Artificial Intelligence (AI) is poised to transform the healthcare payment lifecycle from the patient access point through EHRs and then through the entire reimbursement process. The true promise of AI is the ability to harness massive amounts of unstructured data and filter it into actionable insights at lightning speed, far outperforming a manual process. Focusing this power on prior authorization, insurance eligibility, and patient pay estimation will greatly improve the patient experience and positively impact the bottom line.
Using machine and deep learning methods, AI-enhanced patient access systems would be capable of using information from the EHR and identifying and tracking multiple patterns, and through intelligent algorithms and iterative processing, develop real-time decision filtering and refining methods. From prior authorization to determining a patient’s insurance eligibility, AI can ascertain necessity, interact with payer platforms, and perform follow up electronically.
AI and Patient Access
Once you bridge the provider/payer integration component, AI-assisted software would be able to access its large comprehensive data set based on the patient’s current EHR information to determine vital criteria and move the scheduling process forward quickly. The impact on hospital admissions or provider intake processes would be monumental in both speed and workflow.
By automating the patient access process, the following functions would execute seamlessly and reduce the provider and patient frustration now felt in a manual encounter:
- Prior Authorization (PA)— AI would deliver real-time decisions on necessity per patient encounter, submit PAs to the appropriate insurance payer, and monitor and follow up on progress ultimately notifying appropriate personnel when scheduling could commence. Individual cases that were at risk of denial or were emergent in nature could be directed to a specialized team of experts to be hand processed.
- Insurance Eligibility—Patient insurance coverage would be entered in the EHR and then verified electronically, reducing the need for employees to spend time on the phone or accessing multiple payer portals, each with their own logins, passwords, and processes.
- Patient Pay Estimates—Utilizing a vast database of contracted insurance rates per procedure and matching that with anticipated CPT codes, patients would be made aware
of their portion due before the scheduled visit/procedure and would arrive prepared to pay, greatly reducing the back-end follow up required without automation.
Beyond the expected improvements to be recognized, such as timely and accurate prior authorizations and clean claims available with factual and specific insurance information, the following will occur:
- Increased Patient Engagement—In what is becoming a more consumer-driven industry, automation will meet the demands of patients and lessen the disappointments brought with rejected prior authorizations, eligibility surprises, and back-end financial and collection concerns.
- Reduced Staff Time—AI has been credited with reducing staff workload by over 70% by automating previously manual functions and eliminating needs for follow up.
- Reduced Denials—Denials management would be drastically reduced with the improved PA system.
- Reduce AR Days Outstanding—Directly impacting the balance sheet and bottom line, AR days outstanding would be significantly lowered relieving reimbursement and collection challenges.
ROI on AI
As recently discussed in Healthcare Finance, 91% of healthcare executives expect AI investments to provide positive ROI within four years, with a full 38% expecting ROI in three years or less. This level of anticipated success and early adoption is unprecedented in the healthcare industry and is even being cited as a reliable path toward healthcare affordability.
We are at a tipping point with AI and the industry is already seeing trends toward systems planning, strategy development, and workflow analysis in anticipation of automated improvements. We are heading swiftly towards implementation with an average $33M anticipated to be spent per healthcare system to upgrade and position themselves for AI success.
Want more information? Act now to schedule a demo and decisively improve your automated patient access workflow.