12 Key Factors to Evaluate When Considering Potential AI Solutions for Your Health System
Evaluating AI vendors for healthcare systems is a critical task. Here are 12 essential factors to consider to ensure you select the right solution:
Unified Platform: Look for a single platform--different than a "marketplace"-- that can deploy and manage all AI solutions, avoiding issues with incompatible solutions from different vendors.
Integration Capabilities: Ensure the AI solution offers enterprise-grade connectivity to existing systems of record, reducing the need for multiple, duplicative integrations.
Standardized Output: The AI solutions should provide standardized outputs, which create predictability, flexibility, and uniformity for end users, making them easier to adopt and use.
Streamlined Workflow: Opt for solutions that offer uniform options, filters, and settings, which can simplify and streamline workflows for clinicians.
Patient Management: Evaluate how the AI solution handles post-acute workflows, allowing health systems to monitor patients needing additional care beyond the initial acute finding.
Communication Workflows: The AI solution should facilitate communication workflows that extend its benefits to referral sites, enhancing collaborative care.
Security Standards: Ensure that the AI solutions adhere to best-in-class security standards, providing peace of mind that the deployed solutions are secure.
Analytical Tools: Look for personalized support and actionable tools that offer data visualization to measure the impact of AI solutions against health system goals.
Scalability: The AI solutions should support the implementation, integration, and maintenance of homegrown AI solutions, allowing for growth and customization.
Efficient Orchestration: Consider AI solutions with efficient orchestration processes that allow multiple AI activities to run on a single virtual machine, thereby reducing data center utilization and costs.
Data Drift Mitigation: Ensure the AI solutions include processes for mitigating data drift, which is essential for maintaining the accuracy and reliability of AI performance over time.
Vendor Experience: Assess the experience of the AI vendor in the healthcare sector. Experienced vendors are more likely to understand the unique challenges and regulatory requirements of healthcare, and they can provide valuable insights on important issues like governance and risk. Check their track record, client testimonials, and case studies to gauge their effectiveness and reliability.
By carefully evaluating these factors, healthcare systems can make informed decisions when selecting AI partners, ensuring they choose solutions that are effective, secure, scalable, and compliant.
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