Prior authorization (PA) means doctors must get permission from insurance companies before giving some treatments or medicines. It is meant to control costs and make sure care is right. But the process can be hard and slow. Doctors say they get about 31 prior authorization requests every week. This adds extra work, delays care, raises costs, and causes burnout for providers. A survey shows 93% of providers face care delays because of PA, and 82% see patients stop treatment due to authorization problems.
The traditional way of handling prior authorizations uses paper forms, faxes, and phone calls. This makes things slower and less efficient. Even with efforts to improve, about one-third of prior authorizations were still done completely by hand in 2022. This leads to frustration for healthcare workers and keeps patients from getting care quickly.
Many doctors and organizations have tried AI tools to fix these problems. Examples include using generative AI, electronic prior authorization (ePA), and touchless prior authorization technologies.
Dr. Azlan Tariq, a rehab medicine doctor in Illinois, saw big improvements after using Doximity GPT. This AI helps automate paperwork and appeals for PA requests. It cut his time on these tasks by half and raised approval rates from 10% to 90%. The AI helps make better and clearer prior authorization letters, which leads to fewer denials.
Also, Dr. Michael Albert, an obesity doctor, used AI to increase the number of appeals in his telehealth practice. He went from almost no appeals to 10-20 per week. This helped get more approvals for patients and boosted his practice’s income. These stories show even small clinics can do better by using AI in PA work.
Surescripts is a company that makes electronic prior authorization systems that work inside electronic health records (EHRs). Their system saves about 10 minutes of staff time for each transaction. It also cuts patient wait times for medicine approval by more than two days. The average approval time is now less than four minutes, far faster than the old manual process that could take 20 minutes or more.
One health system using Surescripts ePA did ten electronic prior authorizations in the time it used to take to do one or two by hand. Another system saw a 6% rise in prescriptions picked up by patients. This shows that faster approval helps patients start treatment sooner.
A newer option called Touchless Prior Authorization, also from Surescripts, fully automates approval for medicines when clinical data matches payer rules. In tests, this technology cut approval times from 15–20 minutes down to 27 seconds. It also lowered appeals by 88% and cut denials due to missing information by 68%.
Touchless Prior Authorization works by pulling clinical data from a patient’s EHR, checking it, and sending it straight to pharmacy benefit managers (PBMs). If all clinical rules are met, the request is approved automatically without the doctor needing to do anything. If information is missing or rules aren’t met, the system alerts clinicians inside their EHR to add what is needed.
This system matters for patients too. About 40% of prescriptions delayed by traditional prior authorization are never filled. Faster processing with Touchless Prior Authorization helps patients get their medicines and improves health results.
Current AI solutions not only speed up prior authorizations but also lower errors, simplify workflows, and improve teamwork between providers and payers.
AI tools use natural language processing (NLP) to pull needed clinical data from places like doctor notes and electronic medical records. One project by the KLAS K2 Collaborative showed that NLP tools made reporting more accurate and cut down paperwork.
Simbo AI focuses on automating front-office tasks. It uses AI in phone answering and office communications to reduce mistakes in collecting patient info and PA needs. This helps make submissions accurate and timely.
APIs allow fast, two-way data sharing between providers and payers. This supports real-time checks for authorization and cuts manual delays. For example, FHIR API sharing helps close care gaps faster and supports value-based care.
Simbo AI’s technology works well with this by automating patient communications, checking coverage, and letting staff know about needed authorizations before visits.
Some AI tools use predictive analytics to guess how likely an authorization will be approved. NexAuth, made with Google Cloud, uses this method to lower denials by 25%, cut decision times by 30-50%, and automate up to 75% of manual tasks. AI insights help clinical teams focus on requests that matter and avoid wasting effort on likely denials.
Simbo AI’s platform could also sort calls about prior authorizations. Urgent or complex cases go to staff, while routine questions get handled automatically.
AI platforms improve communication by giving real-time status updates and alerts when more info is needed. This reduces follow-up calls and waiting for replies from insurers, which often slow the process.
Simbo AI’s phone automation can make sure patients and providers get timely news about authorization requests. This lowers uncertainty and improves satisfaction.
Using AI in prior authorizations cuts the long time doctors and staff spend on paperwork. AMA data shows this work can cause burnout and lower patient care quality.
AI workflows free clinical teams to spend more time with patients. Clinics that use AI see faster approvals, more successful appeals, fewer denials from missing data, and shorter patient wait times.
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Insurance companies also benefit by having less manual review work. This lets them focus more on clinical care than on paperwork.
Despite technology progress, AI use in prior authorization faces rules and laws. For example, CMS started the WISeR pilot to use AI to cut fraud but stopped funding it because of worries about transparency and accuracy. Still, CMS’s Innovation Center has budget to support healthcare innovation including AI projects.
Laws aimed at improving health in rural areas and for veterans also encourage using AI to make healthcare easier and more efficient. Using AI tools well will depend on building trust, being open about decisions, and following privacy rules like HIPAA.
For administrators and owners of medical practices in the U.S., AI tools for prior authorization can bring real improvements in efficiency and patient care. It is important to pick technology that fits well with current EHR and front-office workflows.
IT managers have a key role in putting these systems in place. They must make sure systems work together, keep data safe, and train users well to get the best results. New API tools and AI documentation software require smart IT plans that support automation and fast data sharing.
Using solutions such as Simbo AI’s phone automation combined with electronic prior authorization and clinical reasoning can cut down on busy work during patient intake, insurance checks, form filing, and status updates. This leads to smoother and less error-prone workflows.
Prior authorization is still a time-consuming process that affects care speed and patient happiness. AI tools such as generative AI, electronic prior authorization, and touchless approvals have shown they can greatly cut time spent, raise approval rates, lower denials and appeals, and improve workflows.
Medical practices in the U.S. can benefit by using AI tools that automate and improve prior authorization tasks. This lets providers focus more on patient care. Practice leaders should understand these technologies and choose flexible, well-integrated options to manage prior authorization challenges and support long-term success.
Prior authorization is designed by insurance companies to control the use of unnecessary and costly treatments, thereby managing healthcare costs.
Doctors and their staff spend an average of 12 hours a week submitting prior authorization requests, which contributes to the burden of administrative tasks in healthcare.
Doctors are using generative AI to streamline the drafting of prior authorization letters and appeal denials, thereby reducing the time spent on these tasks.
One physician reported that using AI increased his approval rates from around 10% to 90%, demonstrating a significant improvement in success.
Many physicians find prior authorization burdensome, which can negatively impact patient health and complicate care delivery.
Yes, there are concerns that as both insurers and doctors use AI for prior authorization, it could lead to an escalating back-and-forth in approvals and denials.
Insurance companies are exploring ways to incorporate AI into their processes and welcome technologies that can streamline the prior authorization process.
Health plans are investing in AI to automate approvals but often lack the systems to automate denials effectively, requiring human review in many cases.
An ideal UM state minimizes provider frustrations, ensures optimal quality outcomes, and is affordable, emphasizing strong relationships between health plans and providers.
Building trust and collaboration between plans and providers can improve efficiency in prior authorizations and facilitate a more streamlined care delivery process.
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