New OR Safety Recommendations for COVID-19 Pandemic
|
By HospiMedica International staff writers Posted on 19 May 2020 |

Image: The Stanford COVID-19 surgical decision-tree algorithm (Photo courtesy of JACC)
A decision-tree algorithm designed to protect operating room (OR) staff assumes that every patient is potentially infected with COVID-19, until proven otherwise.
The recommendations, devised by surgeons at Stanford University (CA, USA), are designed to protect OR staff, while at the same time conserving personal protective equipment (PPE) use. The recommendations include:
• For emergency procedures (or in situation where SARS-CoV-2 testing is not possible before surgery), personnel should use full PPE, including gown, gloves, eye protection, and a fitted N-95 respirator mask.
• Urgent procedures on symptomatic patients should be delayed if possible. If the procedure cannot be delayed, patients should undergo SARS-CoV-2 testing. Any urgent procedure where testing is positive should be approved by the anesthesia and surgical chair, and if the procedure is approved, personnel should use full PPE and follow the hospital's protocol for COVID-19 patients.
• Asymptomatic patients scheduled for high-risk procedures who test negative for SARS-CoV-2 and asymptomatic patients scheduled for low-risk procedures can proceed to surgery where OR members use standard surgical attire.
• For all intubations or extensive bag-mask ventilation, anesthesia personnel should wear a fitted N-95 mask plus face shield, and other personnel should leave the room for this portion of the procedure to avoid possible droplet and aerosol infection.
•
“This algorithm is based on the urgency of the operation, anticipated viral burden at the surgical site, opportunity for a procedure to aerosolize virus, and likelihood a patient could be infected based on symptoms and testing,” concluded lead author Joseph D. Forrester, MD, and colleagues. “It prioritizes patients based on disease severity, testing status, and symptoms, while ensuring rational use of PPE in a resource-constrained setting. It has been shared with healthcare providers and stakeholders nationwide and is expected to be widely adopted.”
At the time the guideline algorithm was created there was a nationwide shortage of N-95 face masks in the United States. To conserve the institution's supply, the algorithm requires a face shield to be placed over the mask. The U.S. federal government has recently announced that millions of face masks, face shields, surgical masks, gloves, and gowns are entering the medical supply chain.
Related Links:
Stanford University
The recommendations, devised by surgeons at Stanford University (CA, USA), are designed to protect OR staff, while at the same time conserving personal protective equipment (PPE) use. The recommendations include:
• For emergency procedures (or in situation where SARS-CoV-2 testing is not possible before surgery), personnel should use full PPE, including gown, gloves, eye protection, and a fitted N-95 respirator mask.
• Urgent procedures on symptomatic patients should be delayed if possible. If the procedure cannot be delayed, patients should undergo SARS-CoV-2 testing. Any urgent procedure where testing is positive should be approved by the anesthesia and surgical chair, and if the procedure is approved, personnel should use full PPE and follow the hospital's protocol for COVID-19 patients.
• Asymptomatic patients scheduled for high-risk procedures who test negative for SARS-CoV-2 and asymptomatic patients scheduled for low-risk procedures can proceed to surgery where OR members use standard surgical attire.
• For all intubations or extensive bag-mask ventilation, anesthesia personnel should wear a fitted N-95 mask plus face shield, and other personnel should leave the room for this portion of the procedure to avoid possible droplet and aerosol infection.
•
“This algorithm is based on the urgency of the operation, anticipated viral burden at the surgical site, opportunity for a procedure to aerosolize virus, and likelihood a patient could be infected based on symptoms and testing,” concluded lead author Joseph D. Forrester, MD, and colleagues. “It prioritizes patients based on disease severity, testing status, and symptoms, while ensuring rational use of PPE in a resource-constrained setting. It has been shared with healthcare providers and stakeholders nationwide and is expected to be widely adopted.”
At the time the guideline algorithm was created there was a nationwide shortage of N-95 face masks in the United States. To conserve the institution's supply, the algorithm requires a face shield to be placed over the mask. The U.S. federal government has recently announced that millions of face masks, face shields, surgical masks, gloves, and gowns are entering the medical supply chain.
Related Links:
Stanford University
Latest Surgical Techniques News
- Continuous Monitoring with Wearables Enhances Postoperative Patient Safety
- New Approach Enables Customized Muscle Tissue Without Biomaterial Scaffolds
- Robot-Assisted Brain Angiography Improves Procedural Outcomes
- Brain Mapping Technology Enhances Precision in Brain Tumor Resection
- Handheld Robotic System Expands Options for Total Knee Surgery
- VR Experience Reduces Patient Anxiety Before Kidney Stone Procedure
- Injectable Mini Livers Offer Hope for Patients Awaiting Transplant
- Pulsed Field Ablation Technology Cleared in Europe for Persistent AFib
- AI-Powered Imaging Brings Real-Time Margin Clarity to Breast Cancer Surgery
- Minimally Invasive Device Safely Treats Challenging Brain Aneurysms
- Surgical Robot Makes Complex Liver Tumor Surgery Safer and Less Invasive
- Neurostimulation Implant Reduces Seizure Burden in Drug-Resistant Epilepsy
- Minimally Invasive Procedure Effectively Treats Small Kidney Cancers
- Fluorescence Probe Paired with Engineered Enzymes Lights Up Tumors for Easier Surgical Removal
- Novel Hydrogel Could Become Bone Implant of the Future
- Skull Implant Design Could Shape Surgical Outcomes
Channels
Artificial Intelligence
view channel
Machine Learning Approach Enhances Liver Cancer Risk Stratification
Hepatocellular carcinoma, the most common form of primary liver cancer, is often detected late despite targeted surveillance programs. Current screening guidelines emphasize patients with known cirrhosis,... Read more
New AI Approach Monitors Brain Health Using Passive Wearable Data
Brain health spans cognitive and emotional functions and can fluctuate even in adults without diagnosed disease. Detecting early changes remains difficult in routine care and burdens specialty services... Read moreCritical Care
view channel
Automated IV Labeling Solution Improves Infusion Safety and Efficiency
Medication administration in high-acuity settings is often complicated by multiple concurrent infusions, making accurate line identification essential. In a 10-hospital intensive care unit study, 60% of... Read more
First-Of-Its-Kind AI Tool Detects Pulmonary Hypertension from Standard ECGs
Pulmonary hypertension is a progressive, life‑threatening disease that is frequently missed early because symptoms such as dyspnea are nonspecific and diagnostic delays can exceed two years.... Read morePatient Care
view channel
Wearable Sleep Data Predict Adherence to Pulmonary Rehabilitation
Chronic obstructive pulmonary disease (COPD) is a long-term lung disorder that makes breathing difficult and often disturbs sleep, reducing energy for daily activities. Limited engagement in pulmonary... Read more
Revolutionary Automatic IV-Line Flushing Device to Enhance Infusion Care
More than 80% of in-hospital patients receive intravenous (IV) therapy. Every dose of IV medicine delivered in a small volume (<250 mL) infusion bag should be followed by subsequent flushing to ensure... Read moreHealth IT
view channel
EMR-Based Tool Predicts Graft Failure After Kidney Transplant
Kidney transplantation offers patients with end-stage kidney disease longer survival and better quality of life than dialysis, yet graft failure remains a major challenge. Although a successful transplant... Read more
Printable Molecule-Selective Nanoparticles Enable Mass Production of Wearable Biosensors
The future of medicine is likely to focus on the personalization of healthcare—understanding exactly what an individual requires and delivering the appropriate combination of nutrients, metabolites, and... Read moreBusiness
view channel







