What Defines AI Implementation? Three Things to Know

What defines AI implementation in healthcare?

AI implementation involves leveraging the full potential of algorithms, deep learning, technology innovation and investment to improve workflows and capabilities within the medical practice.

When considering implementing artificial intelligence (AI) in your practice, the many different definitions, components, and processes involved in AI integration may seem daunting. Before you start with your implementation there are three things you should consider: your need for AI, choosing the right AI vendor, and integrating AI into your workflows correctly.

Understand your need for AI implementation

The right AI strategy looks at the various touchpoints that will be impacted by the implementation, the overall objectives that the practice wants to achieve, and which factors are critical for long-term success and practitioner uptake.

The discussions around AI are often around very broad terms: “AI will change the world” or “AI will revolutionize medicine.” While these claims may be true, it’s hard to get a sense of what exactly AI can do for you and your practice. Developing an AI strategy first requires that you unpack the AI products that suit your needs. Triage and notification algorithms, for example, are well-equipped for radiology practices with large imaging volumes. These algorithms analyze studies and prioritize cases that require urgent attention, for example intracranial hemorrhage. 

Care coordination solutions with integrated AI, on the other hand, are suited for emergency departments that use multidisciplinary teams to handle certain conditions. These algorithms automatically alert teams of conditions such as pulmonary embolism that necessitate fast and coordinated treatment.

There is immense value when it comes to AI in healthcare; it can really grab hold of the value hidden within huge datasets. And as a recent article entitled: “The rise of artificial intelligence in healthcare applications” emphasizes, it can provide substantial improvements

Choosing an AI vendor

The medical imaging industry is saturated with AI vendors. Choosing the right AI vendor requires careful consideration of factors such as expertise, track record, and capability.

Hundreds of companies have raised more than $1 billion dollars to develop various AI solutions that meet the needs of a growing industry. Knowing how to differentiate between vendors is important, and there are various methodologies you can employ to evaluate them. First and foremost, it’s important to choose a vendor that has market traction. Ensuring the AI company has a proven track record in live clinical environments and has shown value across different workflows and organizations. Identify vendors that have demonstrated seamless and comprehensive AI integration as this is critical to sustainable and capable integration across the organization.

Regulatory clearance is also an essential factor. There are only a handful of companies have FDA approval and/or CE marks for their AI solutions, and it’s important to choose a vendor that has demonstrated regulatory consistency across their product lines. Another consideration is ensuring an AI company that is committed to enterprise AI. This means the developer will work with you as a partner to enable seamless integration of AI across your organization and tailor solutions to unique needs. Read more about choosing an AI partner here

Integrating AI into your workflow

Integrating AI into your workflow is simple if you work with a solution that’s designed specifically for medical best practice, in the medical practice. 

You might think the most daunting part of an AI implementation is integrating it into your IT network and workflow software. Well-developed and carefully designed AI solutions overcome these challenges by taking the complex requirements of the healthcare industry into account. 

Choosing an AI company like Aidoc allows you to trust the experts as they manage your integration seamlessly. With our vendor-agnostic approach, we can integrate into any IT system and any PACS or RIS software. Aidoc’s lightweight deployment process is very straightforward with minimal disruption to business and workflow during the installation periods. Starting with back-end deployment, Aidoc installs the AI orchestrator – the core of the solution that routes all studies to and from secure servers – using a remote installation technique on your institution’s network. After the orchestrator is deployed, the front-end part of the AI solution is installed, called the widget. 

This is what radiologists and other providers see on their computer screens, enabling the prioritizing of urgent cases and acting as an Always-on safety net. Once integrated, AI only gets better. Adding new features or solutions can happen with the click of a button.

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