Doctor reacts to fail videos and explains common injuries. Find out what a doctor thinks about when they see a fail video! Join me to watch videos from the subreddit “what could go wrong” and learn about snake bites, infections, head injuries and knee injuries.
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Health care is undergoing significant transformation, and digital health data is at the center of this change. According to the Centers for Disease Control, nearly 80 percent of the nation’s health care institutions have converted to an electronic medical record (EMR) system from the old paper-based system. New technologies like smartphone applications are also creating new stockpiles of digital data. Genetic data is growing as well; scientists can sequence a person’s entire DNA within 24 hours and for less than ,000. Collectively, the amount of digital health data is expected to grow from 500,000 to 25 million terabytes over the next five years.
Why do we care that our health information is now in a digital format? How does it benefit all of us?
People who work in health care—and every industry for that matter—are smart, well trained, and do their best to stay up-to-date with the latest research, methodologies and trends. However, it is not rational to assume individuals have the depth of knowledge or data access to deal with every situation they encounter. Furthermore, the health care field is already understaffed, and this issue will only get worse as the looming mass retirement of baby boomers from the health care workforce creates an unprecedented supply-and-demand crisis.
Digitized health data has the potential to help mitigate this troubling situation. Predictive medicine uses computing power and statistical methods to analyze EMR and other health-related data to predict clinical outcomes for individual patients. Beyond health outcome forecasting, predictive medicine also can uncover surprising and often unanticipated clinical associations.
Oklahoma State University’s Center for Health Systems Innovation (CHSI), through its Institute for Predictive Medicine (IPM), is a leader in the exploding field of predictive medicine thanks to the unprecedented donation by Cerner Corporation of its HIPAA-compliant clinical health database, one of the largest available in the United States. Specifically, this dataset represents clinical information from over 63 million patients and includes admission, discharge, clinical events, pharmacy, and laboratory data spanning more than 16 years.
Over 20 full-time CHSI employees and nearly two dozen graduate students are working to execute the CHSI mission to transform rural and Native American health through data analytics. Further, CHSI has a number of ongoing partnerships with academia, health systems and corporations to extract value from digitized health data.
One example of CHSI’s numerous predictive medicine projects is an effort to help physicians determine whether the performance of particular cardiovascular drugs varies by gender or race, or both. Conversely, this study will help indicate which drugs perform poorly or even cause complications in these populations. Other CHSI studies are designed to give physicians insight into whether patients with a particular disease are likely to develop or already have an associated disease, which will aid in co-managing these conditions and lead to better health care. Another project is designed to help hospitals use data on patient demographic characteristics, comorbidities, discharge setting, and other medical information contained in comprehensive EMR systems to determine if patients are at high risk for being readmitted for disease-associated complications. If patients are considered high risk, they can get the care and support necessary to prevent frequent cycling through the health care system.
Predictive medicine can also lead to the creation and implementation of tools for managing larger patient loads, which can aid health care providers in dealing with supply-and-demand problems. For instance, CHSI has developed a clinical decision support system that can detect diabetic retinopathy with a high degree of accuracy using lab and comorbidity data available through primary care visits. This algorithm addresses the very real challenge of low patient compliance, particularly among rural and underserved populations, with annual ophthalmic eye exams, which are the gold standard for retinopathy detection and preventing vision impairment or total vision loss. CHSI is extending this work to other common diabetes-related microvascular complications with the goal of developing a comprehensive suite of tools that can help increase prevention and management of these complications among the nation’s growing diabetic population. Video Rating: / 5
Chronic disease is everywhere. CDC’s National Center for Chronic Disease Prevention and Health Promotion (NCCDPHP) is helping communities everywhere make changes to prevent chronic diseases in the future. Through various programs, we’re already seeing a difference. Together, we can help Americans live longer, healthier lives.
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Moderated by John Donovan of Intelligence Squared U.S., this year’s debate is: Retail Alliances – Not Washington – Will Save the U.S. Health Care System.
For the motion:
Dr. Rajaie Batniji, Co-Founder & Chief Health Officer, Collective Health
W. Gregg Slager, Senior Partner and Global Health Leader, EY
Against the motion:
Dr. Lisa Bielamowicz, Co-Founder & President, Gist Healthcare
Rosemarie Day, Founder & CEO, Day Health Strategies
Learn more about Transform: https://transformconference.mayo.edu/
Learn more about Mayo Clinic Center for Innovation: http://centerforinnovation.mayo.edu/
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THE WORST SIDEMEN INJURIES… – PLEASE LEAVE A LIKE!
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*Spoilers* The survivalists on Alone have a very small margin of error and they know a bad injury could mean the difference between the 0,000 cash prize and tapping out. #AloneOnHistory #AloneShow #Survival
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In this video, you will see how various orthopedic sports related injuries are treated!
Check out these other Sport Injury Videos from Dr. Webb
03:33 Derrick Rose ACL Tear
06:10 Description of ACL Surgery
06:40 Tony Romo Clavicle Fracture
07:40 Description of Clavicle Fracture Surgery
08:00 Gordon Hayward Ankle Fracture Dislocation
08:45 Description of Ankle Reduction
09:28 Surgery for Ankle Fracture/Dislocation
10:15 Paul George Broken Tibia
11:35 Description of Broken Tibia Surgery
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Recent advances in artificial intelligence and machine learning are changing the way doctors practice medicine. Can medical data actually improve health care? At this seminar, Harvard Medical School scientists and physicians will discuss how AI assists doctors in diagnosing disease, determining the best treatments and predicting better outcomes for their patients.
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