Coronoviruses may have occurred in Los Angeles around Christmas, before novel novel coronoviruses were identified in the United States, according to researchers at the University of California, Los Angeles, and the University of Washington.
The team of researchers discovered the spike in patients with acute respiratory failure and cough at UCLA health hospitals and clinics, which analyzed health records, according to a university press release in late December 2019. The findings, published in a report by the Journal of Medical Internet Research, suggest that novel coronoviruses may occur months before the first case is officially identified.
The team of researchers analyzed more than 10 million UCLA health system outpatient, emergency department, and hospital facility records between December 1, 2019 and February 29, 2020 – about the presence of novel coronaviruses in the months before There was awareness in United States of america.
The study press release stated that they searched patients for treatment of cough in outpatient clinics “increased by more than 50% and surpassed the average number of the same complaints by more than 1,000 in the last five years.”
Harvested forms of coronavirus came into contact more, but at least, experts say
The published report showed an increase in patients seen in emergency departments for complaints of cough and acute respiratory failure.
The study found that a significant number of patients were identified with the spread of SARS-CoV-2 before clinical awareness and testing capabilities, with the end of December 2019 and continuing until February 2020 and continuing until February 2020.
The study authors also stated that their analysis demonstrated the importance of monitoring electronic health records (EHRs) to identify population change.
“It exemplifies how health system analytics combined with EHR data can provide powerful and agile tools to identify when future trends in patient populations are beyond expected limits.”
The advantage of chorus information, face masks, can be demonstrated by study SUGESTS
The study’s co-authors, UCLA Health’s Chief Information Officer, Drs. Michael Puffer said in the release, “Technology, including artificial intelligence driven by machine learning, has greater ability to identify and track irregular changes in health-related data, including significant excesses. Patients with specific disease-type presentations in the weeks or months before an outbreak. ”
By focusing not only on data from hospitals but also from outpatient settings, the researchers said this could help epidemiologists and health systems more rapidly detect future epidemics, the release said.
“For many diseases, data from the outpatient setting can provide an early warning to emergency departments and hospital intensive care units of the coming time,” lead author Dr. Said Joan Elmore, professor of medicine in the division of general internal medicine and health services research at David Geffen School of Medicine at UCLA.
“We can never know whether these additional patients in our area represented early and undetermined COVID-19 cases,” said Elmore. “But lessons learned from this epidemic, combined with health care analytics that enable real-time monitoring of disease and symptoms, can potentially help us identify and track emerging outbreaks and future epidemics. Huh.”