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New tool helps predict outcomes for COVID-19 patients

A new assessment tool helps guide clinical decisions in emergency departments and urgent care centers


New tool helps predict outcomes for COVID-19 patients. Spurce:

American Journal of Emergency Medicine has conducted a study that reports on a special COVID-19 assessment tool. It was developed by Kaiser Permanente specialists to give patients guaranteed and the right care. It can consult patients with COVID-19 symptoms and help them to indicate whether it will be in a severe or slight way.

As the pandemic surges again across the country and hospitalizations are increasing, front-line physicians often must make quick decisions to hospitalize or discharge patients with COVID-19 symptoms. We created a risk assessment that looks at many different patient variables that might predict a critical poor outcome — without any lab or diagnostic testing
Adam Sharp, an emergency medicine physician and a researcher for the Kaiser Permanente

Also Dr. Sharp says that this risk assessment especially helps physicians at the emergency department visit.

This assessment instrument analyzes comorbidities, obesity, vital signs, age, and sex, so it is called the COVAS. Kaiser Permanente in Southern California has already included the COVAS into the e-health record system.

It directs physical decisions in urgent care and emergency centers. The COVAS in this study exactly scored the level of danger or disease probabilities during seven days for patients at the emergency department of Kaiser Permanente in Southern California.

Between March 1, 2020, to April 30, 2020, researchers managed a study of 26,600 visits to the emergency department. These visits at fifteen Kaiser Permanente hospitals in Southern California were made by adults with common COVID-19 symptoms.

The results help health professionals to understand which COVID-19 patients with fever, cough, and difficulty breathing are at extreme death or complication risk.

We’ve reported that Public Health Wales has accidentally left the personal data of 18,105 COVID-19 patients exposed on a public server.


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