Overcome the Challenges of AI Implementation

Overcome the Challenges of AI Implementation

With more than 1,500 healthcare AI solution providers in the market today, it can be overwhelming to implement your healthcare system’s AI strategy. A report published by Sage Growth Partners highlights the increased adoption of AI strategy in healthcare institutions to 90%, up from 53% in 2019. Implementation is growing much slower, with only 34% of institutions implementing AI, up from 23% during the same time period. Choosing the right AI partner can minimize the challenges of implementing AI in healthcare.

Challenges of Implementing AI

The sheer volume of AI single-point solutions specific to a diverse number of therapeutic areas can be daunting. Coupled with common barriers to AI adoption, healthcare leaders struggle to determine the best route for deploying their AI strategy.

Common Barriers:

  • High cost and resource needs of implementation of each single-point solution
  • Complexity of managing AI growth across the enterprise
  • Management of data security and protected health information
  • Legal, regulatory, and IT risk liability
  • Algorithm validation on chosen patient population
  • Performance monitoring for the lifecycle of the algorithm

Ferrum's Enterprise AI Hub: Your Solution to Overcoming the Challenges of AI Implementation

A secure and scalable platform, or Enterprise AI Hub, can expedite the onboarding of AI healthcare solutions.

Instead of choosing one single-point AI solution and developing individual strategies for deploying each application, the experts at Ferrum Health can orchestrate and launch your AI strategy through an Enterprise AI Hub. This approach allows for the optimal use of multiple AI algorithms while eliminating the need to develop a new infrastructure for each new AI solution. Utilizing an Enterprise AI Hub brings together the tools that cover the entire patient journey and address data security risks without disrupting clinical workflows and daily administrative operations.

The Enterprise AI Hub covers the entire AI lifecycle, including:

  • Set-up and Deployment
    • Fast and Flexible implementation
    • Low IT burden
  • Training
    • Clinical training on Ferrum’s Enterprise AI Hub dashboard
    • Minimal training needed as workflow integration is seamless
  • Health System Integration
    • Standard healthcare system integrations, including DICOM, HL7, FHIR, PACS, RIS, EHR, and other administrative systems for billing and scheduling
  • Validation
    • AI algorithms are validated on your local patient population
    • Validation is completed on your specific medical imaging equipment
  • Security Management
    • On-prem hybrid platform ensures patient data is stored at the hospital and processed on-site
    • Data management tools in the cloud ensure lower IT burden while keeping data on-premises secure and safe
  • Monitoring
    • Monitor algorithm performance on an ongoing basis
    • Enable adjustments as needed

Ferrum’s Enterprise AI Hub enables clinicians to focus on their patients and the care they need, not the complicated deployment of new technology.

Do you have questions regarding the performance of AI algorithms in use at your hospital? 

Interested in learning more about validating and deploying enterprise-wide AI at your hospital?

Drop us a note, and let’s connect.

Picture of Amy Veter

Amy Veter

Amy is an experienced healthcare marketer with a love for the written word. She has a passion for improving patient care and for furthering the integration of technology as a solution to deliver equitable healthcare.

Contact Us

CASE STUDY

ARA Health Specialists

Use the button below to download your free case study and learn how our approach to validation has improved the number of clinically significant findings in AI software.

CASE STUDY

Sutter Health

Use the button below to download your free case study and learn how our approach to validation has improved the number of clinically significant findings in AI software.