AI-powered diagnostics in digital healthcare transforming patient safety: GlobalData

These tools enable a more personalised approach to healthcare by analysing biological and clinical data using advanced algorithms that account for individual patient characteristics, biomarkers, and disease profiles

The introduction of artificial intelligence (AI)-powered diagnostic tools demonstrates the medical industry’s shift towards precision medicine approaches. These tools enable a more personalised approach to healthcare by analysing biological and clinical data using advanced algorithms that account for individual patient characteristics, biomarkers, and disease profiles. Precision medicine exemplifies a larger trend of tailoring therapeutic interventions to improve treatment efficacy and safety, says GlobalData.

AI is rapidly being adopted in the medical field, with many medical devices beginning to incorporate AI capabilities. These AI capabilities include advanced imaging systems, smart robots, wearable technology, AI-based data analysis, simulation platforms, and more.

Elia Garcia, Medical Analyst at GlobalData, comments, “Integrating AI-powered digital health solutions into the existing healthcare systems, such as electronic medical records (EMRs), gives clinicians easy access to diagnostic insights and patient data. The FDA’s recent approval of Prenosis’ Sepsis ImmunoScore, the first AI diagnostic tool for sepsis, demonstrates that AI has the potential to significantly improve patient safety in hospitals and healthcare facilities. The AI/machine learning (ML) software, which is directly integrated into hospital EMRs, boosts clinical workflow efficiency, collaborative decision-making and patient safety.”

The software as a medical device (SaMD) classifies patients into risk groups based on their sepsis risk score, providing clinicians with useful information about the likelihood of deterioration, hospital length of stay, and the need for escalated care. Identifying high-risk patients early on allows healthcare providers to better allocate resources and tailor interventions, resulting in fewer adverse outcomes.

Garcia concludes, “To summarise, AI has enormous potential to improve patient safety in healthcare facilities by enabling early detection and diagnosis, risk assessment and prediction, seamless integration with existing healthcare systems, and the development of personalised therapeutic interventions. The FDA’s approval of the first AI diagnostic tools for sepsis is a significant step forward in realising AI’s potential to improve patient care and outcomes in acute care settings.”