Building trust through transparent and responsible AI
The potential of AI comes with the responsibility of ensuring its implementation is transparent, trustworthy, and centered on human oversight. These principles form the core of responsible AI—guiding its integration into real-world clinical settings to improve outcomes while inspiring confidence among clinicians and patients alike.
“For both patients and doctors to trust and rely on generative AI at the point of care, it is critically important that the technology is trained on content provided and vetted by medical professionals,” says Greg Samios, CEO of Wolters Kluwer’s Clinical Effectiveness Division. “ Where physicians see potential for generative AI to improve how healthcare is delivered, it is because they see a benefit for their patients to receive more timely, personalized care.“
Central to responsible AI is its ability to help solve challenges while ensuring that the information served is accurate. Rigorous development practices and professional oversight ensure these tools are reliable, effective, and always aligned with patient safety.
Advancements in clinical decision support
Clinical decision support (CDS) systems can be a vital resource for empowering healthcare providers to make better, faster decisions at the point of care. Two key advancements are leading the charge in this space:
1. AI-enhanced search for faster answers
AI-driven search capabilities are helping providers access the clinical insights they need with speed and precision. Innovative search functionality allows clinicians to find evidence-based answers faster, saving critical time during care delivery. These tools represent responsible technology in action, designed to streamline workflows while maintaining confidence in the reliability of the information they provide.
“Fewer clicks, less administrative burden, and it cuts down the time to get you to the answer to your clinical question,” Samios said. “It gets you to that trusted answer, but just does it really quickly.”
2. Analytics for better organizational decisions
AI-enhanced analytics represent the potential to translate previously unstructured data into actionable dashboards, equipping healthcare leadership teams with new visibility into system performance. These tools can highlight care gaps, regional variances, and usage trends, enabling a data-driven approach to operational decision-making. With a clear view of where resources and strategies are needed most, administrators can align their initiatives to ensure better care outcomes and smarter use of resources.
