Assessment Guide for Algorithmic Impact: User Instructions
The National Medical Imaging Platform (NMIP) has unveiled a user guide, developed in collaboration with the NHS AI Lab, to help teams seeking access to NMIP imaging data for research, training new medical products, or testing existing ones. This guide outlines a structured evaluation framework, known as the Algorithmic Impact Assessment (AIA) process, designed to ensure ethical, legal, and operational risks are thoroughly evaluated before clinical use.
The AIA process is a crucial component of the guide, encompassing a multi-domain risk assessment, data governance, ethical validation, stakeholder engagement, and continuous monitoring.
Risk Identification and Management
The process begins with a comprehensive evaluation of various risks, including patient safety, operational, strategic, legal, technological, and ethical risks specifically related to AI deployment in medical imaging. This assessment is proactive and covers multiple risk domains beyond immediate patient safety.
Data Governance and Privacy Compliance
Ensuring patient consent, anonymization of imaging data, and adherence to data privacy regulations are foundational parts of the AIA process. This includes careful control of data access, respecting autonomy, and fair use principles.
Validation and Ethical Review
AI models must undergo rigorous clinical validation to ensure accuracy and reliability against real-world clinical data. The process evaluates transparency, fairness (e.g., bias reduction), accountability, and ongoing monitoring post-deployment.
Stakeholder Engagement
Collaborative ideation sessions with clinical personnel and AI experts form part of the assessment to identify and mitigate risks at all workflow levels.
Continuous Lifecycle Oversight
The AIA is part of a lifecycle framework ensuring ethical considerations and technical performance are continually reviewed throughout AI development, deployment, and clinical integration phases.
The user guide also provides a template for the AIA process and step-by-step guidance for project teams on conducting an AIA for their project. Completion of the AIA, as detailed in the user guide, is a requirement for access to the NMIP dataset by the NHS AI Lab team.
The user guide is part of a research partnership exploring algorithmic impact assessments (AIAs) in healthcare. The full report can be accessed from the project page, which also provides information about the wider work exploring AIAs in healthcare. The guide is intended for teams that want to use NMIP imaging data for one of the three purposes mentioned above.
In summary, the AIA process requires a comprehensive, multi-domain risk assessment combined with data governance, ethical validation, and continuous monitoring to ensure trustworthy, safe access to NMIP imaging data as per NHS AI Lab standards. This is designed to align AI integration with patient safety, legal compliance, and clinical efficacy principles.
- The user guide, developed for teams aiming to use National Medical Imaging Platform (NMIP) data for research, developing new medical products, or testing existing ones, encompasses a technology-focused aspect in the Algorithmic Impact Assessment (AIA) process.
- As part of the Health-and-Wellness industry's commitment to ethical, legal, and operational safety, the AIA process for NMIP data includes assessment of scientific, medical-conditions, patient safety, operational, strategic, legal, technological, and ethical risks related to AI deployment in medical imaging.
