Improving operating room capacity management through data analytics and machine learning will be the breakfast keynote topic of discussion at the upcoming 2020 OR Business Management Conference. Ashley Walsh, senior director of client services at LeanTaaS, Inc., a Silicon Valley software innovator that increases patient access and transforms operational performance for healthcare providers, and Melissa Pressley, management engineer at Duke University Health System (DUHS), will address the audience on Thursday, Jan. 30, at 7:30 a.m. in the Global Ballroom of the Bonaventure Resort & Spa in Weston, Florida. "Improving OR utilization and improving surgeon access to OR time significantly enhances the financial results for hospitals and health systems, increases patient access, and facilitates surgeon recruitment and retention" "DUHS has leveraged EHR data to improve OR access with mobile and web technologies and increase accountability with surgeon-centric metrics and reporting to help our surgeons better understand the "why" behind OR metrics," said Pressley. "I'm looking forward to sharing how DUHS and LeanTaaS have enhanced the patient experience while balancing surgeon needs, among other improvements." DUHS is among several leading health systems in the U.S. that have deployed the LeanTaaS iQueue for Operating Rooms solution to effect data-driven changes to their approach to capacity management.
An algorithm to predict which people may experience a mental health crisis has been trialled in the UK and found effective enough for routine use. A version that would track people's mobile phone calls, messages and location in a bid to improve accuracy is now being considered. Birmingham and Solihull Mental Health NHS Foundation Trust worked with Alpha, a division of Spanish telecomms firm Telefonica, which owns O2, to see if there was any benefit in automatically flagging the people thought most at risk of experiencing a mental health crisis to NHS staff. The results of the Predictive Analytics project, released under freedom of information rules, suggest there is. The project ran between November 2018 and May 2019.
A team of University of Illinois researchers estimated the mortality costs associated with air pollution in the U.S. by developing and applying a novel machine learning-based method to estimate the life-years lost and cost associated with air pollution exposure. Scholars from the Gies College of Business at Illinois studied the causal effects of acute fine particulate matter exposure on mortality, health care use and medical costs among older Americans through Medicare data and a unique way of measuring air pollution via changes in local wind direction. The researchers - Tatyana Deryugina, Nolan Miller, David Molitor and Julian Reif - calculated that the reduction in particulate matter experienced between 1999-2013 resulted in elderly mortality reductions worth $24 billion annually by the end of that period. Garth Heutel of Georgia State University and the National Bureau of Economic Research was a co-author of the paper. "Our goal with this paper was to quantify the costs of air pollution on mortality in a particularly vulnerable population: the elderly," said Deryugina, a professor of finance who studies the health effects and distributional impact of air pollution.
DAVOS, Switzerland (Reuters) - Sundar Pichai, the CEO of Alphabet Inc and its Google subsidiary, said on Wednesday that healthcare offers the biggest potential over the next five to 10 years for using artificial intelligence to improve outcomes, and vowed that the technology giant will heed privacy concerns. U.S. lawmakers have raised questions about Google's access to the health records of tens of millions of Americans. Ascension, which operates 150 hospitals and more than 50 senior living facilities across the United States, is one of Google's biggest cloud computing customers in healthcare. "When we work with hospitals, the data belongs to the hospitals," Pichai told a conference panel at the World Economic Forum in Davos, Switzerland. "But look at the potential here. Cancer if often missed and the difference in outcome is profound. In lung cancer, for example, five experts agree this way and five agree the other way. We know we can use artificial intelligence to make it better," Pichai added.
Our Innovation Analysts recently looked into emerging technologies and up-and-coming startups in the healthcare industry. As there is a large number of startups working on a wide variety of solutions, we decided to share our insights with you. So, let's take a look at promising artificial intelligence (AI) solutions. For our 6 picks of AI startups, we used a data-driven startup scouting approach to identify the most relevant solutions globally. The Global Startup Heat Map below highlights 6 interesting examples out of 1.038 relevant solutions.
Technology is evolving at an astonishing rate and transforming many different sectors. One area where technology is having a huge impact is the healthcare industry. This is fantastic news because it can be used to save lives, improve care and also lighten the load for staff who are often overworked and stressed. There are many different ways that technology is being used in healthcare which can make it hard to know the best ways in which it is being used. With this in mind, here are just a few ways tech is being used to improve the healthcare system.
These data, if harnessed appropriately, could enable health-care providers to target the causes of ill-health and monitor the effectiveness of preventions and interventions. For this reason, policy makers, politicians, clinical entrepreneurs, and computer and data scientists argue that a key part of health-care solutions will be artificial Intelligence (AI), particularly machine learning.
A group of high school students was one of the top teams to emerge from the recent AI Tech Sprint by the Department of Veterans Affairs, delivering a web application that could help match cancer patients to clinical trials. The three students from Northern Virginia entered their work in a competition that included software companies like Oracle Healthcare and MyCancerDB. Digital consulting company Composite App took the $20,000 first place prize for its solution -- a tool for helping patients stay on track with their care plan -- but the clinical trials team got an honorable mention. The tech sprint was organized by the VA's new AI institute, and it focused on partnering with outside organizations and companies interested in applying artificial intelligence tools and techniques to VA data. The high school team's members -- Shreeja Kikkisetti, Ethan Ocasio and Neeyanth Kopparapu -- met as part of the Northern Virginia-based nonprofit Girls Computing League.
You may think that artificial intelligence (AI) will make doctors obsolete soon but that day is still far off. In fact, computers are not that intelligent just yet. Most computer solutions emerging in healthcare rely on algorithms written to analyse data and recommend treatments. They do not rely on computers thinking independently. The computers in question are fed with large amounts of known data and use rules or algorithms set by experts to extract information and apply it to a health issue or problem.
If you ask the average person for a working definition of artificial intelligence (AI), you're likely to receive a slew of answers that boil down to the same concept: robots. Most nonexperts are still receiving their information on AI from science fiction films and clickbait articles with headlines adjacent to "Machines to Replace Humans by 2030." It's no wonder, then, why patients would be apprehensive toward AI in a hospital setting. They want a doctor to handle their treatment, not a computer. But what these patients don't often know is that AI is already being used in hospitals globally.