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Aidoc Staff

Choosing the Right AI for Your Healthcare Facility: Key Considerations

Adoption, System Integration
Table of Contents

In the world of clinical AI, it’s easy to get swept up in the excitement and start thinking about “what” it’s going to do for you before fully understanding the “why.” The first and most crucial step in choosing the right AI solution is to avoid implementing AI just for the sake of it.  This might seem counterintuitive, but it highlights the importance of focusing on the problem you’re trying to solve rather than the technology itself. 

In this post, we’re going to give you a some key considerations when assessing your AI options:

First, Determine Your Approach

Like healthcare itself, approaches to clinical AI integration aren’t one-size-fits-all. Three primary paths have gained traction, each with its own unique advantages and challenges:

  • Point Solutions: These offer rapid deployment and focus on specific tasks, but can create data silos and limit scalability.
  • Marketplaces: These provide a hub for discovering and choosing different AI solutions, but require expertise to navigate and may involve varying quality and system compatibility.
  • Platforms: These provide a centralized infrastructure for scalable AI implementation, but require an upfront investment.

Understanding these paths and evaluating which aligns best with your facility’s needs is critical to making an informed decision.

Carefully Choosing a Partner

Selecting the right partner is one of the most important decisions you’ll make when implementing AI. Proceed with extreme scrutiny. While vendors sell products, partners work with you to achieve your goals. In the AI space, you’ll encounter many vendors and partners, but aligning with a partner offers the best change for long term success. Not all AI partners are created equal, and it’s crucial to find one that can support a scalable, enterprise-wide solution.

Must-Have Considerations for Any Clinical AI Partner

  • Market Traction: Look for a proven track record in live clinical environments. AI deployment should be based on established use cases.
  • Clinical Validation: Ensure demonstrated data accuracy from the outset and that there are plans in place to address data drift.
  • Regulatory Clearance: Mandatory for any clinical use case, the number of clearances testifies to the quality and technical maturity of the solution. 
  • A Roadmap: A clearly defined plan for future modalities, proving relevance to your current workflow and how the partner can evolve with your changing needs.
  • Culture of Innovation: A comprehensive portfolio of available technology while also investing in and validating new algorithms and solutions.
  • Seamless Integration: Support for deploying AI at scale and ensuring adoption by end-users.
  • Always On: Fully automated with 24/7 monitoring and analysis that works in real-time without manual intervention.
  • Straightforward Deployment: AI should not require any ‘tricks’ to work. A partner should minimize downtime and reduce IT lift and risk.
  • Change Management: Recognize that people and processes enable change – not just the technology. Any AI partner should be as prepared to support as they were to sell.

By focusing on these key areas, your facility can build confidence in finding the right AI partner and solution, ensuring readiness for successful AI implementation. 

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