Streamlining Healthcare Claim Denials for Revenue Recovery
A robust Denial Notification Authorization (DNA) system that significantly increases the healthcare provider’s overturned denials and revenue.
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Medical testing plays a crucial role in patients’ early detection, diagnosis, and treatment of conditions. Similarly, clear and correct clinicals are critical to fair and timely insurance claim processing for patients and providers alike. According to Health IT Outcomes, most providers report a 70-85% Clean Claim Rate (CL-1), meaning more work to gain reimbursement from approximately a quarter of all patient claims. Insurance companies that do not receive sufficient information to justify treatment can be quick to refuse payment. Roughly one-third of all claims require the inclusion of clinical documentation to avoid insurance denial; claims submitted without adequate documentation of history and physical (H & P) reports and recent lab results are frequently denied. UDig’s Clinical Cleanup Bot solves this challenge.
Incorrect or incomplete clinical information contributes significantly to claim rejection. When we consider that 80% of claims that don’t contain adequate documentation are written off, we realize that practice reimbursement relies upon appropriately capturing clinicals.
This article will examine the clinical inclusion breakdown process and how robotic process automation (RPA) can ensure that proper documentation translates to revenue.
One of the ways that the clinical inclusion process breaks down is through incorrect documentation. According to a 2018 survey by the Physicians Foundation, the average provider sees 20 patients daily. Healthcare providers’ offices are busy places, and medical staff members are prone to errors when working with numerous records and insurance providers.
Clinicals add an additional layer of complexity, given that a different representative might check in a patient than the one that draws blood and that person is rarely the one to conduct the actual test. Simply put, there are many people involved in the clinical process.
At times, files may become crossed, and information for a given patient may be inaccurate or completely incorrect. Claims with the wrong clinicals attached are (justifiably) denied by insurance providers.
The emergency room may always be open, but primary care offices have regular care hours. Patients receiving non-urgent care schedule their appointments at offices that are unstaffed overnight. Patients may wait for overnight care, but insurance companies are usually less patient in waiting for their information.
Depending on an insurance company’s staffing and procedures, notifications of claim denials might arrive outside medical professionals’ office hours, necessitating a staff member to address the denial later. Proper reimbursement may require that insurance requests are met within a specific time frame, opening the door to the possibility of the request being overlooked.
Some insurance providers’ requests require a quick turnaround. In some cases, insurance companies requiring additional information or questioning submitted clinicals require peer-to-peer contact between patient and payer physicians within 24 hours. The clinician cannot respond to the time-sensitive request unless they are notified, and off-hour requests may not be addressed within the proper time frame.
The Agency for Healthcare Research and Quality identifies system-level issues, such as the collection of patient data and data flow, as one of the fundamental causes of claim difficulties and denials. Healthcare providers and insurers have networks that often cannot communicate all aspects of a patient’s experience, from treatment to payment.
When talking about data flow, there’s an assumption there’s a clear path from one system to another. In reality, healthcare systems rely on a unique technology stack. Due to different code bases and a lack of APIs, systems rely on humans to copy data from one program and put it into another. The more humans touch data, the riper the process is for error.
Timely, accurate clinicals directly impact reimbursement. In fact, 80% of claims without written clinicals are written off.
Timely, correct clinicals are an opportunity to improve CL-1, CL-2, and AR-5 KPIs. Claim denials are a multi-faceted problem caused by human error and organizational and physical limitations. RPA is a scalable, economic approach to improve identified KPIs compared to other potential solutions.
Medical reports and patient clinicals contain multiple data points, and incorrect test results or diagnosis codes in the EHR system slow the patient treatment process and may result in payment delays or claim rejection. Clinical Cleanup Bots provide an eye of reason that guards against code errors. Able to pull accurate clinicals into a patient’s record and submit a fax to the payor, bots streamline the patient care and insurance reimbursement processes by scanning for and flagging potential inconsistencies.
Staff hours are a limited resource, yet personnel are the first line of defense in claim correction when claims are denied. Case in point: if clinicals are rejected for the wrong diagnosis code, it stands to reason the proper RPA could troubleshoot by reviewing patient record information to verify code validity.
Many systems are indeed unable to share information seamlessly; however, most readily spot missing data and are quick to throw an error code. These errors become the responsibility of office workers, who must reach out for more information and clean up records.
The fact is, in most cases missing clinical information is readily available. It’s not the lack of information causing the delay; it’s the time personnel must spend locating the absent information. Enter RPA technology – adept at flagging and finding overlooked clinicals, thus reducing or eliminating reimbursement delays.
No matter the tech, more clicks mean more room for error. In healthcare, those errors could result in a devastating patient treatment delay or a lack of payment to the provider. RPA bots are tireless, behind-the-scenes workers capable of drastically reducing the number of human touches in provider workflows.
When you download our Clinical Cleanup Bot Use Case, you will see a typical workflow consisting of ten human touches – from care management tasks to successful record updates. The same RPA-enhanced workflow would require only three human touches, a 67% reduction in personnel engagement.
Robotic process automation prospers in busy healthcare settings recognizing the necessity for complete, correct clinicals and instant, automated claim submission. Though personnel jump through hoops to input accurate clinical codes and full patient data, increasing insurer demands call for advanced optimization to ensure timely provider reimbursement.
Healthcare practices that manage clinicals with RPA deliver more comprehensive patient history and labs to insurance agencies while reducing the administrative burden on providers and office personnel. These bots capably bridge information systems with accurate patient and treatment information, provide instant claim submission, and monitor claim status 24/7/365. They reduce the likelihood of human error, eliminate non-value-added processes, and ensure the claim status is clear to all.
In fact, our Clinical Cleanup Bot reduces the ten human touchpoints involved with clinical submission to only three. This dramatic reduction in labor running at all times every day provides ample opportunity to improve Clean Claim rates, thereby enhancing Revenue Cycle Management.