Dynamic copay health plans, AI-enabled price transparency, and member experience

Area of Science:

• Health Economics
• Healthcare Management
• Health Insurance Policy

Background:

• Rising healthcare costs and complex cost-sharing present challenges for patients.
• Traditional healthcare consumerism models have limitations due to difficulties in observing quality and estimating real-time prices.
• Employer plan designs have evolved from broad networks to include strategies like reference pricing and dynamic copays.

Purpose of the Study:

• To review the evolution of employer health plan designs.
• To examine the operational aspects and potential impact of dynamic copay plans on out-of-pocket spending predictability.
• To propose a combined strategy of dynamic copays, reference pricing, and tiered networks for improved healthcare value.

Main Methods:

• Review of employer plan design evolution, including Preferred Provider Organizations (PPOs), tiered networks, and reference pricing.
• Analysis of dynamic copay plans, utilizing Transparency in Coverage data and AI-enabled analytics.
• Case study examination of UnitedHealthcare's Surest plan to assess copay integrity and effects on spending.

Main Results:

• Dynamic copay plans translate negotiated price variations into pre-service, provider-specific dollar copays.
• Potential for improved out-of-pocket (OOP) predictability and spending control, though constrained by health insurance literacy and limited shoppable services.
• Evidence suggests tiered designs have mixed effects on spending and predictability.

Conclusions:

• Pairing dynamic copays with reference pricing on a tiered network may enhance steerage towards higher-value care.
• This integrated approach could improve out-of-pocket predictability and align member incentives with cost-effective healthcare choices.
• Addressing limitations of health insurance literacy and the scope of shoppable services is crucial for long-term effectiveness.