Health care providers have long used the metric system for billing, but some companies are now using a “mega” computer to track and assess patients, and it’s gaining traction as the fastest-growing use of a technology that dates back decades.
The new system is the brainchild of a pair of Johns Hopkins University researchers who have spent the past two years testing the delta computer systems used by the health care industry.
Their latest findings are part of a growing field of medical diagnostics that’s combining computers and humans, and is now becoming increasingly commonplace in hospitals, outpatient clinics and even emergency departments, according to the American Medical Association, the American College of Surgeons and others.
The medical diagnosticians, nurses, pharmacists and others who use the delta system have long been using a system that combines a single-processor computer with a number of other components that monitor the health of patients.
They use it to detect signs of problems and adjust medication, for instance, by using an electrocardiogram (ECG) machine to measure the electrical activity in the heart.
But the researchers said they now see a “massive” adoption of the delta technology by other healthcare professionals and are pushing for it to be widely adopted.
They say the system can be easily customized to the needs of different people.
In a study published this week in the journal Scientific Reports, the researchers say their software could be used to track patients, monitor their health and assess their symptoms.
It could also be used for detecting or treating other illnesses, they said.
The researchers developed the software in a lab at Johns Hopkins in the early 1990s to help them track and diagnose patients and other medical problems.
They also wanted to develop a “microprocessor” that would combine a number or devices to detect and track patients’ health, and they used that chip to monitor the physical and electrical activity of patients and their health status.
They hoped the software would help diagnose or treat chronic health problems.
“We wanted to figure out if we could integrate the microprocessor, the delta, the software and the hardware into one device that would have a very high reliability, low cost and very low power consumption,” said study co-author Andrew J. Hagerty, who is now a professor of electrical and computer engineering at the University of Maryland and a member of the Johns Hopkins School of Engineering.
He said the researchers also wanted their system to be flexible enough to be used by doctors, doctors’ assistants, nurses or other healthcare workers, who may not be familiar with the systems they are using to measure and treat health.
“The whole concept was to take that existing system and apply it to diagnostics,” he said.
“What we were able to do is put it into a medical imaging system and see if it could be useful.”
The system was tested at Johns Hawkins Medical Center and at Johns Stony Brook University Medical Center in New York, as well as at Johns and Georgetown University in Washington.
Hagerty said his team had to work closely with the Johns and Stonybrook teams to make sure that their software worked together.
“They’re pretty good at communicating and working with each other, and we had to do some work to make that work,” he explained.
The system works by comparing readings from a number devices to a “state map,” which is a series of measurements that doctors make about the body.
A device that is active is the one with the highest reading.
The devices that are inactive are the ones with the lowest readings.
The devices include a heart monitor, a skin monitor and a blood pressure monitor.
The software can also collect information about breathing, heart rate, respiration rate, blood pressure, the temperature of the body and other health data.
When patients are tested, the system then analyzes the data and determines how much a particular device is active and how much it is inactive.
The system then sends the results to a central server for analysis and a report, Hagery said.
A typical patient is tested in the laboratory, the team said.
A patient could have a heart condition, diabetes or a heart defect that is causing their condition.
But it can be difficult to determine if a patient is healthy until the system identifies a condition that causes a high or low reading on a device.
The software can then monitor how the system is functioning and determine if it has caused the patient to deteriorate.
Hagers said his research team used a system called “quantified self” that was developed at Johns in the 1970s and has since been expanded to include more health and medical problems, including cancer.
He said his goal was to find ways to make a system more sensitive to different conditions.
“A lot of people say that this system doesn’t work well for all conditions, but we’ve found that it works well for a lot of conditions,