De-escalating Vital Sign Checks

2019-08-11 17:06:54 | BioPortfolio


The overall goals for this study are: 1) to develop a predictive model to identify patients who are stable enough to forego vital sign checks overnight, 2) incorporate this predictive model into the hospital electronic health record so physicians can view its output and use it to guide their decision-making around ordering reduced vital sign checks for select patients.


Patients in the hospital often report poor sleep. A lack of sleep not only affects a patient's recovery from illness and their overall feeling of wellness, but it is a leading factor in the development of delirium in the hospital. One method for improving sleep in the hospital is to reduce the number of patient care related interruptions that a patient experiences. Vital sign checks at night are one example. In hospitalized patients who are clinically stable, vital sign checks that interrupt sleep are often unnecessary. However, identifying which patients can forego these checks is not a simple task. Currently, the hospital's quality improvement team asks physicians to think about this issue every day and order reduced, or "sleep promotion", vital sign checks on patients they believe could safely tolerate it. The investigators goal is to use a predictive analytics tool to reduce the cognitive burden of this task for busy physicians.

The investigators plan to develop a logistic regression model, trained on data from the electronic health record (EHR), to predict, for a given patient on a given night, whether they could safely tolerate the reduction of overnight vital sign checks. The model will use variables, such as the patient's age, the number of days they have been in the hospital, the vital signs from that day, the lab values from that day, and other clinical variables to make its prediction. The outcome is a binary variable, whether the patient will or will not have abnormal vital signs that night. The training data is retrospective therefore it contains the nighttime vitals that were observed, which the investigators will code as a binary variable and use as the outcome variable for the model to train against.

The investigators will incorporate this algorithm into an EHR alert so physicians can observe its output during their work, and use this information, complemented by their own clinical judgment, to decide about ordering reduced vital sign checks for a given patient.

The investigators will study the effect of this EHR alert on several outcomes: in-hospital delirium (measured by nurse assessment), sleep opportunity (a measurement, based on observational EHR data, of patient care related sleep interruptions), and patient satisfaction (measured by nationally-administered post-hospitalization HCAHPS surveys). Balancing measures, to ensure that reduced vital sign checks do not cause patient harm, will be rapid response calls and code blue calls.

Physician teams will be randomized to either see the EHR alert (intervention arm) or not see the EHR alert.

Study Design




Nighttime Vital Sign EHR Alert, No EHR alert


San Francisco
United States




University of California, San Francisco

Results (where available)

View Results


Published on BioPortfolio: 2019-08-11T17:06:54-0400

Clinical Trials [727 Associated Clinical Trials listed on BioPortfolio]

Effects of a Platelet Transfusion Best Practices Alert

This study is to determine the effectiveness of a computerized clinical decision support tool (Best Practice Alert - BPA) in reducing unnecessary platelet transfusions based on guidelines ...

Using Rapid Cycle Randomized Controlled Trials to Optimize the Influenza Clinical Decision Support Tool

The proposed study aims to examine several iterations of the Influenza Best Practice Alert at NYU Langone Health. The goal is to increase ordering of the influenza vaccine through the aler...

Learning Alerts for Acute Kidney Injury

In this trial, individuals with Acute Kidney Injury will be randomized to usual care or to an electronic AKI alert system. In three phases, the alert system will be trained to identify tho...

Warfarin and Non-Steroidal Anti-Inflammatory Drugs (NSAID) Customized Alert

The hypothesis is that a newly formatted electronic alert that requires the prescriber to pause and enter a specific "reason for override" on this alert, will cause prescribers in the inte...

Safer Use of Antipsychotics in Youth

This study tests the effectiveness of an intervention treatment algorithm vs. usual care control in a practical clinical trial. Control arm providers will receive a standard medication ale...

PubMed Articles [2074 Associated PubMed Articles listed on BioPortfolio]

Rapid Presumptive Identification of Isolates Using the Tetracore RedLine Alert™ Test.

A comprehensive laboratory evaluation of the Tetracore RedLine Alert test, a lateral flow immunoassay (LFA) for the rapid presumptive identification of was conducted at 2 different test sites. The st...

Admission NT-ProBNP in Myocardial Infarction: an Alert Sign?

Oxygen alert wristbands (OxyBand) and controlled oxygen: a pilot study.

Despite the introduction of Oxygen Alert Cards, guidelines and audits, oxygen therapy remains overused in NHS practice, and this may lead to iatrogenic mortality. This pilot study aimed to examine the...

The efficacy of a computer alert programme for increasing HBV screening rates before starting immunosuppressive therapy.

Hepatitis B Virus (HBV) screening before starting immunosuppressive treatment is of vital importance in order to prevent HBV reactivation and its associated clinical consequences. Despite all recommen...

Alert-based computerized decision support for high-risk hospitalized patients with atrial fibrillation not prescribed anticoagulation: a randomized, controlled trial (AF-ALERT).

Despite widely available risk stratification tools, safe and effective anticoagulant options, and guideline recommendations, anticoagulation for stroke prevention in atrial fibrillation (AF) is underp...

Medical and Biotech [MESH] Definitions

Test results which deviate substantially from normal ranges of REFERENCE VALUES or other qualitative results. They trigger CLINICAL LABORATORY SERVICES to place a special alert to ensure PATIENT SAFETY.

Mental fatigue experienced by health care providers who encounter numerous alerts and reminders from the use of CLINICAL DECISION SUPPORT SYSTEMS. As the numbers of alerts and reminders designed to provide meaningful assistance to the patient care process increases, many health personnel may ignore them.

A form of DELIRIUM which occurs after GENERAL ANESTHESIA.

Cognitive disorders including delirium, dementia, and other cognitive disorders. These may be the result of substance use, trauma, or other causes.

An acute organic mental disorder induced by cessation or reduction in chronic alcohol consumption. Clinical characteristics include CONFUSION; DELUSIONS; vivid HALLUCINATIONS; TREMOR; agitation; insomnia; and signs of autonomic hyperactivity (e.g., elevated blood pressure and heart rate, dilated pupils, and diaphoresis). This condition may occasionally be fatal. It was formerly called delirium tremens. (From Adams et al., Principles of Neurology, 6th ed, p1175)

More From BioPortfolio on "De-escalating Vital Sign Checks"

Quick Search

Relevant Topic

Sleep Disorders
Sleep disorders disrupt sleep during the night, or cause sleepiness during the day, caused by physiological or psychological factors. The common ones include snoring and sleep apnea, insomnia, parasomnias, sleep paralysis, restless legs syndrome, circa...

Searches Linking to this Trial