Javascript must be enabled to continue!
Errors, Omissions, and Outliers in Hourly Vital Signs Measurements in Intensive Care
View through CrossRef
Objective:
To empirically examine the prevalence of errors, omissions, and outliers in hourly vital signs recorded in the ICU.
Design:
Retrospective analysis of vital signs measurements from a large-scale clinical data warehouse (Multiparameter Intelligent Monitoring in Intensive Care III).
Setting:
Data were collected from the medical, surgical, cardiac, and cardiac surgery ICUs of a tertiary medical center in the United States.
Patients:
We analyzed data from approximately 48,000 ICU stays including approximately 28 million vital signs measurements.
Interventions:
None.
Measurements and Main Results:
We used the vital sign day as our unit of measurement, defined as all the recordings from a single patient for a specific vital sign over a single 24-hour period. Approximately 30–40% of vital sign days included at least one gap of greater than 70 minutes between measurements. Between 3% and 10% of blood pressure measurements included logical inconsistencies. With the exception of pulse oximetry vital sign days, the readings in most vital sign days were normally distributed. We found that 15–38% of vital sign days contained at least one statistical outlier, of which 6–19% occurred simultaneously with outliers in other vital signs.
Conclusions:
We found a significant number of missing, erroneous, and outlying vital signs measurements in a large ICU database. Our results provide empirical evidence of the nonrepresentativeness of hourly vital signs. Additional studies should focus on determining optimal sampling frequencies for recording vital signs in the ICU.
Ovid Technologies (Wolters Kluwer Health)
Title: Errors, Omissions, and Outliers in Hourly Vital Signs Measurements in Intensive Care
Description:
Objective:
To empirically examine the prevalence of errors, omissions, and outliers in hourly vital signs recorded in the ICU.
Design:
Retrospective analysis of vital signs measurements from a large-scale clinical data warehouse (Multiparameter Intelligent Monitoring in Intensive Care III).
Setting:
Data were collected from the medical, surgical, cardiac, and cardiac surgery ICUs of a tertiary medical center in the United States.
Patients:
We analyzed data from approximately 48,000 ICU stays including approximately 28 million vital signs measurements.
Interventions:
None.
Measurements and Main Results:
We used the vital sign day as our unit of measurement, defined as all the recordings from a single patient for a specific vital sign over a single 24-hour period.
Approximately 30–40% of vital sign days included at least one gap of greater than 70 minutes between measurements.
Between 3% and 10% of blood pressure measurements included logical inconsistencies.
With the exception of pulse oximetry vital sign days, the readings in most vital sign days were normally distributed.
We found that 15–38% of vital sign days contained at least one statistical outlier, of which 6–19% occurred simultaneously with outliers in other vital signs.
Conclusions:
We found a significant number of missing, erroneous, and outlying vital signs measurements in a large ICU database.
Our results provide empirical evidence of the nonrepresentativeness of hourly vital signs.
Additional studies should focus on determining optimal sampling frequencies for recording vital signs in the ICU.
Related Results
NICU Medication Errors: Describing the Cause and Nature of Medication Errors in a NICU in Qatar
NICU Medication Errors: Describing the Cause and Nature of Medication Errors in a NICU in Qatar
IntroductionA medication error can be defined as “any error occurring in the medication use process” and focuses on problems with the delivery of medication to a patient [1]. Medic...
Temporal and spatial distributions of hourly rain intensity under the warm background in Xinjiang
Temporal and spatial distributions of hourly rain intensity under the warm background in Xinjiang
<p>It is well known that climate changes sometimes may cause natural disasters&#65292;especially the disastrous weather days&#65292;as downpour&am...
Role of misoprostol 4 hourly versus 6 hourly in medical termination of pregnancy in 2nd trimester.
Role of misoprostol 4 hourly versus 6 hourly in medical termination of pregnancy in 2nd trimester.
Objective: To determine efficacy of misoprostol given in 4 hourly versus 6 hourly intervals in second trimester for termination of pregnancy. Study Design: Cross sectional study. S...
HRGEN: A stochastic generator of hourly rainfall
HRGEN: A stochastic generator of hourly rainfall
Rainfall data are needed as input to drive hydrological and soil erosion models. Daily rainfall data are commonly used and widely accessible, whether sourced from meteorological ob...
An Improved Innovation Robust Outliers Detection Method for Airborne Array Position and Orientation Measurement System
An Improved Innovation Robust Outliers Detection Method for Airborne Array Position and Orientation Measurement System
The airborne array position and orientation measurement system (array POS) is a key device for high-resolution multi-dimensional real-time imaging motion compensation of military r...
[RETRACTED] Keanu Reeves CBD Gummies v1
[RETRACTED] Keanu Reeves CBD Gummies v1
[RETRACTED]Keanu Reeves CBD Gummies ==❱❱ Huge Discounts:[HURRY UP ] Absolute Keanu Reeves CBD Gummies (Available)Order Online Only!! ❰❰= https://www.facebook.com/Keanu-Reeves-CBD-G...
Research Note: A Study of Outliers of International Tourism Statistics
Research Note: A Study of Outliers of International Tourism Statistics
As international tourism is an industry that is easily impacted by external shocks, there is always structural mutation of the time series related with it, which causes the existen...
Bagan Kendali Robust Multivariat untuk Pengamatan Individual
Bagan Kendali Robust Multivariat untuk Pengamatan Individual
AbstractThe most widely used of control chart in multivariate control processing is control chart T2 Hotelling. There are 2 kinds of control chart T2 Hotelling, namely T2 Hotelling...

