Clinical Trial Details
— Status: Completed
Administrative data
| NCT number |
NCT04116957 |
| Other study ID # |
2016906 |
| Secondary ID |
|
| Status |
Completed |
| Phase |
N/A
|
| First received |
|
| Last updated |
|
| Start date |
February 17, 2020 |
| Est. completion date |
May 31, 2021 |
Study information
| Verified date |
June 2021 |
| Source |
University of Missouri-Columbia |
| Contact |
n/a |
| Is FDA regulated |
No |
| Health authority |
|
| Study type |
Interventional
|
Clinical Trial Summary
The purpose of the project is to develop a new way to understand patient care data analytics
by using a real-time location system (RTLS). The investigators will deploy the RTLS-based
nursing activity analysis system at an ICU at the University Hospital, University of Missouri
Health Care in Columbia, Missouri. The investigators will validate location system
performance against manual observation of nursing activity. The investigators will correlate
nursing activity metrics against patient outcomes as measured by SOFA score.
Description:
Real-Time Location Systems (RTLS) identify and locate tagged assets, staff, or patients as
they move through a hospital. RTLS can address a variety of other practical problems in
healthcare such as inventory management and patient tracking and monitoring. Most RTLS employ
some flavor of Radio Frequency (RF) angle-of-arrival, time-of-flight,
time-difference-of-arrival, or Received Signal Strength Indicators (RSSI). However, these
techniques have several significant disadvantages. Among these are confusion from multipath
and environmental clutter, line-of-sight operation, need for synchronization, range
restrictions, and expense. Furthermore the human body, composed mainly of salt water, occults
high frequency signals making fading a serious problem. Wi-Fi tracking, in particular is,
limited to an accuracy of 10-20ft and cannot provide the precision data required for
high-fidelity applications in healthcare such as workflow management.
In the current study, the investigators will validate location system performance against
manual observation of nursing activity. The investigators will correlate nursing activity
metrics against patient outcomes as measured by SOFA score. The anticipated outcome is
actionable, location-based data to describe, analyze, or validate healthcare processes with a
maximum error of 5% relative to manual observation. Also, the investigators will identify
specific location-based metrics useful in monitoring nursing activity. The investigators will
deploy and test the system in a medical ICU at the University Hospital ICU. The anticipated
outcome is a real-time statistical quality control chart capable of monitoring nursing
processes and detecting anomalies with user-configurable statistical power.
Prospective participants will receive an individual email from co-investigator explaining
study including the need for participants willing to wear location tag for the duration of
their shift. The Informed Consent form and Demographic Question will be attached to this
email. Those willing to participate will also be asked to send the completed Demographics
Questionnaire attached to their email response. Receipt of the completed Demographics
Questionnaire will signify their consent to participate.
The co-investigator will explain in the individual email that this study is to solely gain
knowledge regarding their workflow as they deliver patient care and is not an evaluation of
their performance or clinical judgment. Their participation in the study will not be revealed
to their manager unless the participant wishes. The co-investigator will explain that
participation is voluntary, they can withdraw at any time without risk to their employment
and all aspects of their participation will be confidential.
A Waiver of documentation of consent form will be attached to the individual's email as well
as the Demographic Questionnaire. The Waiver of Documentation of Consent form will provide an
overview of the study. They will be informed both in the form and in the text of the email
that the return of the completed Demographic Questionnaire signifies their consent to
participate in the study and that participation is voluntary and confidential. They will be
provided with the co-investigator's contact information should they have questions or
concerns. In addition, information from the EMRs of patients assigned to the nurse
participants will be abstracted retrospectively under the Waiver of Consent after the
patients have been transferred from the ICU. Patient factors will be used to help interpret
the nurse participant data. However, concurrent patient data abstraction is not necessary for
data analysis in this research project as there will be no intervention introduced that would
impact the patient data. Further, patients in this ICU are usually unable to provide informed
consent due to the presence of mechanical ventilation and continuous sedation.
Recruited nurses will receive one RTLS location tag prior to their shift from trained
undergraduate industrial and manufacturing systems engineering (IMSE) students who will keep
a log of the nurses' name and tag identification. The nurses will carry the tags for the
duration of their shift and then return the tags to the students. While they carry the RTLS
tags, IMSE students will stand at the corner of the nurse's station in each pod to record the
nurses' activities and the time spent in these activities using a data collection form
previously developed during earlier pilot work when IMSE students collected time-motion data
regarding ICU nursing care activities. If any special events occur during the observation
period, they will record a description of these events, which include but not be limited to
unscheduled medical activities or admission of a new patient to the ICU from the Emergency
Department (ED). The RTLS location tag distribution and nurse observation will occur four to
five days per week until a total of 80 days of location and observation data is obtained. For
each patient that is assigned to an observed ICU nurse, data will be extracted
retrospectively from their EMR. The abstracted data will include: age, gender, hospital
admitting diagnosis, medical ICU admitting diagnosis, past medical diagnoses, laboratory
values occurring during, or 24 hours prior to observation time, neurological status, mean
arterial pressures during observation time, intravenous medications administered during
observation time, any diagnostic studies performed outside of the ICU during the observation
time, and any in-room procedures performed during the observation time.
There is minimal risk to the participants in this study. There are no potential risks or
discomfort for the participant as there will be no change in their work process. Methods to
avoid inadvertent coercion in the recruitment process will be deployed.
Analyzing the ICU nurse's workflow can furnish an understanding of the causes of delayed and
missed care delivery. The findings from this research will highlight opportunities to improve
the workflow management design. Such information can guide future workflow management to
reduce the ICU nurse's workload and the risk of delayed or missed care in the ICU resulting
in improved patient outcomes.
