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| ID | Type | Description | Link |
|---|---|---|---|
| 5R18HS029283-03 | U.S. AHRQ Grant/Contract | View source |
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| Name | Class |
|---|---|
| University of Michigan | OTHER |
| Western Michigan University | OTHER |
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The primary objective of this research study is to use simulated pediatric emergencies to test the effectiveness of a drug dosing safety system for EMS providers by comparing usual care to use of an augmented reality device.
The objective of this project is to develop a safe and effective dynamic cognitive aid application for use through a head-mounted display (HMD), to reduce error rates associated with pediatric medication administration (PMA) by emergency medical services (EMS). This objective will be achieved by examining characteristics associated with PMA, using a design thinking process to develop a prototype application, examining usability of the prototype, and testing the safety and efficacy in a randomized controlled trial.
Errors associated with PMA in EMS are alarmingly high. Numerous studies have shown that there is a 31% error rate across all drugs administered to children by EMS. Medications such as midazolam and fentanyl have even higher rates at 61% and 65%, respectfully, with many being 10-fold errors. Sadly, previous strategies have had little impact on reducing error rates below 31%. System changes have failed due to inconsistencies in EMS systems, and challenges associated with medication shortages. Previously developed cognitive aids have fallen short often due to the fact they generally act as simple reference tools and do not address all causes of error associated with PMA. As a result, we are proposing the most comprehensive design process ever taken to combat this issue, utilizing advanced technology, to implement a dynamic cognitive aid to help providers improve dosing accuracy during PMA.
We hypothesize that PMA errors in EMS will be significantly reduced by this application due to the comprehensive and rigorous design thinking process we will utilize followed by a randomized controlled trial to test safety and efficacy. Our interdisciplinary team will combine the fields of pediatric emergency medicine, EMS, engineering, computer science and user interface/user experience to address this issue with the support and effort of two medical schools in Michigan. In SA1 we will develop a prototype application. This will begin with identifying user and contextual information associated with PMA, and examine failure modes, root causes, and a task analysis of the procedure. We will then proceed into a comprehensive design thinking process to develop the application. During this process we will also create a desktop program that will allow EMS agency administrators to add new medications to the HMD application. In SA2, we will examine usability of the HMD application and associated desktop program in a simulation-based environment with a sample of end users, examining task duration, cognitive load and error rates and make any necessary refinements. In SA3, we will test the HMD application in a simulation-based randomized controlled trial to examine its safety and efficacy for use in EMS. This will result in a safe and effective tool to mitigate this alarming issue in the vulnerable EMS pediatric population.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Augmented reality | Experimental | EMS crews who will utilize the augmented reality application |
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| Usual care | No Intervention | EMS crews who will provide usal care using their existing pediatric dosing references |
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Augmented reality software for pediatric drug dosing | Other | Augmented reality software, developed by the study team, will be utilized by the experimental arm. This software is specifically designed to decrease errors in the prehospital pediatric medication administration process. |
| Measure | Description | Time Frame |
|---|---|---|
| Drug dosing accuracy | Proportion of medication administration tasks performed accurately, with a target difference of >20% between control and experimental groups, assessed via structured observational methods over a [2] hour timeframe. | 2 hours |
| Measure | Description | Time Frame |
|---|---|---|
| Tenfold dosing errors | Number of medication doses administered at ten times, one-tenth, or greater deviation from the correct dose, assessed over a 2-hour observation window. | 2 hours |
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Inclusion Criteria:
Exclusion Criteria:
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| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Western Michigan University School of Medicine | Kalamazoo | Michigan | 49008 | United States |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| Background | R: The r project for statistical computing. Accessed May 20, 2022. https://www.r-project.org/ | ||
| Background | Python eda documentation. Accessed May 20, 2022. https://pyeda.readthedocs.io/en/latest/index.html | ||
| Background | Ledalab software. Accessed May 20, 2022. http://www.ledalab.de/software.htm | ||
| 32867055 | Background | Romine WL, Schroeder NL, Graft J, Yang F, Sadeghi R, Zabihimayvan M, Kadariya D, Banerjee T. Using Machine Learning to Train a Wearable Device for Measuring Students' Cognitive Load during Problem-Solving Activities Based on Electrodermal Activity, Body Temperature, and Heart Rate: Development of a Cognitive Load Tracker for Both Personal and Classroom Use. Sensors (Basel). 2020 Aug 27;20(17):4833. doi: 10.3390/s20174833. | |
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| Type | Includes Protocol | Includes SAP | Includes ICF | Document Label | Document Date | Document Uploaded Date | Document File Name |
|---|---|---|---|---|---|---|---|
| Prot_SAP_ICF | Yes | Yes | Yes | Study Protocol, Statistical Analysis Plan, and Informed Consent Form | Dec 16, 2025 |
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| Mar 16, 2026 |
| Prot_SAP_ICF_000.pdf |