The use of AI in healthcare continues to grow. While adopting AI is clearly a big decision with a lot of moving parts for any hospital, it’s particularly tough for standalone and mid-sized organizations that don’t have the backing of a larger system.
At this point, nobody needs to be convinced about the power of AI. But for hospitals of a certain size, pulling the trigger on adoption isn’t easy.
Cost is an obvious factor, especially when you don’t know when the actual ROI might start coming in. Internal ownership is another concern. Who’s going to own the necessary updates when the IT team is already stretched to capacity? And of course, there’s governance, probably the most worrisome aspect. Larger hospitals are forming in-house oversight teams, but smaller hospitals typically don’t have that luxury.
Any one of these factors is probably manageable on its own. But add them up, and the AI decision becomes far more complicated and daunting. Meanwhile, the problems AI can help with, like denial volume and aging A/R, just get worse.
We put together a checklist that tackles the biggest barriers keeping standalone hospitals from moving forward with AI, and provides a resolution for each one.
Access the full checklist here.