Advocacy - Lab Advocate
ADLM released a new policy report, “Artificial Intelligence in Laboratory Medicine: Leveraging Laboratory Expertise to Improve Patient Care,” outlining how laboratory quality systems can support the responsible implementation and governance of artificial intelligence (AI) across healthcare.
The report emphasizes that clinical AI raises many of the same quality and patient safety questions that laboratories routinely address when implementing diagnostic tests. These include defining intended use, validating performance in the local patient population, documenting limitations, continuously monitoring performance, investigating errors, and ensuring that qualified professionals remain accountable for clinical decisions.
ADLM recommends that policymakers and healthcare organizations establish risk-based governance frameworks, require independent validation and post-deployment monitoring, develop external quality-assessment and benchmarking programs, promote laboratory data harmonization and interoperability, and support workforce development. The report also calls for payment policies that recognize both the clinical value of AI and the resources required to govern it responsibly.
Laboratory professionals have extensive experience managing data quality, analytical variability, quality assurance, regulatory compliance, and clinical interpretation. This expertise positions laboratories to serve as foundational governance and operational partners as AI becomes more integrated into patient care.