Researchers at Northwestern University and Ann & Robert H. Lurie Children’s Hospital have developed AI models that predict the risk of sepsis in children within 48 hours of their arrival at the emergency department, based on early electronic health record data. This significant advancement, published in JAMA Pediatrics, allows for timely intervention and potentially reduces mortality rates by identifying high-risk patients before organ dysfunction occurs. Unlike previous models, these AI tools leverage the Phoenix Sepsis Criteria and successfully minimize the likelihood of overdiagnosis, ensuring that healthcare providers can focus appropriate treatment on those truly at risk. This development underscores the growing role of AI in precision medicine and the potential for improved outcomes in pediatric emergency care.

AI Breakthrough: Predicting Pediatric Sepsis 48 Hours in Advance Northwestern University News

Cybercrime has become the third largest global economy by GDP, posing significant threats to the healthcare sector, which is frequently targeted by sophisticated cyberattacks. Experts from Fortified Health Security, speaking at the CIO Connect conference, commended the Bermuda Hospitals Board for its proactive cybersecurity measures but warned that healthcare organizations must remain vigilant, as attackers now operate in highly organized networks. With threat actors often spending an average of 279 days undetected within systems, the imperative for robust data backup solutions—alongside regular testing of these backups—has never been more crucial. This ongoing risk highlights the need for healthcare professionals to prioritize cybersecurity protocols to safeguard sensitive patient data and maintain operational integrity.

Cybercrime Surges as Third Largest Global Economy, Threatening Healthcare Systems The Royal Gazette

A recent MIT study indicates that 95% of enterprise AI pilots in healthcare fail to yield measurable ROI, primarily due to poor integration and misaligned organizational priorities rather than deficiencies in AI models. Dr. Tim O'Connell, CEO of emtelligent, argues that effective AI applications must enhance clinical decision-making while involving human oversight, as current generic models struggle with the complexities of medical language. The findings highlight that the barriers to successful AI implementation are predominantly organizational, necessitating a redesign of workflows and robust data infrastructures to integrate disparate patient information effectively. By focusing on purpose-built medical AI and fostering the right data pipelines, healthcare organizations can unlock significant clinical and financial benefits.

AI Integration Challenges Hinder ROI in Healthcare, Study Shows Healthcare IT News

The Joint Commission has announced a significant policy shift by incorporating staffing standards as a critical component of its 2026 National Performance Goals for healthcare accreditation. For the first time, hospitals must meet specific staffing requirements, particularly emphasizing the role of nursing leadership in ensuring adequate staffing to provide safe and quality care. This decision underscores the vital relationship between appropriate nurse-to-patient ratios and patient safety, especially in light of rising RN turnover and vacancy rates exacerbated by the COVID-19 pandemic. By prioritizing staffing levels within its accreditation criteria, The Joint Commission highlights the need for systemic changes to improve healthcare outcomes and supports the advocacy efforts by nurses for better staffing oversight.

Joint Commission Elevates Staffing to Essential Healthcare Quality Standard Nurse.org

Researchers at Northwestern University and Ann & Robert H. Lurie Children’s Hospital have developed AI models that predict the risk of sepsis in children within 48 hours of their arrival at the emergency department, based on early electronic health record data. This significant advancement, published in JAMA Pediatrics, allows for timely intervention and potentially reduces mortality rates by identifying high-risk patients before organ dysfunction occurs. Unlike previous models, these AI tools leverage the Phoenix Sepsis Criteria and successfully minimize the likelihood of overdiagnosis, ensuring that healthcare providers can focus appropriate treatment on those truly at risk. This development underscores the growing role of AI in precision medicine and the potential for improved outcomes in pediatric emergency care.

AI Breakthrough: Predicting Pediatric Sepsis 48 Hours in Advance Northwestern University News

Cybercrime has become the third largest global economy by GDP, posing significant threats to the healthcare sector, which is frequently targeted by sophisticated cyberattacks. Experts from Fortified Health Security, speaking at the CIO Connect conference, commended the Bermuda Hospitals Board for its proactive cybersecurity measures but warned that healthcare organizations must remain vigilant, as attackers now operate in highly organized networks. With threat actors often spending an average of 279 days undetected within systems, the imperative for robust data backup solutions—alongside regular testing of these backups—has never been more crucial. This ongoing risk highlights the need for healthcare professionals to prioritize cybersecurity protocols to safeguard sensitive patient data and maintain operational integrity.

Cybercrime Surges as Third Largest Global Economy, Threatening Healthcare Systems The Royal Gazette

A recent MIT study indicates that 95% of enterprise AI pilots in healthcare fail to yield measurable ROI, primarily due to poor integration and misaligned organizational priorities rather than deficiencies in AI models. Dr. Tim O'Connell, CEO of emtelligent, argues that effective AI applications must enhance clinical decision-making while involving human oversight, as current generic models struggle with the complexities of medical language. The findings highlight that the barriers to successful AI implementation are predominantly organizational, necessitating a redesign of workflows and robust data infrastructures to integrate disparate patient information effectively. By focusing on purpose-built medical AI and fostering the right data pipelines, healthcare organizations can unlock significant clinical and financial benefits.

AI Integration Challenges Hinder ROI in Healthcare, Study Shows Healthcare IT News

The Joint Commission has announced a significant policy shift by incorporating staffing standards as a critical component of its 2026 National Performance Goals for healthcare accreditation. For the first time, hospitals must meet specific staffing requirements, particularly emphasizing the role of nursing leadership in ensuring adequate staffing to provide safe and quality care. This decision underscores the vital relationship between appropriate nurse-to-patient ratios and patient safety, especially in light of rising RN turnover and vacancy rates exacerbated by the COVID-19 pandemic. By prioritizing staffing levels within its accreditation criteria, The Joint Commission highlights the need for systemic changes to improve healthcare outcomes and supports the advocacy efforts by nurses for better staffing oversight.

Joint Commission Elevates Staffing to Essential Healthcare Quality Standard Nurse.org