Orion Health offers IT solution for current pandemic
March 25, 2020
TORONTO – A computerized system for remote patient management, developed by Orion Health, is now being used in New Zealand, France and elsewhere to monitor patients who have tested positive for COVID-19, enabling them to remain in their own homes. The solution could be quickly adapted in Canada, too, and extended to homes to help monitor patients in this country, the company said.
By remotely managing patients who are not yet showing severe symptoms, the Orion system has been able to reduce pressure on medical facilities and to free up beds at sites in New Zealand and in Paris, France.
Orion Health’s Electronic Health Record platform is already widely deployed in Canada. In particular, in Quebec, it is used for managing chronic diseases, such as diabetes and heart failure.
It would not be difficult to extend the use of the system across the country for managing COVID-19 patients, said Dr. Chris Hobson (pictured on left), the company’s Chief Medical Officer.
With the software on a smartphone or home computer, patients can report on whether their cough or shortness of breath is getting better or worse, and if their temperatures are getting higher. And by adding simple plug-ins like oxygen meters, they can also report on their oxygen saturation.
“You can report on this every day, or every six or eight hours,” said Dr. Hobson. And because the Orion Health solution has been optimized for population management, it can monitor large groups of patients on a centralized dashboard, alerting healthcare professionals with easy-to-read red, amber or green signals.
It points out to nurses and healthcare professionals at centralized locations whether a certain patient is in distress and needs attention. “You can then focus the ones who need to be focused on,” said Dr. Hobson.
The system logs the data and displays trends over time – for whole populations and individual patients. Also, the patient’s health record can be tied in too, for quick reference.
So for example, if a patient with COVID-19 also has diabetes or other issues, a nurse or physician can take these factors into account.
Dr. Hobson noted that a parallel solution – video visits for patients – have recently become popular in Ontario, as the province has provided a new billing code for telemedicine for all physicians. Virtual visits are also increasing in British Columbia, Alberta and Saskatchewan.
However, as useful as they are, video visits will likely not be enough to support the huge number of patients who could be affected by COVID-19 if a massive wave hits.
“We didn’t want to have a purely one-on-one solution,” he said. Instead, the Orion platform is capable of simultaneously monitoring thousands of patients.
“The solution we’ve developed is designed for large numbers of patients,” said Andrea Tait (pictured on right), vice president, client value at Orion Health Canada. She noted that the system can help with social distancing, keeping infected patients apart from care-givers such as visiting nurses and other home healthcare providers, while allowing healthcare professionals to actively monitor those who have tested positive or shown symptoms.
“Social distancing is a big part of this,” she said. “It’s critical to preserve the health and safety of our caregivers.”
Because the system is collecting a large amount of data, artificial intelligence and machine learning can be used to analyze it. “Once we have the data, using AI, we’ll be able to figure out what works and what doesn’t when it comes to diagnosis and treatments,” said Dr. Hobson.
In comparison, Dr. Hobson said a recent population health project, in which Orion Health was involved in the United States, made use of AI to analyze whether a large group of expecting women were facing high-risk pregnancies.
The software analyzed 46 different factors over time, and successfully predicted which women to put into the high-risk category. It was able to do this at 12 weeks of pregnancy, compared with the standard 30 weeks, when the process is done manually.
Because the AI system could pick up high-risk pregnancies at a much earlier stage, planning and treatment for the women could start earlier, too.
“Physicians can typically only juggle six or seven factors at the same time when making clinical decisions,” said Dr. Hobson. “The machine learning system could easily handle 46.” As well, it was also analyzing the data of not just one patient at a time, but a large number of patients.
Tait said that artificial intelligence will assist in the treatment of the novel coronavirus as well, as AI is good at learning over time.
“Already, what we know about COVID-19 is evolving,” said Tait. “For example, we initially believed that young people were not affected by it, but that view has recently changed with new information.”
She said that machine learning systems can absorb a wide range of knowledge, inputs and experiences to arrive at better forms of diagnosis and therapy. “Remote monitoring generates a lot of data,” she said. “Using AI, it can help determine more about the disease and how to manage it.”