Amid a debilitating nationwide blood culture bottle shortage, hospitals across the US faced a severe resource crunch with some institutions having less than 12 bottles in stock at any given time. Nicholas P. Marshall, MD, FAAP, a Pediatric Infectious Diseases and Clinical Informatics Fellow at Stanford University, saw this as an opportunity to innovate, turning…
Surgical site infections (SSIs) rank among the most common healthcare-associated infections (HAIs), leading to increased patient morbidity, extended hospital stays, and greater healthcare costs. For effective infection prevention and control (IPC) strategies, the World Health Organization identifies the surveillance of HAIs, such as SSIs, as crucial. Existing surveillance of SSIs is mainly performed by IPC…
Artificial Intelligence (AI) and Machine Learning(ML) have experienced substantial growth across multiple industries, including healthcare. The integration of these progressive technologies into medical devices already shows promise in detecting infection-related complications swiftly and accurately. However, this integration brings along challenges in aligning it with the established regulatory norms, adding the complexity of devices that provide…
Healthcare-associated infections (HAIs) and multidrug-resistant (MDR) pathogens pose significant threats to global health. Challenges associated with these threats have intensified with the rise of SARS-CoV-2 and an expanding immunocompromised population. Isolation precautions form a critical part of infection prevention control (IPC) strategies, but their arbitrary usage can strain resources and impede patient well-being, necessitating a…
Healthcare-associated infections (HAIs) brought about by multi-drug resistant organisms (MDROs) prove a daunting obstacle for healthcare systems due to their impact on patient safety and cost implications. These infections could already be present in patients upon arrival at the hospital or might be acquired during their stay. Identification of such infections remains complicated due largely…
A recent collaborative study has advanced the use of machine learning (ML) tools, demonstrating their potential to predict the risk of contamination linked with medical devices and to forecast the 30-day health outcomes for patients in the intensive care unit (ICU). The research leveraged data from 8574 ICU patients that underwent invasive procedures, extracted from…
The past few decades have witnessed a dramatic transformation in hospital safety protocols, with an emphasis on enhancing infection control surveillance solutions. This trend, blossoming since the late 2000s, is driven by hospitals worldwide aiming to boost patient safety and diminish infection rates. The catalyst of this revolution is the emergence of advanced electronic medical…