By Jim Sianis, PharmD, MBA, Executive Director of Business Development, Prenosis
LinkedIn: Jim Sianis, B.S., PharmD, MBA
LinkedIn: Prenosis
As artificial intelligence and machine learning become more integrated into healthcare, their potential to improve early identification of sepsis patients offers tremendous promise.
Selecting the right solution can be overwhelming for providers. According to an October 2024 article in JAMA by three senior FDA officials, the sheer pace and scope of new AI algorithms brings into question the ability of regulatory agencies and health systems to properly vet and test them. Prenosis’ Sepsis ImmunoScore™ was highlighted in this article as a pivotal example of an AI innovation that successfully navigated the rigorous FDA regulatory process.
Below are 4 key components to look for when evaluating AI-augmented algorithms for sepsis detection.
Accuracy
Demand evidence of strong performance metrics. Algorithms should support diagnostic and prognostic performance across diverse patient populations and be generalizable across many different sites. Additionally, look for a solution that includes a continuous monitoring plan to monitor algorithm drift over time as patient demographics and care patterns evolve. Finally, choose a sepsis diagnostic solution that only uses complete, consistent datasets to ensure consistency and reliability in the output.
Transparency
“Black box” algorithms have no place in critical care decisions. Clinicians need to understand why a patient has been identified at risk for sepsis. Look for algorithms that provide clear explanations of contributing factors – such as SHAP values or specific abnormal vital signs and lab results. The solution should answer the crucial question: “Why is this patient at risk?” Visibility into the algorithm’s reasoning builds clinical trust and enables appropriate intervention.
Integration and Workflow Compatibility
Even the most accurate algorithm fails if it doesn’t fit seamlessly into clinical workflows. Demand that the solution integrates with your existing EHR platform. Look for a solution that will deliver results within existing workstreams, minimizing alert fatigue and workflow disruption.
Regulatory Compliance
Patient safety demands proper regulatory oversight. Prioritize solutions with FDA authorization, which demonstrates adherence to rigorous quality standards. Third-party validation provides additional confidence in the algorithm’s performance claims.
Focusing on these four key areas, providers can navigate the complex landscape of AI-assisted sepsis detection solutions and select the technology that truly advances patient care.
This article was originally published on the Prenosis blog and is republished here with permission.