Ours is an exciting era. Robots can do brain surgery, and search engines may know you have cancer before you do. But in all the high-tech hype, it seems like artificial intelligence (AI) gets the spotlight when it comes to diagnosing and treating patients — yet not so much when it comes to insuring them.
Perhaps reasonably so. AI has lifesaving potential: Experts estimate that algorithmic learning could boost health care outcomes by up to 40 percent. But here’s the other piece of that: It could do it at half the cost. That cost savings impacts everyone, from doctors and insurers to employers and their employees.
It’s a win-win-win: Powered by predictive analytics and machine learning, artificial intelligence can not only optimize your health benefits, but it can also lead to a healthy, happier workforce — all while helping your bottom line and your workers’ wallets. Here’s how three applications of AI could do just that.
Predictive Customer Service
Thanks to big data, it’s becoming much easier to predict when policyholders might need a little extra customer support as they navigate their health plan, as Healthcare Finance reports. Timing has a lot to do with that — both the time of year (as with open enrollment) and the time of life (such as when you have children). Each can shepherd in a barrage of questions related to claims, paperwork, tax implications and more.
That’s where AI comes in, both predicting when employees will have questions about their benefits as well as proactively reaching out and solving their problem before they even realize there’s a problem to solve. According to a report from PricewaterhouseCoopers, improving customer experience ranked second among what businesses most hope to get out of AI technology (behind revenue and profit growth).
It’s a level of customer service that’s hard to pull off with humans alone — but with automation your employees could get a seamless experience, and you could get the benefit of a satisfied workforce with the tools to make the most of their health benefits.
Wellness Where (and When) It’s Needed
Deploying an uninformed wellness program just for the sake of having one won’t do you many favors. But what if you could provide wellness-centered benefits to employees based on their individual needs — like smoking cessation for smokers or substance use support for addicted employees prone to relapse?
By instantaneously reviewing insurance claims data to spot trends and patterns, AI can help — and not just with suggesting lifestyle programs to manage addiction. Machine learning can also identify people on the brink of getting a chronic condition and serve up resources to help prevent those issues altogether. For example, a prediabetic employee might receive glucose management support, or someone with high cholesterol may get access to a series of heart health tools. Such services could significantly enrich an existing health insurance plan with little additional effort or money.
Time, Resource and Cost Efficiency
Sorting through insurance data, such as claims and prior authorization requests, is a taxing and highly manual process. McKinsey describes how machine learning could speed it up, scanning paperwork at a breakneck pace and using prior patterns and data to apply to new claims and authorization requests for faster review.
It may also help identify components of a health insurance plan that are underutilized. From there, AI could either offer insights-informed ways to optimize them or cut them entirely and reinvest those savings into something that employees may need more, like mental health coverage or wellness programs. AI could also be a strong partner in the fight against health care fraud, a multibillion-dollar problem.
All of this snowballs into cost efficiencies, both for the insurer — who passes savings back to the employer by way of reduced premiums — and for the employer and their employees — in the form of a healthier, more productive workforce. Technology is prevalent in almost every area of business, and as great as robotic surgeons are, it’s time to expand advanced health care tech beyond the doctor’s office.
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