What You Need to Know
- Using one system to monitor many different types of claim information at the same time has been hard.
- AI is good at doing that.
- One benefit: AI can help companies do more to prevent problems.
The United States spends an average of $3.8 trillion per year on health care. Some estimate that fraud, waste, and abuse cost the nation at least $114 billion annually — more than 3% of overall health care spending.
It’s time for change.
Historically, health insurers, benefit plans, pharmacy benefits managers and other players focused on identifying problems after claims were paid.
Now, organizations are focusing more on pre-claim and pre-pay cost containment initiatives.
Part of that effort involves giving many different cost containment stakeholders, in many different departments, an integrated view of medical, facility, pharmacy and even dental claims.
So, what are the five best practices that health care organizations can use to create a holistic unified cost containment program?
- Adopt self-learning artificial intelligence tools.
- Create a unified view.
- Enable better detection of exposures.
- Create value-driven holistic reporting.
- Empower all players in the system to work together.
Much of this is easier said than done.
Health care payers, in particular, still face the challenges of siloed data, organizational dynamics, rigorous compliance mandates, and outdated technology. Payers also face an increase in the number of compliance mandates and audits and dependence on resource-intensive processes.
As a result, payers have fragmented views of their health care payment spectrum, reporting gaps between different departments, provider abrasion, and duplicated efforts.
All of these problems lead to missed opportunities and waste.
Self-learning systems can help, by helping organizations monitor many different information streams at once, and by uncovering existing problems and detecting emerging problems before they hit the bottom line.
It’s All in the AI
In a 2020 KPMG study on AI in the health care industry, 89% of respondents said AI is creating efficiencies.
For unified cost containment programs, AI can:
- Process large volumes of disparate data, such as claims data, and derive the insights needed to create a unified view.
- Identify behavior-based patterns and detect outliers and potential exposures as they emerge.
- Quickly identify practices that intentionally or unintentionally waste money.
- Explain new fraud schemes to the user, while gathering supporting evidence automatically.
- Build connections across data to provide actionable insights.
The power of self-learning AI is that it delivers the rationale behind identified patterns, providing details and support for decisions that health care leaders make. The sophistication of AI-driven predictive analytics enables earlier and more accurate detection of outliers and financial exposures.