How Digital Prior Authorization Is Improving Patient Care

The COVID-19 pandemic has had a devastating impact in the U.S. and around the world. It also has been a major catalyst for healthcare innovation in many ways because it has laid bare the inefficiencies and inadequacies of this country’s existing system.

A nation that can send people to the moon (and potentially to Mars) was unable in 2020 to get ventilators to people who were dying of COVID. Further, we were incapable of getting needed resources to frontline workers trying to treat pandemic victims. These failings have sparked an increase in funding for technologies that are changing how healthcare is delivered.

Innovative use of these and other modern technologies can transform how we address one of healthcare’s biggest challenges—effective collaboration among all constituents toward the best patient outcomes. Arguably, the biggest challenge in healthcare is that there are so many interconnected parties—hospitals and other various medical facilities, surgical centers, nursing centers, physician offices, insurance companies, pharmacies, manufacturers—but poor standards by which they all collaborate. Such lack of collaboration results in delayed or unnecessary care, driving both unnecessary expense and suboptimal patient outcomes.

Getting health plans, providers, and patients working together on a single IT platform that leverages artificial intelligence (AI), machine learning (ML) and real-time analytics—combined with deep, evidence-based clinical expertise—can guide all stakeholders to the best care choices without unnecessary delays, thus promoting the best and quickest outcomes.

A prime inhibitor of effective care collaboration is prior authorization (PA). PA can delay care by days or weeks because of heavily manual processes that don’t effectively utilize technology to drive collaborative activity. A survey of physicians by the American Medical Association (AMA) shows that:

• 79% said the lengthy PA process has caused patients to abandon treatment
• 30% said PA delays have resulted in a serious adverse event for a patient in their care
• 21% said PA delays have led to a patient’s hospitalization

The PA process exacts a huge toll on clinicians and their staff. Practices complete 40 PAs per physician each week, according to the AMA survey, while physicians and staff spend two full workdays each week filling out and submitting PAs. Compounding the problem is that PA requirements differ among health plans, making it hard to establish a consistent workflow. Frustration and resentment over PAs have contributed to clinician burnout, which impacts from 40% to 54% of physicians in the U.S., based on several studies cited in a 2019 report by the National Academies of Sciences, Engineering, and Medicine.  Health plans also suffer.  Manual UM staff clinical reviews are extremely expensive, and are subject to human error, which can affect care quality and outcomes.

Federal and state governments are responding with new regulations intended to accelerate and standardize the PA process. A new rule published last December by the Centers for Medicare and Medicaid Services (CMS) is designed to “improve the electronic exchange of healthcare data, and streamline processes related to prior authorization, while continuing CMS’s drive toward interoperability, and reducing burden in the healthcare market.” CMS expects this new rule to go into effect on Jan. 1, 2023, which is less than 17 months from now.

More immediately, in Texas, a new regulation that went into effect Sept. 1 of this year enables providers who achieve above 90% approvals to skip the authorization process altogether. Removing the ability to monitor care quality and costs will dramatically increase unnecessary medical expense, which could also drive higher premiums—and higher costs for members—not to mention less protection from unnecessary prescriptions, implants, and other potentially harmful services.

Although interoperability, data exchange, and manual processes remain ongoing challenges, technology exists today that not only dramatically speeds up the PA process via digital automation, but also transforms the process into one that proactively encourages the best care, without delays and unnecessary costs, while ensuring patient safety.

Automating the administrative processes involved in PA—such as faxing, inbound calls, and filling in missing information—vastly reduces the amount of time clinicians and staffers must spend on each request to authorize a medical procedure or treatment. This frees up more time for clinicians to spend with patients and for staffers to focus on higher-value activities. There are solutions that speed the process this way, but they often can’t reduce the clinical review workload. Web portal-driven processes that are supposed to automate the clinical review process (the heart of PA) often send at least 50% of requests to health plan clinical staff for manual review anyway. Clearly, the portal solutions don’t do much more than the fax machine!

A digital PA platform that includes AI and natural language processing (NLP) can immediately authorize many procedures and can also identify those PA codes for which PA no longer may be necessary. For PAs that can’t be automatically approved, AI and NLP can expedite the clinical review process, should one be required. The PA process also can be made more efficient by using analytics to stratify providers based on performance, and by fast-tracking PA approvals for those providers with the highest ratings. So, as opposed to the Texas regulation, it’s possible to “greenlight” high-performing providers while still retaining or even increasing the avoidance of unnecessary medical services and costs.

In addition, AI, ML and NLP can be deployed to interpret and categorize unstructured data in electronic medical records (EMRs), enabling insurance plans and providers to overcome another major barrier to improving care and accelerating PA decisions.

Finally, AI-driven digital PA platforms can integrate information from professional medical organizations regarding evidence-based care paths for specific procedures to inform PA and treatment decisions. Combined with data about the individual patient, this evidence-based information can be used to ensure better clinical outcomes and an optimized care plan that reduces costs. Behavioral economics has major applications in changing practice behavior as well.

Technology change can be slow and grudging in the healthcare industry. But with impending PA regulations and accelerated use of innovative technologies post-COVID, health plans have an excellent opportunity to transform how they process PAs in a way that works best for patients, providers, and health plans. Digital prior authorization that makes innovative use of modern information technologies can be the catalyst for this transformation, while regulations will end up costing everyone in the system.