
Can automation solve the prior authorization problem?
It’s clear the state of PA must change. Artificial intelligence has a role in streamlining administrative tasks.
In the
In 2021 alone, Medicare Advantage insurers fully or partially denied more than
If providers largely agree this process is so dangerous to patient care, why hasn’t it changed? The complications and delays caused by PA boil down to the exchange of information for providers and payers.
The burden of proof
Prior authorization exists so insurers can reduce payments for medically unnecessary procedures and treatments. The argument against this cost-control process is that it burdens providers, plans, and patients unnecessarily. PA often delays or prevents access to care, and patients may spend more out-of-pocket in instances of improper denial.
Health plans are complex, and patients often don’t know what services require prior authorization, the criteria used for making a coverage decision, or if their doctors provide the necessary information to insurers to secure coverage. Today, payers have no standardized method for receiving and approving requests. It’s a largely manual, arduous, and time-consuming process that detracts from valuable resources and time spent on patient care. With health care staff forced to complete PA requests differently for every payer, it’s cumbersome, lengthy, and inefficient, creating slow processing and turnaround times.
Although 2022 data from the
The data challenge
The proposal from CMS is designed to relieve the administrative hassles of PA by creating a standard electronic model for exchanging data and could make it significantly easier to automate prior authorization. CAQH reports that one-third of prior authorizations are still completely manual, meaning they're completed over the phone, mail, fax, or email. More insurers provide web portals where medical staff can submit the necessary information. Still, the lack of automation coupled with the proliferation of web portals only adds to the volume of prior authorization methods that medical staff need to track.
Because prior authorization is based on data exchange, technology-driven improvements have tremendous potential and opportunity, especially with a standardized model. The biggest obstacle concerning introducing AI revolves around the need for accurate provider information to support the claims.
Insurers sift through clinical and administrative data to build a case for approval or denial. Payers need to pull information from the patient record and billing system while ensuring the administrative data regarding the provider, location, and office are all accurate. Treatment and procedures are typically denied because of poor documentation. Often requests lack the proper medical documentation as to why tests or procedures should be done. It could also be as small an error as the wrong medical code was included. The challenge of having accurate data fields highlights why the approval process is so cumbersome, especially when requests are created manually.
Automating authorization
Today, robust exchange models are augmenting administrative efficiencies between providers and payers. The final step to solve the PA question requires a model that includes patient information. Without it, payers will always have incomplete data that prevents them from making proper decisions.
Last year,
From the patient's perspective, a streamlined, automated process has clear positive implications. Patients often need to wait a week for requests to be approved or denied, which can often cause them to forgo treatment entirely. According to McKinsey, AI can reduce that window to days, if not hours.
The bottom line
Physicians agree that the state of prior authorization has tangibly negative implications on patient health. When you take the risk to patients and combine it with the financial obligation it places on providers dealing with the administrative side, it’s clear the state of PA must change. If automation can enhance efficiency and reduce provider dissatisfaction while improving patient health, there’s a strong case for introducing automation into the mix.
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