Prior authorization isn’t just a burden for healthcare providers—data indicates that patients actually bear the brunt of outdated systems.
According to the American Medical Association, 34% of physicians report that prior authorization (PA) has led to a serious event threatening the health of a patient in their care, including hospitalizations, disabilities, and even death. Further, 93% of physicians report delays in care associated with PAs, and 82% report abandoned treatment. The urgency for automated prior authorization is clear:
Not only can improvements to current systems contribute to better patient outcomes, but they also save medical providers time, money, and hassle.
The same report revealed that physicians and their staff spend almost two business days per week completing an average of 41 PAs, the majority of which are handled over the phone. The PA process is clearly overdue for improvement and innovation.
Let’s dig deeper into the case for automating prior authorization, as well as details on how automation works for PAs and how model providers are already streamlining prior authorization using automation.
Simply put, prior authorization is the process a healthcare provider undertakes to verify that services and treatments are covered by a patient’s insurance before they are administered. In many cases, PA is a money-saving measure for health insurance providers, and employers often choose plans with more PAs to reduce healthcare costs. This to say, prior authorization is a routine part of patient care and won’t likely disappear anytime soon.
Prior authorization is commonly a manual, time-consuming process involving multiple steps. Healthcare providers must:
For both medical services and prescriptions, physicians report using the phone most often for PA. In the case of services, fax is the next preferred method; for prescriptions, fax is the third most-used option.
What does all this mean for the human workers managing these processes? Phone calls can lead to extended wait times, dropped calls, and miscommunication resulting in errors and delays.
Sadly, in some cases, the insurance companies on the line do have electronic portals, but because these are so difficult to navigate, it’s faster for providers to call. Fax machines can also return busy signals and generally transfer data more slowly and inefficiently than digital systems, a challenge made exceedingly clear by extra strain the pandemic has laid on the medical system.
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Key challenges for medical providers without automated prior authorization include:
While automation can’t improve insurance portals or simplify PA requirements, it can help providers navigate complex, manual processes with greater speed and efficiency.
Providers may resist updating their PA process for a variety of reasons; perhaps the majority of their patients use one of a few major insurers for which prior authorization workflows are well-established. Still, this doesn’t mean those processes couldn’t be faster, or that serving patients with other insurances should be as challenging as it is.
The bottom line is that updating the prior authorization process will provide value well beyond the initial investment. Case in point:
A 26% increase in the automation of prior authorization in 2020 saved $437 million across the U.S. and decreased handling time by 16 minutes per PA.
RPA bots are trainable, rules-based software entities that can interact with systems through user interfaces to extract and review data. Since these bots can be trained to recognize specific data types wherever they’re stored, healthcare professionals can utilize bots to identify and extract patient insurance data for example, or check this data against an insurer system to complete prior authorization.
RPA bots don’t require custom software development, making them quicker, more nimble, and less expensive to deploy than other potential solutions for PA. Intelligent automation layers RPA with technologies like AI to leverage Optical Character Recognition (OCR), Natural Language Processing (NLP), computer vision, and machine learning. Using these tools allows RPA bots to identify and copy the right information, even among a range of forms.
Automation is also compatible with PA aggregator systems that allow providers to check benefits for a cluster of health insurance companies using a single system. An RPA bot can easily be trained to perform the same operations a human worker would with greater speed and fewer errors. There is also no aggregator on the market that includes every insurance company a patient could potentially use, so even with an aggregator, the PA process still requires navigation through multiple systems—systems that lend themselves to data extraction and review using automation. In this scenario, a provider could train a smart bot to interact with both the aggregator system and every other insurance company the provider accepts to speed up prior authorization.
The desire to enhance patient experience (with the added benefit of reduced operational costs) is a powerful incentive for automated prior authorization. For providers wondering how to speed up prior authorization, consider the following examples.
To accommodate over 500 patients daily, an eyecare group with more than 120 optometry stores in the U.S. previously relied on staff to preauthorize insurance among 40+ carriers.
In an arduous, error-prone process, team members manually extracted individual eligibility details from multiple legacy applications—and repeated the process for every visit even in the case of returning patients, given continuous updates to covered benefits.
Using the Nividous Platform, they deployed bots to complete the full process:
As a result, the group saved 1,500 staff hours per month and improved data accuracy by 100%.
A leading specialty healthcare company focused on oncology and cardiovascular care was looking to provide a better patient experience by improving back-office workflows. Specifically, the company wanted to streamline prior authorization and claim submissions, a process that required more than ten employees to extract, review, and submit patient data.
The PA and insurance claims process meant workers had to manage a range of document types (sent and received) in various formats, including fax and scan; this resulted in errors, claim rejections, and a sizable PA backlog.
Using Nividous Bots with cognitive capabilities, the company was able to automate prior authorization and claim processing in just two weeks, reducing manual work by 80% and decreasing operational costs by 45%.
The power of intelligent automation is spurring increasing adoption across the healthcare sector, for a range of processes including PA. If you’re interested in freeing up valuable staff time and optimizing patient care, it’s time to explore Nividous.
Our expert team has a strong history of partnering with health care organizations of all sizes to help them focus more resources on what matters most—the long-term health and wellbeing of those they serve. Reach out today to learn more and get started.