At A Glance
Coverage issues at registration can lead to denials, slower reimbursement and more manual work. In an all-new Forrester study commissioned by Experian Health, Forrester modeled the potential financial impact of Patient Access Curator for a composite organization, a representative U.S.-based integrated health system created using insights gathered through customer interviews and financial analysis. For this composite organization, Forrester modeled $11.5 million in three-year risk-adjusted present value benefits, $50.4 million in revenue protected through reduced coordination of benefits, eligibility and registration denials, and $82.2 million in accelerated cash collections.
The Total Economic Impact™ Of Experian Health Patient Access Curator was a commissioned study conducted by Forrester Consulting on behalf of Experian Health, August 2026. The study modeled how front-end coverage accuracy affected denials, cash flow, and staff productivity in a composite organization.
Key takeaways:
- Coverage accuracy at intake can give revenue cycle teams a clearer view of active coverage, payer order and patient demographics before a claim is created.
- Earlier coverage checks were linked to fewer denials, faster cash collections and less manual rework.
- Patient Access Curator™, an Experian Health solution, uses AI decisioning to validate demographics and coverage information during intake, so teams can identify insurance and payer issues earlier.
Revenue cycle problems often appear downstream, but some begin much earlier. When patient access teams do not have a complete view of active coverage, payer primacy and patient demographics, teams may need to correct claims, appeal denials or search for coverage after service, delaying reimbursement.
Checking coverage earlier can reduce that rework. Patient Access Curator brings insurance discovery, eligibility, coordination of benefits (COB) and demographic validation earlier in the revenue cycle.
What happens when coverage issues are missed at registration?
Coverage issues missed at registration can turn into wrong-payer denials, extra work and slower collections. For healthcare claims management teams, that means more claims corrections and denial follow-up. Interviewees said they moved insurance discovery, payer-order determination and coverage correction earlier so teams could fix more issues before claims reached billing.
Before adopting Patient Access Curator, interviewees relied on a mix of eligibility tools, manual registration workflows, insurance discovery tools and outsourced recovery services. These tools could validate submitted insurance but often could not find missing coverage, determine payer order or correct inaccurate patient and payer information before claims moved downstream.
“My question was always, why wait until an account is nearing bad debt to run insurance discovery? Why not do it upfront? That’s what we wanted PAC to do.”
Senior director of revenue cycle, multiregional health system
How Patient Access Curator checks coverage earlier
Patient Access Curator uses AI to check patient and insurance information during intake. This includes demographics, insurance coverage, coordination of benefits, Medicare Beneficiary Identifier (MBI) and related payer information. These checks reduce the need for manual decision-making and improve data accuracy before a claim is created.
For the composite organization, Patient Access Curator was used to identify coverage, determine payer primacy and update coverage information before claims were submitted. The study modeled fewer denials, less manual coverage research and lower third-party revenue cycle costs when coverage was checked earlier.
“Having the right insurance information at the right time means there’s less for our team to touch downstream. We can fix issues at registration because we have visibility into what’s causing them, and that has improved our clean-claim performance. It’s allowed our teams to move beyond insurance-related issues and focus on understanding why other claims are ending up in hold work queues. That is the value of PAC.”
Senior director of revenue cycle, multiregional health system
Financial results from the model
For the composite organization in the Total Economic Impact™ study, the modeled results included:
| Financial results: |
| – $11.5 million in three-year risk-adjusted present value benefits |
| – $50.4 million in revenue protected through reduced COB, eligibility and registration denials over three years |
| – $82.2 million in accelerated cash collections over three years |
| – A 40% reduction in COB denials, a 35% reduction in eligibility denials and a 20% reduction in registration-related denials |
| – A 5% reduction in accounts receivable (AR) days |
| – An 80% reduction in time spent on insurance discovery for back-end revenue cycle teams by Year 3 |
| – A 45% reduction in outsourced claims and denial management costs by Year 3 |
Forrester based the model on a U.S.-based integrated health system with $5 billion in annual revenue, 20,000 employees, approximately 700,000 patients a year and 21 million hospital and professional claims annually. Forrester risk-adjusted the financial benefits in its Total Economic Impact™ analysis.
The figures are not a forecast for every organization; they show where the model assigned financial value when more coverage work moved upstream.
“The savings from reduced denials alone have helped pay for the cost of the solution. That’s a powerful outcome and one of the reasons we’re continuing to invest in PAC.”
Senior director of revenue cycle, multiregional health system
What the study found about downstream revenue cycle friction
For the composite organization, the modeled downstream effects showed up in workload and operating costs. The composite model projected less time spent on insurance discovery by back-end revenue cycle teams and lower outsourced claims and denial management costs. An interviewee also said that with fewer insurance-related issues to address, teams could focus more attention on other reasons claims entered hold work queues.
“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.”
Senior director of revenue cycle, multiregional health system
For the full financial model, assumptions and modeled benefits, download The Total Economic Impact™ Of Experian Health Patient Access Curator.
Source: Forrester Consulting, The Total Economic Impact™ Of Experian Health Patient Access Curator, a commissioned study conducted by Forrester Consulting on behalf of Experian Health, August 2026.
Frequently asked questions
Patient Access Curator is an Experian Health patient access solution that uses AI decisioning during intake to validate and curate demographics, eligibility, insurance discovery, coordination of benefits, Medicare Beneficiary Identifier and related payer information.
A composite organization is a modeled organization that Forrester Consulting constructs from interview findings to analyze potential benefits, risks and financial impact. Results for the composite organization are not a guarantee of results for every organization.
Coordination of benefits helps determine the correct payer order when a patient has more than one coverage source. Incorrect payer order can contribute to denials, rework and reimbursement delays.
Forrester Consulting used its Total Economic Impact™ framework to model benefits, risks and present value for the composite organization. The study explains its calculations and risk adjustments.
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