Arab News: King Salman orders free coronavirus treatment in Saudi Arabia, including residency violators. “King Salman has ordered free treatment be provided to all coronavirus patients in all government and private health facilities in Saudi Arabia. The Kingdom’s health minister, Dr. Tawfiq bin Fawzan Al-Rabiah, announced the king’s order at a press conference in Riyadh on Monday and said it included citizens and residents – even those in violation of residency laws.”
Washington Post: ‘We care, we grieve, we love’: Dispatches from doctors, nurses on the front lines in the battle against coronavirus. “An emergency room doctor in New Jersey who had to intubate a fellow physician. A doctor in New York who had to tell her patient’s wife he was dying over FaceTime. An ICU nurse in Michigan who had to spend a 13-hour shift caring for two critically ill patients essentially on her own. These are just some of the firsthand accounts from health professionals in emergency departments and critical care units across the United States that have emerged on social media in recent weeks — providing raw, unfiltered glimpses into the lives of those on the front lines of the country’s battle against the novel coronavirus.”
University of Toronto: U of T researchers create interactive tool to help hospitals plan for COVID-19. “A group of researchers at the University of Toronto’s Dalla Lana School of Public Health have developed an interactive online tool that helps hospitals and other health-care providers estimate their capacity to manage new cases of COVID-19. By taking into account the number of acute and critical care resources available to a specific health-care provider, data on the age distribution and severity of COVID-19 cases and expected duration of patient stays, the online tool helps hospitals model their capacity to respond to the fast-moving pandemic.”
CBS News: How to donate personal protective equipment like masks and gloves to health care workers. “Public health experts have advised people not to stockpile masks — they say only people who are already sick and medical professionals should wear masks. But panicked members of the public had already exhausted existing supplies, leading to widespread shortages. Desperate doctors and nurses are taking to social media to plead for donations of much-needed supplies using the hashtag #GetMePPE. However, it can be difficult to figure out exactly how to get these supplies into the hands of the people who need them.” Good-sized list.
Mashable: Relying on crowdfunding to pay health bills? It’s more common than you might think.. “Researchers from NORC at the University of Chicago recently conducted a survey to learn about the prevalence of crowdfunding health campaigns. It turns out that a large swath of the American public — approximately 50 million, or 20 percent of Americans — have contributed to these sorts of campaigns. What’s more, eight million Americans have started a campaign to help pay for medical expenses for themselves or someone in their household, while 12 million had started a campaign for someone else. According to the researchers’ survey, that’s three percent and five percent, respectively.”
BDaily News: Over 27 Million People Affected in Healthcare Data Breaches Last Year. “Bitglass has released its sixth annual Healthcare Breach Report. Each year, Bitglass analyses data from the U.S. Department of Health and Human Services’ ‘Wall of Shame,’ a database containing information about breaches of protected health information (PHI). In 2019, these breaches collectively affected over 27 million individuals. Bitglass’ latest report analyses the breaches of 2019, compares them to those of previous years, and reveals key trends and cybersecurity challenges facing the healthcare industry.”
UCLA Anderson Review: Machine Learning Can Help Reduce Postsurgical Hospital Readmissions. “In a study published in the medical journal Anesthesiology, UCLA Anderson’s Velibor V. Mišić and Kumar Rajaram, Ronald Reagan UCLA Medical Center’s Eilon Gabel and Ira Hofer, and University of Pittsburgh’s Aman Mahajan report devising three ‘machine learning’ models that scored significantly higher than standard statistical programs in predicting which surgical patients were at greatest risk of readmission.”