities, including:

• Continuous optimization of patient access workflows. Interviewees noted that PAC is not a “set it and forget it” solution. As their organizations refined workflows, payer mappings, coverage rules, and automation strategies, they worked closely with Experian Health teams to optimize performance and address emerging requirements. This ongoing collaboration helped interviewees’ organizations continue improving coverage accuracy and denial prevention outcomes over time while adapting to evolving payer and operational needs.
  The director of system patient access and financial clearance at a regional health system said: “We use [PAC] in several different ways. If we enter a patient as self-pay, PAC will go out and look for coverage. It can identify secondary coverage that we weren’t aware of, and we’ve even configured it to run before accounts are sent to collections to see whether there is coverage that may have been missed earlier or whether Medicaid was approved retroactively.”

• Expanded denial prevention and coverage optimization opportunities. Interviewees explained that after establishing PAC as the foundation for coverage intelligence, their organizations continued identifying new opportunities to automate coverage-related workflows and improve reimbursement outcomes. They noted that as payer requirements, patient access models, and organizational priorities evolve, PAC provides a solution that can support additional automation, insurance discovery, and denial prevention use cases. Interviewees’ organizations can refine payer mappings, coverage rules, and workflow configurations over time to increase automation rates, improve coverage accuracy, and address emerging operational needs. Several interviewees described ongoing opportunities to expand PAC into additional workflows and decision points across the revenue cycle, which allowed their organizations to uncover new reimbursement opportunities and drive further operational improvements over time.
  The director of system patient access and financial clearance at a regional health system said: “We use [PAC] in several different ways. If we enter a patient as self-pay, PAC will go out and look for coverage. It can identify secondary coverage that we weren’t aware of, and we’ve even configured it to run before accounts are sent to collections to see whether there is coverage that may have been missed earlier or whether Medicaid was approved retroactively.”

Flexibility would also be quantified when evaluated as part of a specific project (described in more detail in Total Economic Impact Approach).