Big Data keeps getting bigger, and the healthcare industry is working hard to leverage the information it’s amassing to make populations — and individual patients — healthier. A key component impacting patients on a personal level is predictive technology.
“In same vein as predictive modeling for population health, predictive technology is appearing as wearable sensors and even phone apps to ascertain changes in a patient's vitals, routines and even moods,” Healthcare IT News explained in a recent report.
The thinking behind predictive technology is something like this: data is information, and by collecting patient data in real time, health care providers and caregivers can use that information to predict, and work to prevent, patient harm before it has a chance to happen.
One of the clearest examples of predictive technology is the Ginger.io app, which tracks “digital exhaust” from a patient’s smart phone to continually assess his or her mental health status. The tool is geared to patients with depression and anxiety.
By collecting day-to-day data on a particular patient—say, her patterns of texting, calling, and even moving about—and combining it with predictive models, the app can identify when that patient may be becoming symptomatic. For example, a sudden ceasing of activity may raise a red flag.
"It's a foundation that allows for the identification of the right intervention for the patient," said ginger.io’s Pat Saxman in the Healthcare IT News report. "The smartphone is the most powerful sensor in healthcare. Digital exhaust creates a signature for the individual—we look for changes in communication patterns. It chronicles what happens between clinic visits."
Predictive technology from CISCOR allows skilled nursing facilities to learn individual resident’s patterns of movement and activity. When the system detects a deviation from the norm, it sends an alert to caregivers.
"This allows caregivers the opportunity to intercede before an incident occurs," company principal Sam Youngwirth told Healthcare IT News. "A key element is the ability to provide a system that can be individualized to each resident."
Long-term care, the article explains, is especially interested in predictive technology because of its ability to monitor residents in an unobtrusive manner. A spokeswoman from PointRF Solutions said its next generation of smart infrastructure will provide patient health metrics, such as pedometer and heart rate.
In fact, robots are in line to not only provide companionship but also remote monitoring of patients in the future, according to Laurence M. Yudkovitch, a product manager at RF Technologies’ Senior Living Solutions.
What’s more, “artificial intelligence agents, such as Apple's Siri or Amazon's Echo, will be expanded to not only answer questions, but also store patient preferences and detect mood changes,” Yudkovitch told the publication.
Things that would have been considered science fiction just years ago are quickly becoming reality. And healthcare institutions are biting, with the understanding that data can potentially keep patients healthier and safer. Costs, too, are lowered when adverse health events are prevented.
Is your organization using predictive technology? How is it impacting patient care?