New implementation community builds on global collaboration to improve
real-time device data exchange for AI-enabled care.
Data has become overwhelming in healthcare. While it has provided tremendous solutions and outcomes, however, it can sometimes be a problem, too! How can data utilization in Clinical Studies and a ground up data strategy help make your technologies, your team, and your trials more efficient?
Artificial intelligence is moving quickly into mainstream medical devices, and the industry has become fluent in a familiar set of concerns: bias, transparency, and cybersecurity. These topics matter, but they don’t capture the risks most likely to shape patient safety in the coming decade. The deeper challenges lie in the interactions between algorithms, clinical workflows, data pipelines, and human decision making. Those interactions are where safety is won or lost, and they remain the least examined part of AI adoption.
AI and large language models (LLMs) are revolutionizing critical care by integrating scattered data from various sources to deliver real-time insights. This allows for prompt escalation or de-escalation of treatment and enhances patient outcomes. These technologies also help reduce staffing issues and prevent clinician burnout by continuously monitoring patient risk and supporting decision-making in busy ICU settings.
Acquisition is expected to strengthens Thermo Fisher’s position in delivering clinical information to pharma and biotech customers.
The rise of AI-powered health apps that claim to diagnose conditions in real time is transforming how we approach healthcare. From symptom checkers to wearable ECG monitors and AI stethoscope apps, these tools promise early diagnoses and personalized healthcare at our fingertips. What if they go wrong?
The companies have reached a long-term agreement allowing customers to use software, data, technology, and service offerings from Veeva and IQVIA together.
FHIR (Fast Healthcare Interoperability Resources) is an open standard designed to streamline data sharing within national healthcare systems and across systems in different countries. Its introduction aims to bring more consistency to patient care, ensuring that no matter where healthcare professionals (HCPs) are located, they can access the same up-to-date information on medications and their patients.
This silent crisis has dire consequences. Patients face delays, errors increase and the entire system suffers. This cannot continue. But in the face of such crippling challenges, how can healthcare practices look to improve the interoperability of their systems?
MTI Viewpoint: I expect fundamental changes to our medical device ecosystem; not all companies will survive them. The ability to consistently use AI will also determine who will be among the survivors and even the winners. AI will not only be part of the devices but also an internal tool.