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AI-Based Solution Reinvents Revenue Cycle

TRISH’ Identifies and Reduces Revenue Leaks

A new artificial intelligence (AI)-based application promises to reinvent the revenue cycle for hospitals and healthcare organizations by building a “digital employee” that will recognize vulnerabilities in an organization’s revenue cycle and reduce errors that impact profitability.

Trusted Revenue Innovation for Smart Healthcare – TRISH – will analyze the areas of the revenue cycle that are most problematic for healthcare organizations: eligibility, authorizations, pre-certification, claims status, and the like. TRISH will reduce the administrative burden without human intervention, learn & adapt as new variables are introduced and ensure accurate reimbursement without endless iterations of re-work.

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TRISH is the result of a joint venture between the Healthcare Advisory Group of Windham Brannon, the Atlanta-based accounting and consulting firm, and Deep Indigo, a data science firm with proven success delivering artificial intelligence (AI) and machine learning (ML) solutions across multiple industry verticals. The joint venture is called SHOAR Health, LLC (SHOAR, for Smart Health Operations and Revenue Solutions).

“The revenue cycle is extremely rigorous,” Windham Brannon Healthcare Practice Leader Valerie Barckhoff said. “HIPAA laws back in 1996 gave us an outline for how to communicate the pieces back and forth, but healthcare organizations still struggle to manage the data. Reducing errors and inefficiencies can ultimately reduce the cost of doing business for healthcare organizations, increase revenue, and allow hospitals to focus on taking care of patients,” Barckhoff said.

Barckhoff teamed up with Vipin Ramani, of Deep Indigo, to match her extensive revenue cycle expertise with his AI/ML expertise to develop TRISH. Ramani holds B.S. and Ph.D. degrees in Electrical Engineering and AI from Georgia Tech and holds more than forty (40) patents. He has created applications for industries spanning financial services, law, accounting, government, manufacturing, transportation, and retail. His AI/ML solutions have been deployed at organizations like Bank of America, the United States Air Force, and Northrop Grumman.

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In healthcare organizations, key areas that create revenue leaks include:

1. Poor front-end data
2. Missing or delayed referral
3. Missing prior authorization
4. Ineffective use of billing edits
5. Lagging collection times
6. Inconsistent follow-up
7. Poor denials management

Each of these areas represents a function typically rife with administrative confusion, significant human staff intervention, and frequent re-work. Accurate reimbursement is compromised, and, in many cases, patient care is impacted by preventable delays and uncertainty. TRISH promises to correct and automate the associated workflow and free staff to pursue higher value efforts.

As Barckhoff says, “Go into most business offices and less and less will you find staff on a phone with an insurance company. Rather, they will be clicking through a payer web portal to secure an authorization, provide requested documentation, or seek a claim status day by day. With TRISH, the authorization request will be initiated automatically, and TRISH will continue to seek that approval until it is secured and held for eventual bill drop and payment.”

True AI/ML technologies remain basically non-existent within healthcare provider environments. What exists today is largely robotic process automation (RPA) that requires ongoing rule maintenance and significant human intervention to achieve successful outcomes. SHOAR is actively implementing TRISH in select client environments and remains available to deliver TRISH to interested organizations regardless of size or geography. The implementation process is relatively short, involving a comprehensive workflow analysis and customization of the ML tools to meet the specific requirements of each client’s unique workflow needs – becoming a true complement, rather than burden, to a hospital’s existing human staff.

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