RTLS for Healthcare Process Validation

Study Overview
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Brief Summary
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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
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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.

Official Title
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A Next Generation, Low Cost Tracking System for Healthcare Process Validation

Conditions
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Workflow, Nursing

Intervention / Treatment
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* Device: RTLS current tag
* Device: RTLS tag revised


Participation Criteria
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Eligibility Criteria
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Inclusion Criteria: English speaking, RN or LPN licensure Exclusion Criteria: Nurses helping to provide care but not having a patient assignment and nurse managers

Ages Eligible for Study
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Minimum Age: 18 Years

Sexes Eligible for Study
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All

Accepts Healthy Volunteers
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Accepts Healthy Volunteers

Study Plan
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How is the study designed?
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Design Details

Primary Purpose: Device Feasibility
Intervention Model: Single Group Assignment
Masking: Single


Arms and Interventions

| Participant Group/Arm | Intervention/Treatment |
| --- | --- |
| Other: Time 1<br>First two months of data collection at an ICU at the University Hospital, University of Missouri Health Care in Columbia, Missouri. | Device: RTLS current tag<br>* Validate location system performance against manual observation of nursing activity<br>|
| Other: Time 2<br>Second two months of data collection at an ICU at the University Hospital, University of Missouri Health Care in Columbia, Missouri. | Device: RTLS tag revised<br>* Test a next-generation RTLS tag for healthcare process validation<br>|

What is the study measuring?
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Primary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Nurse location accuracy | 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. | up to 4 months | 
| Identify Correlation between Nurse characteristic and Patient Severity of illness in care delivery workflow | The anticipated outcome is a real-time statistical quality control chart capable of monitoring nursing processes and detecting correlation between nurse characteristic and patient severity of illness with user-configurable statistical power. | up to 4 months |