Clinical Decision Support At Bedside Aids Patient Monitoring - InformationWeek

InformationWeek is part of the Informa Tech Division of Informa PLC

This site is operated by a business or businesses owned by Informa PLC and all copyright resides with them.Informa PLC's registered office is 5 Howick Place, London SW1P 1WG. Registered in England and Wales. Number 8860726.

IoT
IoT
Healthcare // Clinical Information Systems

Clinical Decision Support At Bedside Aids Patient Monitoring

Combining clinical decision support tools with medical monitoring gear can help nurses quickly recognize early signs of complications and infection in critically ill patients.

As more healthcare providers implement health IT systems, like e-medical records and computerized order entry, clinical decision support tools will increasingly aid doctors and nurses by analyzing patient data for trends and other pertinent information that should be acted upon. But clinical decision support tools are also already helping some clinicians analyze the reams of patient data that gets generated by medical monitoring gear.

When critically ill patients are hooked up to medical equipment to monitor breathing, blood pressure, heart rate and other functions, the gear typically displays "a lot of raw data" often as numbers or waves, said Karen Giuliano, a registered nurse and principal scientist of clinical outcomes research at Philips Healthcare, a maker of medical monitoring equipment.

However, the addition of clinical decision support tools can aid clinicians by allowing key data to be analyzed and displayed in a manner that helps nurses and doctors watch for very subtle, early signs that patients are developing complications or other medical issues.

At Long Beach Memorial Medical Center in Long Beach, Calif. clinicians recently participated in a study to evaluate how clinical decision support tools can be used to help watch for trends that indicate early signs of sepsis in critically ill patients in simulated settings.

"Sepsis is sneaky, often you don't realize a patient is septic till it's bad," says Sue Crockett, a registered nurse and director of clinical workforce development at Long Beach Memorial Medical Center and its Miller Children's Hospital.

In the study, 75 critical care nurses were randomly assigned to working with either standard or enhanced bedside monitoring gear to recognize simulated cases of sepsis, an infection that can spread throughout a person's body, and a leading cause of death in intensive care patients.

The study aimed at evaluating how different screen views of data can affect how clinicians recognize the signs and symptoms of sepsis, said Crockett.

If caught early enough, the administration of antibiotics can help control the potentially deadly effects of the sepsis, which causes body-wide inflammation and other serious problems.

Also, even when a patient doesn't die from sepsis, full recovery is often difficult. "Any opportunity to intervene early can help and save lives," said Crockett.

The enhanced monitoring was loaded with Philips clinical decision support tools. The software allowed the devices to be programmed to provide clinicians with visual cues in watching for a combination of patient parameters that are early signs of sepsis, including falling blood pressure and creeping up rates for heart beats and temperature.

Long Beach Memorial found that compared to nurses using standard monitoring displays, the clinical decision support tools helped reduce the time it took for clinicians to recognize when patients were developing early signs of sepsis, allowing the treatment to be initiated sooner.

Currently, Long Beach is training its clinical staff on how to use Philips clinical decision support tools for recognizing sepsis in critical care patients, said Crockett. Long Beach has several hundred critical care beds in its pediatric, women's and adult care facilities and expects to have the tools in "wide use in the coming months," she said.

The monitoring data can also be fed into patients' Epic e-medical records, which Long Beach rolled out about two years ago, said Crockett.

Philips clinical decision support software can be programmed to help clinical staff monitor and identify other occurrences in patients, said Guiliano. That includes systems that can watch for trouble with patients being cared on other medical floors, such as surgical wings.

"We're making more enhancements so that the information comes only when the clinician wants it," said Patricia McGaffigan, who leads Philips Healthcare's clinical decision support efforts.

Having "too many alerts" can contribute to so-called alert fatigue when clinicians begin to override or ignore too-frequent or unnecessary warnings.

"We're working to broaden the intelligence of alarms," she said.

Read our new report on how IP telephony is being used in healthcare settings. Download the report now (registration required).

We welcome your comments on this topic on our social media channels, or [contact us directly] with questions about the site.
Comment  | 
Print  | 
More Insights
Slideshows
IT Careers: Top 10 US Cities for Tech Jobs
Cynthia Harvey, Freelance Journalist, InformationWeek,  1/14/2020
Commentary
Predictions for Cloud Computing in 2020
James Kobielus, Research Director, Futurum,  1/9/2020
News
What's Next: AI and Data Trends for 2020 and Beyond
Jessica Davis, Senior Editor, Enterprise Apps,  12/30/2019
White Papers
Register for InformationWeek Newsletters
Video
Current Issue
The Cloud Gets Ready for the 20's
This IT Trend Report explores how cloud computing is being shaped for the next phase in its maturation. It will help enterprise IT decision makers and business leaders understand some of the key trends reflected emerging cloud concepts and technologies, and in enterprise cloud usage patterns. Get it today!
Slideshows
Flash Poll