Do the words ‘command centre’ make you think of huge rooms with NASA scientists, expertly making sure a Mars rover lands safely on the Red Planet?

What if a command centre could revolutionize the patient experience in one of the busiest hospitals in North America, bringing a new standard of patient-centered, quality healthcare?

Combining Artificial Intelligence, Machine Learning, and professional expertise, Humber River Hospital in Toronto has launched the world’s first clinical analytic applications, in partnership with GE Healthcare Partners (GEHC). 

Displayed on large-screen monitors at HRH’s 4,500 square-foot Command Centre, these four new applications or analytic ’tiles’ use “standardized early warning systems, predictive analytics, real-time information from multiple digital systems,” alongside the professional expertise of experienced nurses.

Canadian Patient Safety Institute and Canadian Institute for Health Information data shows that 1 in 18 hospital stays in Canada involved at least one harmful event. This addition to the Command Centre means quicker alerts for clinical staff, and better protection for patients with conditions that make them vulnerable to risks of adverse events, or adverse outcomes.

The Humber River Hospital is the Greater Toronto Area’s (GTA) largest acute care centre, serving a catchment area of more than 850,000 in the city’s northwest. Opening in 2015, it was also North America’s first fully digital hospital. 

Just two years later, HRH opened the first generation of its Command Centre, a data-driven ‘mission control’ offering real-time insight on patient flow, via advanced algorithms and predictive analytics. As a result, the hospital has “unlocked” the equivalent of 35 additional beds — and the ability to treat thousands of additional patients.

Get an inside look at HRH’s Generation 2 Command Centre:

The U.K. National Health Service (NHS) is to partner with Amazon’s Alexa in order to provide health information. This is being piloted as an alternative to medical advice helplines and to reduce the number of medical appointments.

While the U.K. NHS is much admired around the world as a free-at-the-point-of-use healthcare system, health officials are always keen to find ways to reduce the strain on the systems, especially relating to medical visits where the process of booking appointments and waiting times for sessions with doctors can be lengthy. The average time to obtain a non-medical emergency appointment with a general medical practitioner is averaging around two weeks.

Although a non-emergency medical helpline is active (accessed by dialling 111), plus an online system, health officials are keen to explore other ways by which the U.K. population can access medical services. For this reason, NHS England is partnering with Amazon.

The use of Alexa voice technology not only offers an alternative service for digitally-savvy patients, it provides a potentially easier route for elderly and visually impaired citizens, as well as those who cannot access the Internet through a keyboard, to gain access to health information. This fits in with a new initiative from the U.K. Government called NHSX, which is about the NHS Long Term Plan intended to make more NHS services available digitally.

As PharmaPhorum reports, Alexa can now answer questions such as “Alexa, how do I treat a migraine?” and “Alexa, what are the symptoms of flu?”

Outside of the U.K., Amazon is working with several healthcare providers, including digital health coaching companies, in order to launch six new Alexa healthcare ‘skills’. According to Rachel Jiang, head of Alexa Health & Wellness: “Every day developers are inventing with voice to build helpful and convenient experiences for their customers. These new skills are designed to help customers manage a variety of healthcare needs at home simply using voice – whether it’s booking a medical appointment, accessing hospital post-discharge instructions, checking on the status of a prescription delivery and more.”

IBM has taken a step forward in disease prevention by designing an artificial intelligence technology that can predict the risk of breast cancer developing up to one year before the first signs of cancer appear.

With this new step in medical diagnosis, IBM has developed an artificial intelligence model which is capable of predicting malignant breast cancer within a year with an 87 percent accuracy rate (when the output from the machine is compared with expert radiologists.) In addition, the technology could correctly predict 77 percent of non-cancerous cases.

The prediction methods uses both mammogram images and medical records in order to make the assessment, based on a data review of the medical evidence. This is the first application of AI to draw upon both images and data to make a prediction in relation to breast cancer.

At the heart of the deep neural network technology is an algorithm, which was trained by IBM technologists along with medical professionals from Israel’s largest healthcare organizations. The training of the artificial intelligence took place using anonymized mammography images which were linked to biomarkers (like patient reproductive history) together with clinical data. The training data-set consisted of 52,936 images from 13,234 women who underwent at least one mammogram between 2013 and 2017.

The aim of the medtech is not to replace the physician, but to act as a ‘second pair of eyes’, providing a backup in the event that something has been missed through conventional patient assessment. This could prove especially useful in areas with staff shortages where a second medical professional is not available to provide a second assessment.

An assessment of the technology has been published in the journal Radiology. The research paper is titled “Predicting Breast Cancer by Applying Deep Learning to Linked Health Records and Mammograms.”

In related news, IBM is applying artificial intelligence to catch Type 1 diabetes much earlier. IBM’s other health technology project could help identify patients at risk and help chart a course for tracking the condition. The predictive tool is a joint project between IBM and JDRF (formerly known as the Juvenile Diabetes Research Foundation).