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When Data is Siloed, Care is Compromised.

Patient data is one of the most valuable assets in health care, but it is an asset not always available to clinicians.  Bedside devices offer just a snapshot of data and the effort it takes to monitor and analyze data from a series of standalone devices leads to desensitization, alarm fatigue and information gaps. Gaps in data can lead to gaps in care and result in a reactive approach based on trial and error. Tools developed using AI have given us the ability to make highly-informed clinical decisions, but they’re only as good as the inputs they receive.

Health systems are looking to improve quality and lower costs through more precise and proactive care. These models rely on a steady stream of high-fidelity data, integrated and disseminated in a way that enables critical insights.

Untapped Data
and Insights
99
%
of medical device data generated is not recorded and charted in the EMR 1
Errors in Manually
Collected Vital Signs
30
%
of manually collected vital sign records contain an error when they were transmitted to the EMR 2
Alarms Resulting
in No Action
72
%
of alarms result in no action being taken 3

Data can be a distraction rather than a guiding tool.

  • Documentation takes up to 35% of a nurse’s time 4
  • Manual documentation isn’t just time-consuming; it’s also error prone 5,6
  • Clinicians don’t have access and visibility to critical data, with only < 0.1% captured and charted in the EMR 7
  • Inconsistent and inaccurate data can impact coordination and handoffs and lead to gaps in care

Visibility of data empowers clinicians and improves care.

  • A secure infrastructure that connects data across care settings, with one of the world’s largest integrated ecosystem of medical devices and applications
  • Aggregates, standardizes and contextualizes data and makes it accessible at all points of care, giving clinicians ready access to the information they need
  • Intelligent connectivity management systems can also capture data at the bedside, reducing documentation time from hours to minutes while reducing the transcription error rate to zero 8
  • High-quality streaming data feeds algorithms that deliver insights to clinicians caring for the highest acuity patients
neuron-N3-7S

Vitals Stream

Designed for ORs and high-acuity care areas, Vitals Stream provides continuous near-real time vitals data and connectivity status at a glance. Users can easily see which devices are connected and associate all captured data with the right patient ID.

MEHR ERFAHREN
clinicians neuron N3 with-CPC

Chart Xpress

Chart Xpress enables accurate and rapid delivery of validated information into the EMR. Upgrading from Chart Xpress to Vitals Plus extends your connectivity investment and helps maintain consistency in workflow and documentation.

MEHR ERFAHREN
clinicians-neuron-N3s-x4

Neuron

A mobile clinical computer features built-in connectivity ports and the ability to manage data and connectivity status from multiple devices on a single display.

MEHR ERFAHREN
clinicians-flat-axon-v202402

Axon

A single-, four- or eight-port serial to network bridge providing robust connectivity to the EMR in crowded care areas like the ICU.

MEHR ERFAHREN
1
ICU Patient when connected to 10 devices. Data on file. Capsule 2017.
2
Wood J, Finkelstein J. Comparison of automated and manual vital sign collection at hospital wards. Informatics, Management and Technology in Healthcare. Doi: 10.3233/978-1-61499-276-9-48, 2013.
3
Chambrin MC, Ravaux P, Calvelo-Aros D. Multicentric study of monitoring alarms in the adult intensive care unit (ICU): a descriptive analysis. Intensive Care Med 1999;25(12):1360–6.
4
Hendrich A, Chow MP, Skierczynski BA, Lu Z. A 36-Hospital Time and Motion Study: How Do Medical-Surgical Nurses Spend Their Time? The Permanente Journal. 2008;12(3):25-34.
5
Bellomo R, Ackerman M, Bailey M, et al. A controlled trial of electronic automated advisory vital signs monitoring in general hospital wards. Crit Care Med 2012 Vol. 40, No. 8.
6
Fieler VK, Jaglowski T, Richards K. Eliminating Errors in Vital Signs Documentation. CIN: Computers, Informatics, Nursing & Vol. 31, No. 9, 422–427. 2013.
7
Data on file. Capsule 2018.
8
Bellomo R, Ackerman M, Bailey M, et al. A controlled trial of electronic automated advisory vital signs monitoring in general hospital wards. Crit Care Med 2012 Vol. 40, No. 8.