Intracav Wiki

Evidence-based clinical guidelines and policies for vascular access teams

Evidence-based protocols and standardized procedures

Foundations of Clinical Practice and Specialized Population Management

This comprehensive guide outlines evidence-based principles of vascular access and infusion therapy across the lifespan, including neonatal, pediatric, obstetric, and geriatric populations. It covers regulatory compliance, ethical practice, device selection, infusion accuracy, and population-specific risks such as DEHP exposure, DIVA management, pregnancy-related hypercoagulability, and geriatric polypharmacy. Designed for clinicians, nurses, and vascular access specialists, this resource supports safe, patient-centered decision-making aligned with current standards of care.

Blood Draws and Hemolysis: Physics, Biochemistry, and Best Practices

Comprehensive guide to preventing hemolysis during blood draws: understanding catheter-to-vein ratio (CVR), cavitation physics, and evidence-based techniques for optimal lab sample quality.

Cortisol Levels in Hospital Staff and Work Efficiency: A Critical Clinical Analysis

Critical analysis of cortisol dysregulation in hospital staff and its impact on clinical performance, patient safety, and healthcare workforce wellbeing with evidence-based interventions.

ASEPTIC NON-TOUCH TECHNIQUE (ANTT®) in Clinical Practice

Comprehensive clinical guideline for ASEPTIC NON-TOUCH TECHNIQUE (ANTT®) - evidence-based infection control protocols for invasive procedures and medical device management in healthcare settings.

Intracav AI Prompting Guidelines

Complete guide to maximizing Intracav AI effectiveness: best practices for prompting, query formulation, and leveraging AI assistance for vascular access clinical practice and research.

Exploring the Dynamics of Clinical Decision Making in Vascular Access

Comprehensive guide to clinical decision-making in vascular access: exploring interprofessional collaboration, evidence-based protocols, and patient-centered care strategies for optimal outcomes.

Analysis, perspectives, and healthcare innovation

Cortisol Levels in Hospital Staff and Work Efficiency

This article examines how elevated cortisol levels—the body's primary stress hormone—affect hospital staff's health and work performance. It explains that healthcare workers face unique stressors such as high-stakes patient care, excessive workloads, and lack of institutional support, which can lead to chronically elevated cortisol and subsequent health issues including anxiety, depression, cognitive impairment, and cardiovascular problems. These effects ultimately reduce work efficiency and can compromise patient safety. The article reviews research on cortisol patterns in emergency care providers, discusses how the COVID-19 pandemic exacerbated these challenges, and offers strategies for managing cortisol levels through lifestyle modifications (exercise, sleep hygiene), stress management techniques (mindfulness, CBT), organizational changes (workload management, flexibility), and when necessary, medical interventions. It concludes by urging healthcare organizations to prioritize staff well-being through transparent, supportive management practices to maintain both employee health and quality patient care.

APIs Over Guidelines

Clinical guidelines as static PDFs are failing healthcare. Learn why API-first medical knowledge distribution is essential for modern clinical decision support and how open-source approaches can revolutionize healthcare interoperability.

IntracavOS: The Beautiful Paranoia of Total Control

Why IntracavOS moved from cloud APIs to a fully isolated, self-hosted AI system: exploring the security philosophy behind closed-loop healthcare AI and the paranoid approach to patient data protection.

Healthcare is a Slow Moving Carcass

A candid critique of healthcare's resistance to innovation: why vascular access and clinical practice remain stuck in outdated patterns while real problems like CLABSIs persist.

Introducing IntracavOS

Why we built IntracavOS on NixOS: A reproducible, secure, and scalable operating system designed specifically for healthcare AI deployment. Learn about our architecture and why traditional approaches fail.