Users' experiences of an emergency department patient admission predictive tool: A qualitative evaluation

No Thumbnail Available
File version
Author(s)
Jessup, Melanie
Crilly, Julia
Boyle, Justin
Wallis, Marianne
Lind, James
Green, David
Fitzgerald, Gerard
Griffith University Author(s)
Primary Supervisor
Other Supervisors
Editor(s)
Date
2016
Size
File type(s)
Location
License
Abstract

Emergency department overcrowding is an increasing issue impacting patients, staff and quality of care, resulting in poor patient and system outcomes. In order to facilitate better management of emergency department resources, a patient admission predictive tool was developed and implemented. Evaluation of the tool's accuracy and efficacy was complemented with a qualitative component that explicated the experiences of users and its impact upon their management strategies, and is the focus of this article. Semi-structured interviews were conducted with 15 pertinent users, including bed managers, after-hours managers, specialty department heads, nurse unit managers and hospital executives. Analysis realised dynamics of accuracy, facilitating communication and enabling group decision-making. Users generally welcomed the enhanced potential to predict and plan following the incorporation of the patient admission predictive tool into their daily and weekly decision-making processes. They offered astute feedback with regard to their responses when faced with issues of capacity and communication. Participants reported an growing confidence in making informed decisions in a cultural context that is continually moving from reactive to proactive. This information will inform further patient admission predictive tool development specifically and implementation processes generally.

Journal Title

Health Informatics Journal

Conference Title
Book Title
Edition
Volume

22

Issue

3

Thesis Type
Degree Program
School
Publisher link
Patent number
Funder(s)
Grant identifier(s)
Rights Statement
Rights Statement
Item Access Status
Note
Access the data
Related item(s)
Subject

Health informatics and information systems

Health services and systems

Applied computing

Persistent link to this record
Citation
Collections