The Future of Healthcare: How Artificial Intelligence is Impacting Medical Practices

Artificial Intelligence (AI) is changing how the world works with data. Its ability to analyze, decode, and draw predictions from enormous datasets makes it a tremendous asset to any data-heavy sector – healthcare among them. But while most clinicians are likely to associate AI with lofty, yet-to-materialize efforts to eradicate cancer, AI actually has dozens of real and immediate applications that healthcare professionals can take advantage of right now.

AI Means Efficiency and Cost Savings

There are myriad use cases – potential and proposed – for AI in healthcare, ranging from robot-assisted surgery to virtual nursing assistants. But for clinicians working in a practice or a smaller hospital, several ready-to-implement use cases come to mind. Thanks to its ability to categorize data, AI can be an enormous diagnostic asset, helping with image enhancement and analysis, or drawing predictions from patient medical records and genetics. When combined with NLP (Natural Language Processing), AI can also be a powerful tool for assisting with medical coding and billing, along with compliance issues. Currently, coding errors are estimated to cost between $17-29 billion each year. Introducing AI into your office could be a tremendous cost and time saver. Clinics that implement AI have the added benefit of being able to use the technology as a key market differentiator.

Implementing AI in Your Office

AI has the potential to dramatically reduce costs and inefficiencies while also improving accuracy and quality. However, knowing when and how to implement AI is key. For small, unique projects or projects with very little data, AI can be cost-prohibitive or not particularly accurate. That’s because AI becomes more accurate and effective the more data it has to work with. However, if your clinic or hospital is working on a large-scale project or is regularly doing a simple, repetitive task, AI can be a viable solution. Medical coding, for example, can be easily streamlined using out-of-the-box tools tweaked for your particular situation. For diagnostic and medical imaging problems, AI can provide a digital “first look” or “second opinion.” In both cases, the ROI can be absolutely worth it.

Here’s what to ask yourself before considering implementing AI in your office:

  • What’s the business case? AI has to make sense from both a technological and business perspective. If there’s a cheaper, easier way to get the same result, try that instead.
  • Do you have enough data? The bigger the dataset, the more effective AI is. If you’re working from a small dataset, AI might not be the solution. For problems with huge datasets, such as medical coding, AI can be a great investment.
  • Is the problem an “AI-friendly” problem? AI deals with probabilities. It’s great at drawing trends, identifying patterns, and predicting outcomes as a result. Text- or image-based problems are AI-friendly and can get good results.
  • How will AI fit into your workflow? AI isn’t going to replace great workers anytime soon but it can augment their skills. Think of it as a “helper” to your existing staff, and always make sure your workflow includes room for a human to make the big decisions.
  • How will you get buy-in? You might have incredible technology at your fingertips, but the human element can be the tough part. Figure out how you’re going to “sell” the solution throughout your organization so that people actually use it the way you intend.

There are exciting things ahead for AI in healthcare, but some of its crowning achievements are already with us. Implementing tried-and-tested approaches such as AI for medical coding or AI for medical diagnostics can deliver great results for your clinic and position you at the cutting edge of healthcare.