How Patient Tracking Data Can Drive Patient Safety
Big picture and in-the-moment insights from throughput analytics
By Megan Headley
Even as emergency departments (ED) grapple with increasing levels of demand, delivering nearly half of all medical care in the United States, they’re experiencing unprecedented physician and nursing shortages.
Although the Centers for Disease Control and Prevention’s latest available National Hospital Ambulatory Medical Care Survey shows a recent slight decrease in ED visits, from 145 million in 2016 to 139 million in 2017, it’s a generally upward-swinging trend. Couple this with dramatic physician and nursing shortages, and it becomes clear why strategies for improving patient flow are so critical. After all, poorly managed patient flow drives up readmissions, medical errors, and mortality rates.
While hospitals have long been looking for the right blend of strategies for improving throughput, today health systems have insight into entirely new levels of data, often available in real time, that can help identify flow bottlenecks as they happen. More EDs are now turning to data-rich patient tracking systems to improve patient flow, especially during peak times with high patient volume.
Sheila Minton, chief operating officer of TAGNOS, a clinical software provider, explains how the company’s technology supports patient care. TAGNOS provides health systems with real-time location systems such as radio frequency identification (RFID) tags to track patients as well as equipment. By RFID-tagging patients with identification and chief complaint information, the hospital gains more accurate data around how many patients are coming into the facility, how long they’re waiting, how they’re moving through the process, where they’re interacting with staff, and who needs to be alerted to their arrival.
“The fact that we have this real-time data that we’re constantly collecting about patients and how they move through the journey enriches and allows us to build off of historical data sets by incorporating the new information,” Minton explains. In addition to reducing errors from manually entered data, this real-time information provides insight into trends that can be used to support staffing today and in the future.
For example, Minton shares, “Our predictive model will look at what was happening at the same time a year ago, what was done just a few weeks ago, what was done just a few days ago, and we can even add into our model what happened this morning so we can predict what’s going to happen this afternoon.” Predictive analytics begins to leverage the massive amounts of data health systems gather by using that data to predict future conditions.
As Minton puts it, “That’s the power of having that real-time data constantly being processed in the predictive model. We can get much more precise prediction for leadership to work from.”
While patient tracking can provide department leaders with a big-picture perspective of where bottlenecks are occurring, this type of connected system can also boost moment-to-moment efficiency. As a case in point, Minton points to Adventist Health White Memorial (AHWM), a 353-bed hospital in Los Angeles. The facility wanted to identify opportunities to speed up OR turnaround time via improved patient throughput. Rather than relying on nursing to take time to ask environmental services staff to turn over a room, an RFID tag on the patient sends out automatic alerts by text or through a mobile app at different stages of the patient’s journey.
“By simply alerting EVS staff the moment that the patient [is] wheeled out of the room that the room is now empty and ready to be cleaned, they were able to reduce the minutes spent on room turnover times and therefore the overall OR cycle time to where the next patient could get in the room quickly for their procedure,” Minton says.
“Since we implemented the solution, we have reduced EVS response times to operating rooms by 41%, enabling us to significantly improve our operational efficiency and reduce costs while seeing more patients,” adds Randy Saad, director of perioperative services at AHWM. That faster throughput has amounted to more than $1 million in savings.
Minton acknowledges that the RFID system has found greater acceptance in ORs than EDs because, as she explains, “With trauma patients, in some cases, it’s difficult for [staff] to tag the patients and in a lot of cases they don’t even have all the information.” However, the surge crisis unfolding with the COVID-19 pandemic provides evidence of how critical patient tracking can be in the ED.
“I think that the current crisis makes a solution like this more of a necessity,” Minton says. “It will not only be needed in the hospitals, but now with the popup testing sites, in areas like New York where they have had to open up the Javits Center as a disaster response center to help with patients. We’re needing to track patients outside of the walls of the hospital.”
In addition, Minton says, the pandemic has identified another critical layer of patient tracking.
“I think contact tracing is going to be huge in the future,” she adds. “We have reports that can show the interactions between patients, staff, and assets. Where there wasn’t as much excitement about that factor prior to COVID-19, it’s definitely something we’re hearing a lot more about now.”
Perhaps the most critical benefit of bringing in patient tracking, Minton finds, is that the insight supports health systems in identifying clear answers to ongoing problems. “In doing the patient tracking, you start to get an awareness that’s not just anecdotal anymore,” she says. “You start to see, ‘Now I understand why this patient waited so long. It’s because once I dug a little further, I saw that no one attended to this patient for longer than what we expected.’ Then then they’ll start to incorporate staff tracking. Or they might find that maybe patients are waiting a long time because staff is having trouble finding equipment, and that’s where asset tracking gets introduced.”
Healthcare has long understood that “if you can’t measure it, you can’t improve it.” However, today’s intelligent tracking and predictive analysis tools support a deeper level of data at every patient touchpoint and just may help drive patients more quickly to the right care solution.
Megan Headley is a freelance writer and owner of ClearStory Publications. She has covered healthcare safety and operations for numerous publications. Headley can be reached at megan@clearstorypublications.com.