The FDA CDRH is seeking input from industry and the public on expanding access to home use medical technologies. The comment period closes on August 30, 2023.
On August 11, the FDA released a Final Guidance on Off-the-Shelf Software Use in Medical Devices, which supersedes Off-The-Shelf Software Use in Medical Devices issued September 27, 2019.
Hospital at Home models are expanding capacity for overcrowded hospitals and emergency departments and providing comfort to a growing range of patients. Dave Kerwar, co-founder of Inbound Health, discusses the best candidates for hospital at home care and opportunities for MedTech providers to enhance this model of care, as payers and CMS look at long-term adoption.
Healthcare cyberattacks are becoming more common and more costly—both financially and to patient care continuity. Internet-connected IoMT devices and equipment remain a security concern for healthcare delivery organizations. Deeper collaboration between HDOs, medical device manufacturers and security providers is needed to reduce risk and vulnerability.
Supply chain challenges and the move to advanced manufacturing are two key issues affecting the Medtech industry. On November 7-9, MedTech Intelligence will be hosting the MedTech Advanced Manufacturing Conference and Supply Chain Summit, in partnership with Axendia, Inc. The two events will run back-to-back with registration options available for each program as well as a discounted rate for professionals who would like to attend both programs.
Sonio Detect, a manufacturer-agnostic software product that uses artificial intelligence (AI) to enhance the quality of fetal exams, and automatically detect views and quality criteria of ultrasound images has been granted FDA clearance.
The use of artificial intelligence in medical device design is already transforming health care. In this article we look at areas of greatest promise as well as the challenges that must be addressed to realize the promise of AI in device design and engineering.
The dramatic increase of medical devices in patient care has yielded many benefits. However, this technology also carries various risks, including risks to patient privacy, that must be addressed.
Results from the AVEIR DR i2i Investigational Device Exemption (IDE) study through three-months post-implant showed a 98.3% implant success rate for physicians and more than 97% of people had a successful atrio-ventricular synchrony, so that the upper and lower chamber were beating normally, despite different types of underlying slow heart rhythms.
When considering use cases and data classification methods for machine learning, image quality, power consumption and latency must be considered.