How Might AI Impact Employee Benefits and Healthcare Delivery?
Employee Benefits
How Might AI Impact Employee Benefits and Healthcare Delivery?
The use of artificial intelligence (AI) is booming; it is expected to grow by more than 35% annually between now and 2030.1 It is worth exploring how businesses currently leverage AI and how they may do so in the future. Across almost all industries, there is an opportunity to automate tasks, streamline operations and administration, improve efficiency and increase productivity. The question for employer-sponsors of health plans is: How might AI impact employee benefits and healthcare delivery?
As employers continue to take on challenges around healthcare cost, access quality and overall population health, AI may be able to help drive better solutions. At this time, there are four major areas where AI could become transformative for healthcare.
- Operational and administrative efficiencies: simplified billing and claims submissions, appointment scheduling, fraud detection and improved integration of data across the healthcare system
- Improvements in employee experience: greater efficiency, personalization and sharing of medical information for more seamless care and better navigation
- Clinical enhancements: AI will not replace doctors – but AI could transform the way healthcare workers diagnose and treat patients
• Example: Some AI can read a scan, process an image or identify a rare condition more accurately than a human, which could help to reduce human error and identify innovative treatments - Empower true transparency: Recent regulations require health plans and providers to post prices through Machine Readable Files, but the files are massive and difficult to use. With increased consistency and completeness combined with AI, there may be an opportunity to marry cost and quality to make pricing data more accessible and actionable.
These four AI-driven developments could significantly and positively impact employer-sponsored health plans. However, It is important to remember that AI technology is complex and still in its infancy. There are numerous ethical and privacy concerns to consider, such as the following:
- Legal and social issues: For example, a Chatbot might steer a group of employees representing a protected class to the wrong treatment setting. Not only can this type of bias result in legal problems for the plan sponsors, but it also raises potential equity concerns.
- AI and emotional cues: A human can see body language or hear a tone of voice that might suggest anxiety or other emotional issues impacting the member that AI may not pick up on.
- Employee hesitancy: Employees as patients may not feel comfortable with AI-fueled healthcare, such as Chatbots, even if they promise greater self-service and more availability. Employers should strike a balance between AI automation and the human touch when considering plan design changes and potential enhancements.
- Security of sensitive information: AI models ingest data as they make predictions. This means the information could be stored by vendors, which brings more data security and privacy concerns for employers.
Employers should be proactive and understand how the vendors in their ecosystems use AI today or if they plan to in the future. Questions might include:
- How do you plan to leverage AI over the next three to five years? What does the roadmap look like? How has AI improved the efficiency of your operation? How could this potentially impact healthcare costs and quality for both our firm and plan members?
- How will AI provide a more personalized and engaging member care journey?
- How will AI decrease healthcare barriers and improve outcomes in diverse populations?
- How are you mitigating any AI-related bias in your models?
- What can be done to validate your AI models?
- How will we quantify success?
While there are concerns about the future of AI and employer-sponsored health plans, it is important that the entire healthcare system, including employers, understand its advantages while mitigating its risks.
