Your customers have spoken. They want more coordinated, seamless, and holistic healthcare, according to a 2022 Health Care Insights Study from CVS. And as a payer, you are subject to the same expectations facing providers. People expect their insurers to know them both clinically and operationally, while delivering the same omnichannel experiences they enjoy in retail, restaurants, and other settings.
Operational, industry-wide cost pressures, coupled with customer demands, continue to push payers’ investment in modernization. To implement modernized experiences, payers are prioritizing analytics and emerging AI technologies.
According to the 2023 Gartner® U.S. Healthcare Payers’ Emerging Technology Priorities and Progress by Use Case, “while only 7% of U.S. healthcare payer organizations have fully deployed generative AI and large language models to resolve member self-triage, 35% of payer leaders already cite this technology as a top priority.”1
To hear more about how payers are closing their transformation gap, click here to listen to a recent conversation between payer executives and Point B leaders.
Asking the Right Questions
In this ecosystem of emerging technologies, it can be tempting to start with the solution instead of the problem. But before implementing specific AI applications or data and analytics capabilities, outlining the potential impact on payers, providers, members, and other stakeholders is a critical first step:
- What will help patients live healthier lives?
- How can you improve engagement with providers, members, and brokers?
- How might you enable more real-time, personalized customer experiences?
- Where is there room for operational efficiency within the healthcare ecosystem?
- How can your organization make better use of data to understand who's at risk from a clinical standpoint?
How Payers are Leveraging Data & AI Today
To improve the member experience, payers have addressed high call center volumes by embedding AI-powered chatbots on their websites to help answer questions about benefits, incentives, and other health plan information. Innovations around prior authorizations are also being explored to increase transparency and ease the burden on providers, making it easier to become a payer of choice. Customer experience improvements like these are critical for keeping pace with changing customer expectations and moving beyond price as the key determinant of perceived value.
Beyond operational applications, payers are leveraging advanced predictive analytics to build models that help drive improved targeting and engagement across all clinical touchpoints. Similar innovation specific to disease progression will help payers model and forecast disease progression more accurately and effectively when refining care plans.
Even with these, payers are understandably hesitant to fully invest in AI-driven solutions. Payers need to see rapid cost savings from AI innovations due to the increasing pace of employment changes that lead to shifts in membership. Although healthier members mean lower medical costs and reimbursement rates, if less expensive coverage is not realized within a few years, payers will opt for a more conservative investment in AI.
These considerations highlight the need for intentional investment and use of AI—payers need to identify where AI will have the most impact for their organization.
Implementation Best Practices
Ready to implement and scale a new solution? Whether you're working with a member-facing or internal tool, here are some best practices to consider as you get started:
Connect innovation to your mission and purpose
Building a compelling narrative about the value of emerging technologies is essential. Ultimately, analytics, artificial intelligence, and automation should be a massive catalyst for growth and experience improvements across the industry, but they should serve a clear purpose. Ensure your solutions deliver on your organization’s mission and purpose to avoid building a segmented customer experience.
Start with great data
Within the payer landscape, everything starts and ends with an organization’s ability to access and leverage quality data. When it comes to harnessing the power of AI or analytics capabilities, better data means better outcomes. As you ideate for the future, consider ways to create a data supply chain that more effectively and repeatedly delivers the data your organization needs to feed new solutions.
Avoid scope creep
Be intentional about your organization’s change strategy by committing to a fixed-scope proof-of-concept (POC) to demonstrate a new technology’s impact. From there, build on initial learnings from the POC to properly refine and scale the solution.
Plan for iterative optimization
Consider how your organization will track and report on the impact of technology integrations on stakeholder experiences. The ability to measure and benchmark improvement is just the starting point. Gathering stakeholder feedback to better understand impact while finding opportunities to iterate, test, and improve the customer experience is essential.
A Constant Amidst the Change
Every day, the tools powering our healthcare experiences continue to change. There’s no shortage of innovation opportunities that healthcare leaders must evaluate to determine if they are worthy of investment. But there is a tremendous potential upside. When implemented successfully, these new solutions are a prime opportunity to leverage next-generation technologies while exceeding customer expectations.
While healthcare technology will continue to evolve, the desired outcome remains the same: To provide more effective, timely, impactful care across the healthcare ecosystem.
1Gartner, U.S. Healthcare Payers’ Emerging Technology Priorities and Progress by Use Case, By Mandi Bishop, Published 22 December 2023
GARTNER is a registered trademark and service mark of Gartner, Inc. and/or its affiliates in the U.S. and internationally and is used herein with permission. All rights reserved.
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