RTLS for Healthcare Process Validation

Not Applicable

Completed

Conditions: Nursing
Workflow

Interventions: Device: RTLS current tag
Device: RTLS tag revised

Registration Number: NCT04116957

Lead Sponsor: University of Missouri-Columbia

Brief 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.

Detailed 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.

Recruitment & Eligibility

Status: COMPLETED

Sex: All

Target Recruitment: 19

Inclusion Criteria

English speaking, RN or LPN licensure

Exclusion Criteria

Nurses helping to provide care but not having a patient assignment and nurse managers

Study & Design

Study Type: INTERVENTIONAL

Study Design: PARALLEL

Arm && Interventions

Group	Intervention	Description
Tracking System	RTLS current tag	Nurse location data collection using the original NFER system at an ICU at the University Hospital, University of Missouri Health Care in Columbia, Missouri.
New Tracking System	RTLS tag revised	Nurse location data collection using the upgraded NFER system at an ICU at the University Hospital, University of Missouri Health Care in Columbia, Missouri.

Primary Outcome Measures

Name	Time	Method
Patient Severity of Illness - Sequential Organ Failure Assessment (SOFA) Score	Assessed at ICU admission	Sequential Organ Failure Assessment (SOFA) score is a measuring system that determines the extent of a person's organ function or failure rate. This scoring system consists of six organ systems (respiratory, coagulation, liver, cardiovascular, renal, and neurologic). It assesses critically ill patients in an intensive care unit. The SOFA score has shown decent predictive validity for inpatient mortality. Each system is assigned a score from 0 to 4 based on the degree of dysfunction, with higher scores indicating more severe dysfunction. The sum of the scores for each organ system is reported. The total score can range from 0 to 24. A higher total score indicates greater organ dysfunction and a higher risk of mortality. The anticipated outcome is that there is no significant difference in the patient severity of illness between the first and second data collection.
In-Room Activity Time Difference Between RTLS System and Manual Observation	Up to 12 hours	To compare the time difference between the RTLS system and manual observation data, all In-Room activity times collected from the RTLS system are statistically compared to the In-Room activity time collected from the time study data done by observers. A paired t-test is used to determine whether the means of the two groups are statistically different from each other. 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. In other words, the time difference between the RTLS system and manual observation should be less than 15 minutes during the day shift (up to 12 hours).
Out-of-Room Activity Time Difference Between RTLS System and Manual Observation	Up to 12 hours	To compare the time difference between the RTLS system and manual observation data, all Out-of-Room activity times collected from the RTLS system are statistically compared to the Out-of-Room activity times collected from the time study data done by observers. A paired t-test is used to determine whether the means of the two groups are statistically different from each other. 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. In other words, the time difference between the RTLS system and manual observation should be less than 15 minutes for the day shift (up to 12 hours)