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Filtering by: Creator Leecaster, Molly Keyword wireless sensors Resource type Dataset Subject cardiology

Raw Wireless Sensor Data from the University of Utah from the CDC-funded Granular Modeling Project

Description:

The objective of using the wireless sensors was to improve understanding of the heterogeneity of healthcare worker (HCW) contact with patients and the physical environment in patients’ rooms. The framework and design were based on contact networks with a) nodes defined by HCW’s, rooms, and items in the room and b) edges defined by HCW’s in the room, near the bed, and touching items. Nodes had characteristics of HCW role and room number. Edges had characteristics of day, start time, and duration. Thus, patterns and heterogeneity could be understood within contexts of time, space, roles, and patient characteristics. At the University of Utah Hospital Cardiovascular ICU (CVICU), a 20-bed unit, we collected data for 54 days. HCW contact with patients was measured using wireless sensors to capture time spent in patient rooms as well as time spent near the patient bed. HCW contact with the physical environment was measured using wireless sensors on the following items in patient rooms: door, sink, toilet, over-bed table, keyboard, vital signs monitor touchscreen, and cart. HCW’s clipped a sensor to their clothing or lanyard.

Keyword:

wireless sensors and patient contact

Subject:

cardiology

Creator:

Rubin, Michael, Haroldsen, Candace, and Leecaster, Molly

Owner:

Michael Rubin

Based Near Label Tesim:

Salt Lake City, Utah, United States

Language:

English

Date Uploaded:

05/23/2023

Date Modified:

11/28/2023

Date Created:

2018-03-01 to 2018-04-28

License:

CC BY NC - Allows others to use and share your data non-commercially and with attribution.

Resource Type:

Dataset

Identifier:

https://doi.org/10.7278/S50d-acm8-epwg
Cleaned Ping-level Wireless Sensor Data from the University of Utah from the CDC-funded Granular Modeling Project

Description:

The objective of using the wireless sensors was to improve understanding of the heterogeneity of healthcare worker (HCW) contact with patients and the physical environment in patients’ rooms. The framework and design were based on contact networks with a) nodes defined by HCW’s, rooms, and items in the room and b) edges defined by HCW’s in the room, near the bed, and touching items. Nodes had characteristics of HCW role and room number. Edges had characteristics of day, start time, and duration. Thus, patterns and heterogeneity could be understood within contexts of time, space, roles, and patient characteristics. At the University of Utah Hospital Cardiovascular ICU (CVICU), a 20-bed unit, we collected data for 54 days. HCW contact with patients was measured using wireless sensors to capture time spent in patient rooms as well as time spent near the patient bed. HCW contact with the physical environment was measured using wireless sensors on the following items in patient rooms: door, sink, toilet, over-bed table, keyboard, vital signs monitor touchscreen, and cart. HCW’s clipped a sensor to their clothing or lanyard. This dataset contains cleaned sensor pings of RFD reads between healthcare worker worn sensors and environmental sensors placed in facility using methods described in the "Data Cleaning Steps" section.

Keyword:

patient contact and wireless sensors

Subject:

cardiology

Creator:

Rubin, Michael, Haroldsen, Candace, and Leecaster, Molly

Contributor:

Huber, Tavis and Stratford, Kristina

Owner:

Michael Rubin

Based Near Label Tesim:

Salt Lake City, Utah, United States

Language:

English

Date Uploaded:

12/26/2023

Date Modified:

01/04/2024

Date Created:

2018

License:

CC BY NC - Allows others to use and share your data non-commercially and with attribution.

Resource Type:

Dataset

Identifier:

www.doi.org/10.7278/S50d-twbh-955q

Raw Wireless Sensor Data from the University of Utah from the CDC-funded Granular Modeling Project

Cleaned Ping-level Wireless Sensor Data from the University of Utah from the CDC-funded Granular Modeling Project

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