Introduction

Many healthcare providers may prescribe treatments that are not considered routine or may be expensive, an insurance company may need prior authorization (PA) to determine whether they will cover what the healthcare providers recommends. The healthcare provider must get approval from the insurance company. The use of a PA aims to reduce costs and manage the use of certain healthcare services for the insurance company. The goal of PAs is to ensure patients receive the most appropriate care for their medical needs in agreement with the most up-to-date medical evidence and guidelines. Prior authorizations can be very time-consuming, as they require documentation and paperwork from healthcare providers to show why the patient would need the treatment.

The rapidly evolving field of healthcare is now experiencing the growth of artificial intelligence (AI) in administrative processes has become increasingly common. AI is a growing technology that simulates human intelligence within machines. In the healthcare field, many organizations are actively incorporating AI technology into different aspects of the field such as diagnostics, medical imaging, and lifestyle management, towards enhancing overall care delivery. This advancement holds immense promise for healthcare, offering the potential to deliver consistent, high-quality, and efficient outcomes for patients. 

AI-driven automation can expedite the approval process, making access to prescribed medications more readily available to patients.  Additionally, the implementation of AI in prior authorizations offers the potential to significantly reduce the administrative burden on healthcare staff, allowing them to allocate more time and resources to direct patient care. 

ACCESS TO NECESSARY MEDICATIONS

Automating AI in prior authorizations may provide necessary benefits to the improvement of patient care. By implementing AI technology, healthcare providers, and insurance companies can smooth the prior authorization process, ensuring patients receive timely access to essential medications. AI could quickly analyze patient data, treatment histories, and insurance policies to determine if prior authorization is required, expediting the approval process, and reducing delays in medication delivery. AI decision support systems could also assist healthcare providers in selecting the most appropriate medications based on the most up-to-date clinical guidelines, specific to each patient. AI systems can assist pharmacists in selecting the most appropriate medications based on clinical guidelines and insurance requirements, increasing the likelihood of approval upon submission for prior authorization. AI may allow pharmacists to provide correct guided treatments that are covered without PA and provide feedback on the drug of choice based on what the insurance could possibly cover to physicians or other healthcare providers. This helps ensure that prescriptions are more likely to receive approval upon submission for prior authorization, minimizing the risk of medication denials or delays.

TIMELY APPROVALS

Traditional manual prior authorization processes often experience lengthy delays, due to paperwork and documents that are required to be submitted by prescribers, preventing patients from receiving the necessary care they need. The 2018 American Medical Association Prior Authorization Physician Survey revealed that 26% of providers reported waiting up to 3 days or more for a PA decision from health plans. Patient adherence to their treatment often declines when delays like postponements or additional steps are shown to them. 

Automating the PA process using AI can be engineered to expedite the approval process for healthcare providers, ensuring patients receive timely access to medications. Improving patient satisfaction and enabling healthcare professionals to focus more on delivering quality care rather than going through administrative hurdles. Patients could experience reduced wait times at pharmacies and quicker access to their prescribed medications. Healthcare providers can significantly expedite the approval process which could be seen with patients spending less time waiting for approval and fewer delays. Improved treatment adherence can lead to better health outcomes, as patients are more likely to follow their prescribed medication plans consistently. 

REDUCING THE ADMINISTRATIVE LOAD ON HEALTHCARE STAFF

AI has the greatest potential to create a generation of PA workflow design. AI may help organize information from electronic health records (EHR), emails, policies, medical protocols, and other sources, vastly reducing time-consuming tasks involving searching, collating, and cross-checking information that was traditionally done manually. AI can automate documentation processes, generating and populating prior authorization forms with relevant patient information. AI-enabled systems free up valuable time and resources for healthcare staff, reducing the administrative burden on healthcare staff, and allowing them to focus on patient-centered care rather than paperwork and submissions. 

Electronic prior authorization was created and accelerated the exchange of information between payers and providers. An authorization automation engine can be applied to elements to consolidate information to healthcare staff (e.g., automated eligibility determination, clinical rationale based on historical PA decisions, annotation and highlights of relevant information, visualization of patient medical history, suggestions for requests (additional information about treatment, step therapy, and alternative treatment; all with up to date supporting clinical literature), and integration with case management workflow).

CHALLENGES TO OVERCOME

When it comes to AI in the world of healthcare there are many changes already occurring and changes that are waiting to occur. AI will certainly have a transformative effect on PA. Patient privacy and data security must be kept as a top priority in the development and deployment of healthcare AI in prior authorizations.

AI companies will need access to EHRs, which requires both strict data privacy regulations and a design effort to ensure interchangeable access among different EHR software applications and platforms. Industry participants and companies will need to work together and define standard guidelines for attachments, data templates, and data exchange protocols as another important prerequisite for PA automation. The approaches, and regulations related to storage, control, and ownership of EHRs will significantly affect the degree of automation that can be achieved in the PA workflow. 

It is also important to ensure that training data sets for the self-learning AI do not have unforeseen biases that could result in unintended or inappropriate decisions for minority populations and lower socioeconomic status. AI could discover associations that have not yet been detected by humans and make predictions that differ from prevailing knowledge and expertise, resulting in some currently accepted practices being abandoned, and practice guidelines being adjusted. 

The use of AI in administrative processes is becoming vastly prominent within the field of healthcare. Many organizations are actively incorporating AI technology into different aspects of the field offering efficient health-related outcomes for patients. Automation of AI could possibly expedite the approval process allowing patients to receive their medications promptly and reduce the burden of documentation and paperwork for healthcare staff allowing them to allocate more time and resources to direct patient care. 

References:

1. Al-Haque, S., Khanna, V., Mandal, S., Rayasam, M., & Singh, P. AI ushers in next-gen prior authorization in healthcare. 2022. McKinsey & Company. https://www.mckinsey.com/industries/healthcare/our-insights/ai-ushers-in-next-gen-prior-authorization-in-healthcare#/ 

2. Lenert LA, Lane S, Wehbe R. Could an artificial intelligence approach to prior authorization be more human? J Am Med Inform Assoc. 2023;30(5):989-994. doi:10.1093/jamia/ocad016

3. Morgan Bojorquez et al., “Electronic prior authorization,” CoverMyMeds, 2020.

4. Myndshft. The Ultimate Guide to Prior Authorization. 2023. https://www.myndshft.com/the-ultimate-guide-to-prior-authorization/#how-long-does-prior-authorization-take