The Payment Crisis Behind Healthcare With: Monique Lappas
The financial crisis in healthcare is deeper than most clinicians and executives realize. In this interview, Monique Lappas, founder and CEO of Qualify Health, explains how hospitals lose billions annually due to denied claims, underpayments, and patient affordability challenges. Drawing from her background in finance and healthcare consulting, she outlines how AI-driven automation can identify financial assistance opportunities, reduce bad debt, and improve revenue cycle performance.
Lappas reveals how her company uses intelligent workflows to match patients with copay programs, charitable foundations, and financial aid in real time. The result is a rare alignment of incentives: hospitals recover revenue while patients avoid overwhelming medical debt. This discussion also explores systemic issues such as Medicaid reimbursement gaps, payer dynamics, and the growing burden of administrative complexity. For healthcare leaders, the message is clear: leveraging AI in revenue cycle management is no longer optional—it is essential for financial sustainability and patient access.
Episode Contents:
About the Guest
Monique Lappas is the founder and CEO of Qualify Health, a healthcare technology company focused on automating patient financial assistance. She is a CFA charterholder with an MBA from Dartmouth’s Tuck School of Business. Prior to founding Qualify Health, she held roles in investment management and healthcare banking. Learn more on her professional profile: https://www.linkedin.com/in/monique-lappas/
Key Takeaways
- AI can match patients to financial aid programs in real time, reducing bad debt
- Denied claims represent billions in recoverable revenue for hospitals
- Automating revenue cycle workflows improves both margins and patient access
Transcript Summary
Why are hospitals facing a financial crisis?
Hospitals are under pressure due to payer mix challenges, especially in states without Medicaid expansion. Many must treat uninsured or underinsured patients while receiving reimbursements below the cost of care. Certain service lines, such as emergency care or maternal health, operate at a loss.
How do pricing and reimbursement actually work?
Hospitals bill higher amounts than expected reimbursement due to contractual agreements with insurers. These inflated charges help offset underpayments from government programs and uncompensated care.
What role does AI play in solving this problem?
AI is used to scan patient schedules and match individuals with financial assistance programs based on eligibility criteria. This includes copay cards, charitable foundations, and other funding sources.
Where does financial assistance funding come from?
Many programs are funded by pharmaceutical companies and nonprofit foundations. These organizations aim to reduce patient cost barriers while ensuring treatment adherence.
Why is automation necessary in revenue cycle management?
Manual processes cannot keep up with the complexity and speed required to secure funding. AI enables real-time identification, enrollment, and claims submission, which would otherwise require large teams.
What are the biggest inefficiencies today?
Hospitals often lack staff to pursue small-dollar patient balances while also managing high-value prior authorizations. Additionally, many denied claims go unappealed due to administrative burden.
What risks are emerging in the near future?
With the expiration of ACA subsidies, more patients may lose coverage or fail to pay premiums, leading to retroactive claim denials and increased self-pay burdens.
Can AI improve both patient and hospital outcomes?
Yes. AI enables hospitals to recover revenue while reducing financial stress on patients. In one case, a $300,000 patient bill was fully covered through retroactive assistance programs.
More Topics
- AI in Patient Care
- AI in the Healthcare Industry
- AI and Medical Innovation
- Healthcare Ethics and Policy
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