- ICH GCP
- Amerikanska kliniska prövningsregistret
- Klinisk prövning NCT04046458
De-escalating Vital Sign Checks
Using Predictive Analytics to Reduce Vital Sign Checks in Stable Hospitalized Patients
Studieöversikt
Status
Betingelser
Intervention / Behandling
Detaljerad beskrivning
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.
Studietyp
Inskrivning (Faktisk)
Fas
- Inte tillämpbar
Kontakter och platser
Studieorter
-
-
California
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San Francisco, California, Förenta staterna, 94143
- UCSF
-
-
Deltagandekriterier
Urvalskriterier
Åldrar som är berättigade till studier
- Barn
- Vuxen
- Äldre vuxen
Tar emot friska volontärer
Kön som är behöriga för studier
Beskrivning
Inclusion Criteria:
- All physician teams that operate under the UCSF Division of Hospital Medicine
Exclusion Criteria:
- N/A
Studieplan
Hur är studien utformad?
Designdetaljer
- Primärt syfte: Förebyggande
- Tilldelning: Randomiserad
- Interventionsmodell: Parallellt uppdrag
- Maskning: Ingen (Open Label)
Vapen och interventioner
Deltagargrupp / Arm |
Intervention / Behandling |
---|---|
Experimentell: EHR Alert
Physician teams will observe the EHR alert as they perform their clinical duties in the EHR.
|
A pop-up window in the EHR will notify a physician that their patient has been judged by a predictive algorithm to be safe for reduced overnight vital sign checks.
|
Placebo-jämförare: No Alert
Physician teams will perform their clinical duties in the EHR as usual, with no visible alert.
|
No change to EHR function; no alert visible to providers
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Vad mäter studien?
Primära resultatmått
Resultatmått |
Åtgärdsbeskrivning |
Tidsram |
---|---|---|
delirium
Tidsram: average will be measured at study completion (6 months from study start date - Sep 11, 2019)
|
Nursing Delirium Screening Scale (Nu-DESC score) - assessed by the nurse, can range from zero to ten, a score > 2 has good accuracy for delirium
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average will be measured at study completion (6 months from study start date - Sep 11, 2019)
|
Sekundära resultatmått
Resultatmått |
Åtgärdsbeskrivning |
Tidsram |
---|---|---|
sleep opportunity
Tidsram: average will be calculated at study completion (6 months from study start date - Sep 11, 2019)
|
a *novel* measurement based on observational EHR data - for every night in the hospital, the investigators can extract from the EHR all event timestamps that could have interrupted the patient's sleep (measured between 11 pm and 6 am).
These are blood pressure recordings, fingerstick glucose checks, blood draws for labs, and not-as-needed medication administrations.
The maximum time period between such events is considered the patient's sleep opportunity for that night (measured in hours).
A higher sleep-opportunity on a given night is better.
The investigators can calculate an average sleep-opportunity for a hospital encounter and then an average sleep-opportunity for all encounters in a clinical trial arm.
|
average will be calculated at study completion (6 months from study start date - Sep 11, 2019)
|
patient satisfaction
Tidsram: average score will be measured at study completion (6 months from study start date - Sep 11, 2019)
|
results from Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) surveys administered to patients after discharge from the hospital (scale is a categorical response: never, sometimes, usually, or always)
|
average score will be measured at study completion (6 months from study start date - Sep 11, 2019)
|
Andra resultatmått
Resultatmått |
Åtgärdsbeskrivning |
Tidsram |
---|---|---|
number of code blue events
Tidsram: average number will be calculated at study completion (6 months from study start date - Sep 11, 2019)
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when a patient has a code blue (respiratory or cardiac arrest) called on them in the hospital, the resuscitation team that responds then writes a note documenting the event; the investigators can count these notes as a proxy for counting code blue events themselves (lower number is better)
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average number will be calculated at study completion (6 months from study start date - Sep 11, 2019)
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number of rapid response calls
Tidsram: average number will be calculated at study completion (6 months from study start date - Sep 11, 2019)
|
when a patient has a rapid response (significant change in vital signs or alertness) called on them in the hospital, the team that responds writes a note documenting the event and the investigators can count these notes as a proxy for counting rapid response events themselves (lower number is better)
|
average number will be calculated at study completion (6 months from study start date - Sep 11, 2019)
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Samarbetspartners och utredare
Utredare
- Studierektor: Mark Pletcher, MD, Director of the UCSF Informatics and Research Innovation Program
Publikationer och användbara länkar
Studieavstämningsdatum
Studera stora datum
Studiestart (Faktisk)
Primärt slutförande (Faktisk)
Avslutad studie (Faktisk)
Studieregistreringsdatum
Först inskickad
Först inskickad som uppfyllde QC-kriterierna
Första postat (Faktisk)
Uppdateringar av studier
Senaste uppdatering publicerad (Faktisk)
Senaste inskickade uppdateringen som uppfyllde QC-kriterierna
Senast verifierad
Mer information
Termer relaterade till denna studie
Ytterligare relevanta MeSH-villkor
Andra studie-ID-nummer
- nightvitals
Plan för individuella deltagardata (IPD)
Planerar du att dela individuella deltagardata (IPD)?
IPD-planbeskrivning
Läkemedels- och apparatinformation, studiedokument
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Oslo University HospitalUniversity of Melbourne; Norwegian Academy of MusicAvslutadDelirium i ålderdom | Delirium av blandat ursprung | Delirium överlagrat på demens | Delirium FörvirringstillståndNorge
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Universidad de SantanderOkändDelirium av blandat ursprung | Hypoaktivt delirium | Hyperaktivt deliriumColombia
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Imperial College Healthcare NHS TrustRekryteringHjärtkirurgi | Intensivvårdsavdelning Delirium | Postoperativt deliriumStorbritannien
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Chinese PLA General HospitalBeijing Tiantan HospitalRekrytering
-
Charite University, Berlin, GermanyBARMERRekryteringDelirium i ålderdomTyskland
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Qin ZhangNational Natural Science Foundation of ChinaRekrytering
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Qin ZhangNational Natural Science Foundation of ChinaRekryteringDelirium, postoperativtKina
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University Hospital, Basel, SwitzerlandInnosuisse - Swiss Innovation AgencyRekryteringPostoperativt delirium (POD)Schweiz
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