The medical field is awash with interesting and important patient data – blood pressure, body temperature, pulse rate, just for starters – data that practitioners have, of course, been faithfully collecting for decades.
Harness that data to a machine, and all kinds of useful tools emerge for physicians, giving them ways to provide better care, quicker treatment and, critically, allowing them to better allocate physician and hospital resources.
That was the thrust of a seminar Wednesday evening delivered by retired London, Ont., anesthesiologist Dr. Steven Dain called “Future Vision for Mass Casualty and Autonomous Care,” sponsored by Waterloo Medtech, a multi-disciplined association of health-care and technology professionals who aim to connect Waterloo Region’s innovation culture with the medical field and, in the process, “address the gap between healthcare research and its adoption.”
Dain laid out for his audience, many of them health-care providers, how smart, portable machines, powered by AI and machine learning, can help doctors provide a base level of care that can stabilize a patient and keep them alive. The capability is particularly useful in the wake of an event like a mass shooting or a natural disaster that overwhelms available care-givers and hospital resources.
The machines are additionally capable of recording and storing patient vital signs and other data for review when time and medical resources allow, enabling health-care workers to deliver smarter care when time and resources allow.
The barriers, Dain said, are significant, starting with the hodgepodge of technology currently in use by hospitals North America-wide. Making disparate hardware and software platforms – each written by a different company, each of them seeking to preserve market share – capable of sharing data, is a challenge, he says, one that has yet to be solved.
“In some hospitals in this province, I have to go through five different software packages to put together a medical record,” said Dain. “It's incredibly frustrating. It's incredibly time consuming.
“At one of the hospitals, I couldn't figure out how [a] drug was administered in the recovery room. I had to phone the [hospital] IT department and they bounced me all around the medical record departments. It took about half an hour to find somebody who knew how to do it.”
Dain is a self-described medtech disruptor. He is also a medical advisor for Waltham, Mass.-based DocBox Inc., a technology company that makes a suite of patient monitoring and care-delivery systems.
He got his start in medtech back in 1990, while working as an anesthesiologist at St. Joseph’s Hospital in London. He wanted to do a clinical study comparing techniques for tonsillectomies and needed to record patient oxygen saturation levels every five seconds.
“We didn't want to write it all down,” he said.
“And so we found some devices around the hospital which had serial interfaces on the back, and then we wrote custom software to collect the data.”
The homemade device and the software worked, and the study, which he said is cited to this day, was a success.
“We used an IBM 386,” he recalls. “It was their first laptop. It had a 360K floppy drive, running DOS.”
Dain said that in much the same way technology now helps pilots fly an aircraft during certain phases of a flight, reducing workload and enhancing safety, an opportunity exists for it to do the same for doctors.
He acknowledges that, apart from the problem of making software and hardware compatible, there are hurdles to overcome, not least among them the issues bound to unfold due to a device’s programming error or a hardware failure. Patient health could be compromised.
“Well, one has to look at it from a whole risk-management perspective,” said Dain. “What are the advantages of using the device? What are the disadvantages of using the device? If you have a critical event, a mass-casualty shooting like in Las Vegas, or the hurricane in Puerto Rico, where the medical requirements overwhelm the healthcare manpower, having [access to] closed-loop control robotics is far better than [providing no care].
“So, you know, a medic could run from person to person, do a very rapid triage, hook them up and say, ‘This [patient isn’t critical], this algorithm will help them, now let me go on to the next patient.’
“So you have to look at the whole big, overall perspective.”
Gaining buy-in from perennially cash-strapped provincial medical systems, or a hospital looking to reduce expenditures, is a problem, too.
“In Canada and the United States, there's a huge FUD factor – fear, uncertainty and doubt,” said Dain. “[The administrators will think], ‘I don't want to be the person that makes the multimillion-dollar decision to purchase a device and have my name plastered in the newspaper five years later if it didn't work.’”
The key, he said, is to prove the business case and show ways that technology saves money and stretches resources.
The introduction of technology to the medical field, he added, is still at its early stages, but one that is ultimately bound to “make an enormous difference."
