10 Oct 2022
How come? What if? Why not? Who said?
These are the questions driving Shery Wachtel, PhD, RN, CNS-CC, CCRN-K, Clinical Nurse Scientist at Christus Health, to find a better way to predict patient deterioration.
In a recent Voalte Platform Virtual User Experience conference session titled, “Predicting the Warning,” Wachtel shared her research and learnings regarding evidence-based surveillance practices that take real-world nursing workflows into account. Her presentation shared her journey to find a way to make nursing surveillance more effective for patients — and for busy nurses.
After combing through 20 years of evidence related to patient surveillance, Wachtel compared the positive predictive values (PPV) of common forms of alarm/alert monitoring today:
Patient monitors: 2-4% PPV
Humans: 18-24% PPV
Early warning scores: 22% PPV
Integrated monitoring: 95% PPV
While patient monitors, human surveillance and early warning score programs can all produce effective warnings, they all depend upon the timeliness of the data going to them.
The information coming out will only be as accurate as the data going in.
Shery Wachtel, PhD, RN, CNS-CC, CCRN-K, Clinical Nurse Scientist at Christus Health„
Some units may have RNs entering vital signs into the EMR as they measure them in real time. However, on many units, stretched clinicians may take 20 sets of vital signs in a row, then enter them into the EMR all at once — perhaps an hour after the first set was taken.
“If that takes an hour to get through because they keep getting [interrupted], how real is your data by the time it gets escalated?” asks Wachtel. “We’re still leaving it up to manual processes.”
Wachtel has worked closely with her in-house technology teams and medical device integration vendors to identify new ways of monitoring that go beyond physiological data collection — and actually synthesize it to help nurses choose the right actions, sooner.
“They asked me, ‘What do you want, Shery?’” Wachtel recalls. “And I said, ‘I want something that’s going to come up and tap me on the shoulder and say, ‘Hey, that patient in 501 is sick and you need to go check him out.’ And not only tell me he’s sick — but tell me what parts of him are making him sicker or more unstable.”
Thus began the journey to a better method of integrated patient monitoring.
Christus Health is now using the PatientWatch® solution and VISENSIA Safety Index to help their busy nurses better monitor patient statuses and changing risk levels. Situated directly next to their telemetry data central stations, the PatientWatch viewer displays five vital signs:
Beyond tracking these physiological data points individually, the system assesses how each parameter impacts the others, then assigns the patient a stability score from 0-5.
For example, if a patient’s heart rate has elevated, it recognizes which other parameters have changed in a way that would impact that heart rate. Then it highlights those changing parameters with specific colors and calculates a score — where 0 indicates the patient is completely stable, and 5 indicates vitals are changing frequently, representing significant instability.
The PatientWatch solution does more than track patient vital signs. It supports multiple steps in the nursing surveillance process, from data acquisition to investigation and data synthesis, helping nurses and care teams uncover meaning in the data.
Instead of nurses receiving up to five separate alerts, a single alarm tells them there is an issue, and immediately shows them which parameters have changed to cause the issue.
Each parameter is color-coded, making it easy for nurses to see causes of instability at a glance.
Every time new vital signs are entered into the system, it recalculates scores and reorders the display from lowest to highest patient stability.
The solution has helped Christus Health use a common language for clear communication between care teams. From Rapid Response Team activations to evaluating sepsis risk levels, the medical device software interprets physiologic changes so care teams know when and how to intervene.
Wachtel has seen the benefits firsthand.
“This integrated monitoring is truly putting your patient monitoring to work to interpret the patient changes for you — and give you that alert or that tap on the shoulder that says, ‘Hey, this guy’s sick. You need to check him out.’ And then it gives you the supporting information you need to go check him out. We’ve come a long way.”
“Think about your institution,” advises Wachtel. “What are you using? What is your notification system? What are you expecting your nurses to identify in the course of being bombarded all day long with data and information?”
Wachtel sees better surveillance support and medical device integration as important ways to make data analytics work for healthcare — and, importantly, address the industry’s critical staffing shortages.
“It’s up to us in the IT world, in the leadership world and in these settings to invest in this type of intervention,” she says. “It’s the only way we’re going to get our people back in the workforce and have them feel safe in the environments they’re working in.”
Above all, Wachtel recommends going back to the questions that have driven her research from the start: How come? What if? Why not? Who said?
Asking the right questions can make all the difference.
Using Excel Medical Device Integration, from Hillrom, to predict early warning signs of patient deterioration can save your hospital time and money.
Find out how you can predict the early warning signs patient deterioration with advanced Hillrom solutions.