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Aidoc Staff

5 Things You Need to Assess AI Readiness at Your Facility

Adoption
Table of Contents

Successful AI implementation requires a thorough and honest assessment of your facility’s readiness. Here are five essential factors to consider when evaluating your health system’s preparedness for AI adoption. 

1. Assessing State of Readiness

Before diving into AI, it’s crucial to gauge your system’s current state of readiness. This involves understanding the existing infrastructure, workflows and technological landscape. Establishing a clear problem statement, for example, and aligning AI goals with strategic priorities are the first step toward successful implementation. This should come before you start shopping solution options.

2. Identifying Use Cases

The readiness for AI adoption hinges on identified use cases where clinical AI can enhance patient and provider experiences. These use cases could include:

  • Reducing length of stay
  • Improving emergency department workflows
  • Enhancing patient follow-up management

Similarly, having dedicated clinical teams and workflows for specific conditions such as stroke, pulmonary embolism, aortic dissection or IVC filters is essential. These teams can leverage AI for triage, notification and workflow enhancement, ultimately improving outcomes and aiding in use cases most relevant to your facility’s goals.

3. Establishing Oversight and Governance

Your facility should have a multidisciplinary committee to oversee the AI adoption process, evaluating clinical, financial and operational considerations. This oversight would involve:

  • Reviewing and assessing use cases
  • Establishing goals and expected outcomes
  • Conducting vendor interviews

Furthermore, it’s vital that this committee works to earmark a budget for pilot projects and establish mechanisms to measure potential ROI or cost savings from these initiatives.

4. Considering Enterprise-Wide vs. Departmental Implementation

While department-specific AI solutions can offer immediate benefits, an enterprise-wide approach often yields better ROI potential. Leveraging a clinical AI solution for specific pathologies, such as triage and notification, can serve as a foundation for expanding AI capabilities across more service lines or facilities.

5. Building a Multidisciplinary Team

Successful AI implementation requires a multidisciplinary team of stakeholders, including clinical, technical and operational experts. This team should collaborate to define opportunities for involvement and align AI initiatives with strategic business goals. As Sunil Dadlani, Chief Information Officer at Atlantic Health System emphasizes:

The approach we have always taken is to never start with the technology. We always identify what are the key challenges and opportunities…how they are aligned to our specific business goals and mission. Then identifying the right technologies with the right people, initiating pilots, defining key measures of success and building a cross-functional collaboration.

Conclusion

Assessing AI readiness involves more than just evaluating technology; it requires a strategic approach that aligns with your facility’s goals and leverages the collective expertise of a multidisciplinary team. By considering these five factors, your health system can effectively prepare for AI adoption in healthcare and be closer to actualizing the goal of enhanced patient care and operational efficiency.

Click here to download the Clinical AI Readiness Assessment and find your strengths and areas of opportunity.

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