Blackford Analysis
Across every organization, there are varying structures, services, priorities, IT infrastructures, PACS vendors, and even politics. Consequently, the priorities, potential benefits, and challenges that are associated with designing a medical imaging AI adoption strategy vary significantly among the departments within an organization.
For this reason, it is essential to consider how each department and its associated priorities will be impacted by AI. It is also vital to identify role-specific challenges faced by administrators, IT teams, and radiologists at the project outset to ensure they are thoroughly considered and methodically mitigated throughout each phase of an AI strategy rollout. Administrators While administrators are primarily focused on budgets and ROI, they are also responsible for ensuring that AI is efficiently and rapidly implemented and operationalized within their organization. Given that budgeting and IT cycles are often long, it can take anywhere from 6 months to 2 years to identify, evaluate, select, contract, fund, deploy, and integrate an individual AI solution. Prioritizing and creating a roadmap for algorithm deployment requires thorough and careful consideration. Therefore, administrators must be meticulous in their approach when comparing the procurement and support costs of an AI strategy against its potential benefits for the entire organization. It can be tempting to focus on top-line revenue and evaluate algorithms based solely on their direct impact on reimbursement. However, greater value often lies in the system-wide impact of AI and its value potential for quality improvements and cost savings such as:- Increasing radiologist productivity and confidence,
- Improving modality utilization and Service Level Agreement (SLA) adherence,
- Reducing readmissions and length of stay.