How much can AI in healthcare improve the Pre-auth Burden?

Prior authorization is a delicate administrative procedure of the medical industry. While sometimes it is referred to as the “necessary evil,” it significantly affects the patient clinical outcomes as well as the payer-provider relationship. Provider organizations have repeatedly complained about the issues of pre-authorization of procedures, but not much progress has been made so far. In 2021, the CMS proposed interoperability rule might bring profound positive changes that all stakeholders were looking for. Changing the system to electronic prior authorizations can benefit the health systems in several ways, but are they ready to adopt the massive changes with AI in healthcare?

While the health systems are still struggling to implement the current rules, they are optimistic that the change was long due, and they will put in their best effort to realize its full potential. But how has does AI in healthcare practically progressed? Can it be implemented right away? What are the issues that the AI-backed systems still need to overcome?

This article will take you through the entire spectrum of prior authorization, how AI can help change it for the better, and the gaps that still need filling.

Realistic Benefits of AI for Pre-Auth

When we say realistic benefits, we mean the advantages that the health systems can leverage to improve their prior authorization systems with the AI-based systems already developed. Here is what the healthcare leaders feel:

  • The current pre-authorization system through phone and fax is highly time-consuming for the administrative staff. While the time spent will come down, the costs will also decrease, improving the health system’s finance.
  • The staff will be able to see which of the procedures mentioned in the medical records require the prior authorization of the payer network. This will significantly reduce the delay caused due to documentation confusion.
  • The system will also show the particular procedures required for the prior authorization process so that there is a reduced chance of denial due to missing papers.
  • The single-point software solution will be another great benefit for hospitals. They can forward their prior authorization request through a single system without transferring data from one point to the other. It will reduce the costs and simplify the administrative workflow.
  • With the streamlined procedure in place, the time required for the request assessment will significantly come down. This will help the health systems provide better clinical outcomes for their patients while the patients do not have to wait too long to complete the process.
  • On the payer side, they can review the documentation in a standardized way because the EMR details will be included along with the pre-auth request coming their way.
  • Implementing the electronic mode of the pre-authorization process will improve the payer-provider-patient relationship by promoting transparency, which is one of the critical goals that CMS has been trying to achieve.

Scalability of AI in Healthcare

While some healthcare organizations and Accountable Care Organizations (ACO) have already started incorporating advanced technology-based workflow management systems into their system, a large part of the industry is still wary about a non-human system making decisions. Keeping the risks in mind, here is some scalability where AI can help.

  • The algorithms used in the systems are accurate as they have been developed and made public after several rounds of trial and error.
  • Artificial intelligence eliminates any subjective error that might crop up when the entire process is done manually.
  • It can also help interpret the complex medical policies so that the decision-making is evidence-based and accurate.
  • The majority of the leaders who are not confident about the AI system are afraid of any wrong decisions that the system might provide. Compared to the existing manual pre-auth system, the mistakes of AI are predictable and can be fixed easily with data.
  • If the AI system shows particular bias in the decision making process, developers can update the programming to get rid of it.
  • Apart from all this, the healthcare interoperability systems need to adhere to the HL7 FHIR standards as put forward by CMS. This will help scale up your patient data security while realizing benefits from the electronic mode of pre-authorization.
  • Overall, AI in healthcare can help you scale your organization’s workflow with its real-time bias-free results.

Importance of Data Insights for the Right Implementation

Collection and analysis of data are the two main ways in which the future world will work. The same holds for interoperability and, in turn, AI in healthcare for pre-authorization.

  • Evidence-based care needs the correct data to move forward. For the AI systems to give you the right results and better clinical outcomes, they should have access to a range of data so that they can evaluate different unique situations.
  • In the case of prior authorization, it is elementary to prioritize the medical conditions of the patients to move forward with the process.
  • AI systems can go through the existing data and cross-reference it with a natural language processing system to assign the level of priority to the patient.
  • For example, MCG Health developed and used such a platform called the Indicia for Effective Focus. The solution made use of the clinical data insights in a way that the time consumed for the patient approach came down significantly, and the utilization staff could move forward with their administrative work as per the priority status of the patient.
  • Several health systems are also tying up with health-tech start-ups to come up with customized solutions. It is a kind of symbiotic relationship where the start-ups develop the product with the help of the use cases and other data provided by the health systems.

Overall, every sector of the healthcare industry is pushing forward to improve the AI models in healthcare. The evidence shows that these innovations coupled with interoperability can be a game-changer for prior authorization. However, there is still a long path to go before electronic pre-authorizations become the common rule with the help of sophisticated AI systems.

We hope that this blog helped you understand how AI in healthcare can improve the pre-authorization burden of the healthcare systems. Please subscribe to our blog to know more news and articles on healthcare, medical billing, and technology. Follow us on LinkedIn, Twitter, Facebook, and Instagram to get regular updates.





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