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Optimizing Patient and Payor Payments with Patient Responsibility Estimator Tool
September 1, 2022In 2021, the total US out-of-pocket healthcare patient spending increased by 10% from the previous year and is expected to continue to increase by 9.9% annually through 20231. An increase in a patient’s financial responsibility is a growing problem in healthcare and is driven by several factors including:
Payors shifting a larger portion of the payment to patient responsibility, on average the insured patient is responsible for 30% of the payment to providers2 .
A rise in the number of patients who are uninsured or self-pay, with income that excludes them from charitable programs or state Medicaid programs.
Growth of insurance coverage limitations resulting in patients receiving bills for services they expected to be covered.
At the same time, in 2022, the No Surprises Act was enacted to protect patients from unexpected medical bills by addressing surprise billing. Broadly speaking, surprise billing refers to a situation in which an insured patient receives an unexpected medical bill, usually from a physician outside of that patient’s network. Surprise billing can also occur when an insured patient or self-pay patient receives a bill for an amount greater than what they were financially expecting.
For an uninsured or self-pay patient, under the No Surprises Act, providers are required to provide a good faith estimate of all services prior to performing the services. For more information on providing a good faith estimate visit the XiFin No Surprises Act Resource Center.
Turning a Challenge Into An Opportunity
While these trends can present challenges for healthcare providers and staff, they can also present opportunities. Providers have an opportunity to enhance patient engagement, increase physician satisfaction, and optimize patient payments by providing tools that offer insight into costs and patient payment responsibility.
An accurate patient responsibility estimator is a vital tool in improving patient engagement and ensuring patients are not blindsided with unexpected costs. Providing price transparency early in the diagnostic ordering process is an excellent way to enhance both the patient and ordering physician experience, as well as to support evolving surprise billing rules and regulations.
XiFin, Inc. developed a patient responsibility estimator, a sophisticated application that allows providers to share cost estimates with the patient prior to care. By uniquely leveraging important data from the billing system, the XiFin patient estimator tool can provide access to the expected reimbursement at the CPT level by payor plan. Utilizing this in conjunction with the patient real-time eligibility information, providers can determine the amount that should be collected from a patient at the time of the order.
Learn more about our patient estimator in this video.
Collecting Patient Information – The XiFin Patient Estimator tool allows for easy collection of the patient demographic, insurance information, and tests or procedures being performed.
Identifying Expected Reimbursement – Through integration with the XiFin RPM billing system, utilizes the patient information collected to confirm insurance eligibility and determine the expected reimbursement by the payor when billed.
Providing an Accurate Patient Estimate – The tool offers accurate estimates of a patient’s expected out-of-pocket expenses under their payor-specific health plan that considers copays, coinsurance, and deductible amounts from the billing system.
The XiFin Patient Estimator…
Increasing Payor Payment Accuracy
Clients also utilize the XiFin Patient Estimator to monitor payor payment accuracy. Comparing actual payment from the payor to the estimated payment provided to the patient (the expected or contracted payor amount loaded into the billing system) allows monitoring of accuracy by test, payor, and client to identify and resolve issues impacting reimbursement.
The XiFin reporting tools allow an analysis of the data in multiple ways including:
- Accuracy comparison of the top paid tests and top payors, based on volume or revenue
- Payor accuracy comparisons by defined date of service including month-to-month, quarter-to-quarter
- Patient estimation accuracy by top referring client and test mix
Analysis of the patient estimation accuracy allows providers to not only ensure the information being provided to patients is accurate but also provides an opportunity to identify when payors are not paying according to contracted terms. Narrowing down the issues based on the test mix provides an opportunity for providers to work with the payor to ensure accurate payment based on agreed-upon fee schedules.
XiFin Patient Accuracy Reporting Example
Increasing Patient Collections
Through the XiFin patient estimation, providers can collect pre-payment at the time of the service. Integrating the services will enable payments to transfer automatically to the billing system. Collecting a partial payment at or before the time of service can reduce potential uncollected bad debt.
XiFin has also introduced text functionality that provides the option of enabling the patient responsibility estimate to be communicated in near real-time to the patient via text message. This new capability will notify patients via text message that they can retrieve their estimated out-of-pocket expense, approve to move forward with the test, and prepay—all through the patient portal.
The XiFin Patient Estimator can also be utilized the provide uninsured or self-pay patients with a cost estimate of services. On average, 90% of all billed self-pay claims are uncollected from patients. By educating the patient prior to performing the service, patients will have an opportunity to decline the services or will not be surprised when they do receive a bill.
Combining patient estimation tools with other patient engagement tools such as pre-payment options, e-bills and notifications, payment plan options, and self-service portals can support improved patient collections.
See how Ambry Genetics utilized the patient estimator among other RPM capabilities to improve the patient experience in this case study.
1 “Out-of-Pocket Healthcare Expenditures in the United States, 5th Edition.” KaloramaInformation, 8 Aug. 2021, kaloramainformation.com/product/out-of-pocket-healthcare-expenditures-in-the-united-states-5th-edition.
2 Sanborn, Beth Jones. “Revenue Cycle Expert: The Patient Is the New Payer.” Healthcare Finance News, 6 Feb. 2018, www.healthcarefinancenews.com/news/revenue-cycle-expert-patient-new-payer.