The Cleveland Clinic has a history of being on the bleeding edge of health IT and its new CEO Tom Mihaljevic has made it clear that the Ohio-based health system will keep pushing ahead as a medical technology pioneer. "Most of our plans for the future will depend on digital platforms: telemedicine, data analytics, artificial intelligence," Mihaljevic said during the State of the Clinic address in late February. "Digital technology will allow us to deliver smarter, more affordable and more accessible [care]. The Cleveland Clinic has always been an early adopter, beginning with our electronic medical records. But now, we have to take technology even more seriously.
The academic medical center of the University of Michigan is leveraging investments in artificial intelligence, machine learning and advanced analytics to unlock the value of its health data. According to Andrew Rosenberg, MD, chief information officer for Michigan Medicine, the organization currently has 34 ongoing AI and machine leaning projects, 28 of which have principal investigators. "There's a lot of collaboration around these projects--as there should be for the diversity of thought and background needed to deal with complex problems--working with at least seven other U of M schools," Rosenberg told the Machine Learning for Health Care conference on Friday in Ann Arbor, Mich. "That's one of the powers that we enjoy." One of the machine learning projects cited by Rosenberg leverages a combination of electronic health records, monitor data and analytics to predict acute hemodynamic instability--when blood flow drops and deprives the body of oxygen--which is one of the most common causes of death for critically ill or injured patients.
The core business of healthcare organizations is to care for the medical needs of patients. Yet information security is a key component of any healthcare organization. There are electronic healthcare records (EHRs) and HIPAA privacy regulations, both of which make your average hospital or big healthcare practice an enticing target for hackers looking to steal data. "We are attacked about a million times a day," said Jennings Aske, chief information security officer at NewYork-Presbyterian Hospital. Aske joined the organization in 2015 to create a cyber security strategy for the organization, and he used platforms from Splunk which he said was "basically a security analytics platform."
A team of data scientists, researchers and clinicians from UNSW Sydney have won a major prize at the second annual Healthcare Artificial Intelligence Datathon held at the National University of Singapore (NUS). The two-day event – organised jointly by the National University Health System (NUHS), Massachusetts Institute of Technology (MIT) and NUS – hosted more than 200 local and international data scientists and clinicians last weekend to address current problems in healthcare with the latest machine learning and artificial intelligence technologies. The joint UNSW-NUS team won first prize in the Critical Care Track, competing against eight other teams to analyse clinical data contained in the MIT/Philips eICU Collaborative Research Database, comprising information on more than 200,000 patients treated in intensive care units in US hospitals over the past five years. The UNSW-NUS team included researchers Oluwadamisola Sotade, Dr Mark Hanly and Oisin Fitzgerald from UNSW's Centre for Big Data Research in Health, Dr Tim Churches, data scientist from the Ingham Institute for Applied Medical Research and UNSW South Western Sydney Clinical School, and Dr Peter Straka from UNSW Mathematics and Statistics. "The installation of next-generation electronic medical records systems in ICUs and throughout hospitals enable very sophisticated machine-learning and artificial intelligence algorithms to be developed to assist busy clinicians in patient care and treatment decision making." said Dr Churches.
For today's leading deep learning methods and technology, attend the conference and training workshops at Predictive Analytics World for Healthcare, June 16-19, 2019 in Las Vegas. Moving patient data online has been a great boon for the practice of medicine. Patient records, formerly pieces of paper in a folder, are transitioning to electronic health records, or EHRs. While this has done wonders for transferring records between offices and aiding in connecting technology like wearables and providing big data for machine learning, the quantity also raises questions of patient privacy and data security. The start of this story is in the volume of data.