What Are The Best Countries For Health Care? U.S. Last Among Wealthy Nations

International Business Times

The United States finished dead last in an analysis of health care quality across several wealthy nations, ranked either the worst or close to worst in categories like affordability, administrative efficiency and the health of the overall population. A report from The Commonwealth Fund, a private, American-based foundation focused on health care issues, compared the country to seven others in Europe -- France, Germany, the Netherlands, Norway, Sweden, Switzerland and the United Kingdom -- as well as to Canada, Australia and New Zealand. Those other 10 were found to spend significantly less on care while enjoying better health, after the foundation inspected 72 "indicators" throughout the health care systems of each nation, which included gathering data from patient and doctor surveys as well as from the World Health Organization and other agencies. "Based on a broad range of indicators, the U.S. health system is an outlier, spending far more but falling short of the performance achieved by other high-income countries," the report said. "The results suggest the U.S. health care system should look at other countries' approaches if it wants to achieve an affordable high-performing health care system that serves all Americans."


New Data Shows Artificial Intelligence Technology Can Help Doctors Better Determine Which Patients are Having a Heart Attack

#artificialintelligence

ABBOTT PARK, Ill., Sept. 12, 2019 -- Abbott announced that new research, published in the journal Circulation, found its algorithm could help doctors in hospital emergency rooms more accurately determine if someone is having a heart attack or not, so that they can receive faster treatments or be safely discharged.1 In this study, researchers from the U.S., Germany, U.K., Switzerland, Australia and New Zealand looked at more than 11,000 patients to determine if Abbott's technology developed using artificial intelligence (AI) could provide a faster, more accurate determination that someone is having a heart attack or not. The study found that the algorithm provided doctors a more comprehensive analysis of the probability that a patient was having a heart attack or not, particularly for those who entered the hospital within the first three hours of when their symptoms started. "With machine learning technology, you can go from a one-size-fits-all approach for diagnosing heart attacks to an individualized and more precise risk assessment that looks at how all the variables interact at that moment in time," said Fred Apple, Ph.D., Hennepin HealthCare/ Hennepin County Medical Center, professor of Laboratory Medicine and Pathology at the University of Minnesota, and one of the study authors. "This could give doctors in the ER more personalized, timely and accurate information to determine if their patient is having a heart attack or not." A team of physicians and statisticians at Abbott developed the algorithm* using AI tools to analyze extensive data sets and identify the variables most predictive for determining a cardiac event, such as age, sex and a person's specific troponin levels (using a high sensitivity troponin-I blood test**) and blood sample timing.


Artificial Intelligence Can Help Doctors Better Detect Heart Attacks

#artificialintelligence

Caption: Paramedics respond to an emergency. Scientists have developed an artificial intelligence tool that lets doctors determine whether someone is having a heart attack much faster than current methods. New research published by healthcare firm Abbott shows that its algorithm could enable hospital accident and emergency departments to more accurately identify and treat patients having a cardiac arrest. The study, which involved researchers from the U.S., Germany, U.K., Switzerland, Australia and New Zealand and more than 11,000 patients, found that AI could provide doctors a more comprehensive analysis of the probability that a patient was having a heart attack. Agim Beshiri, a senior medical director at Abbott, said: "AI technology has the capability to consider many variables, characteristics and data points and combine them in seconds into meaningful results. "Because of today's advancements in computational power and AI applications, healthcare stands to benefit greatly by this approach where clinicians have to do this with their patients every day." Developed by a team of physicians and statisticians at Abbott, the algorithm uses machine learning techniques to enable a more individualized calculation of a person's heart attack risk. The technology aims to improve and quicken heart attack diagnosis by analyzing extensive datasets and identifying factors such as age, sex and a person's specific troponin levels (a cardiac biomarker). Abbott said the algorithm is designed to help address two barriers that exist today for doctors looking for more individualized information when diagnosing heart attacks. The first is that international guidelines for using highly sensitive troponin tests don't always account for personal factors, impacting test results. And the second is that while these guidelines recommend that doctors carry out troponin testing at fixed times, they don't consider a person's age or sex and put patients into a one-size-fits-all situation. However, Abbott's algorithm differs from existing approaches as it takes into consideration personal factors and troponin blood test results over time. Beshiri added: "The World Heart Organization estimates that 17.9 million people die from cardiovascular disease each year, and 85% are due to heart attacks and strokes.


Artificial Intelligence Can Help Doctors Better Detect Heart Attacks

#artificialintelligence

Caption: Paramedics respond to an emergency. Scientists have developed an artificial intelligence tool that lets doctors determine whether someone is having a heart attack much faster than current methods. New research published by healthcare firm Abbott shows that its algorithm could enable hospital accident and emergency departments to more accurately identify and treat patients having a cardiac arrest. The study, which involved researchers from the U.S., Germany, U.K., Switzerland, Australia and New Zealand and more than 11,000 patients, found that AI could provide doctors a more comprehensive analysis of the probability that a patient was having a heart attack. Agim Beshiri, a senior medical director at Abbott, said: "AI technology has the capability to consider many variables, characteristics and data points and combine them in seconds into meaningful results.


Artificial Intelligence Can Help Doctors Better Detect Heart Attacks

#artificialintelligence

Scientists have developed an artificial intelligence tool that lets doctors determine whether someone is having a heart attack much quicker than current methods. New research published by healthcare firm Abbott shows that its algorithm could enable hospital accident and emergency departments to more accurately identify and treat patients having a cardiac arrest. The study, which involved researchers from the U.S., Germany, U.K., Switzerland, Australia and New Zealand and more than 11,000 patients, found that AI could provide doctors a more comprehensive analysis of the probability that a patient was having a heart attack. Agim Beshiri, a senior medical director at Abbott, said: "AI technology has the capability to consider many variables, characteristics and data points and combine them in seconds into meaningful results. "Because of today's advancements in computational power and AI applications, healthcare stands to benefit greatly by this approach where clinicians have to do this with their patients every day." Developed by a team of physicians and statisticians at Abbott, the algorithm uses machine learning techniques to enable a more individualized calculation of a person's heart attack risk. The technology aims to improve and quicken heart attack diagnosis by analyzing extensive datasets and identifying factors such as age, sex and a person's specific troponin levels (a cardiac biomarker). Abbott said the algorithm is designed to help address two barriers that exist today for doctors looking for more individualized information when diagnosing heart attacks. The first is that international guidelines for using high sensitive troponin tests don't always account for personal factors, impacting test results. And the second is that while these guidelines recommend that doctors carry out troponin testing at fixed times, they don't consider a person's age or sex and put patients into a one-size-fits-all situation. However, Abbott's algorithm differs from existing approaches as it takes into consideration personal factors and troponin blood test results over time Beshiri added: "The World Heart Organization estimates that 17.9 million people die from cardiovascular disease each year, and 85% are due to heart attacks and strokes.