Dissertation
Designing computerized support for identifying and treating patients with life-threatening injuries during medical emergencies
Doctor of Philosophy (Ph.D.), Drexel University
Sep 2024
DOI:
https://doi.org/10.17918/00010625
Abstract
During medical emergencies, clinical teams evaluate and treat patients with life-threatening injuries. Clinical decision-support systems (CDSSs) can assist clinicians in evaluating and treating patients, helping to avoid misdiagnoses, delays, and errors. However, human-computer interaction issues, such as data entry barriers and poor workflow integration, often limit adoption of these systems. While advances in artificial intelligence (AI) can improve the accuracy of CDSSs, integrating AI within these systems can lead to additional HCI challenges. This dissertation focuses on developing computerized support for identifying and treating patients with severe blood loss or traumatic brain injury, two of the most frequent causes of preventable deaths during trauma resuscitation. The research has two aims: (1) design features to capture the data needed for identifying patients with severe blood loss or traumatic brain injury and (2) present decision support to the medical team. For the first aim, we developed features on a digital checklist to obtain the patient context information needed to identify patients at risk for severe blood loss or traumatic brain injury. We also designed and evaluated alerts to prompt timely documentation of critical information and examined automatic approaches to capturing data. For the second aim, we investigated different strategies for communicating information during time-critical medical events to support decision-making. We also examined collaboration, agency, and decision-making within teams responding to medical emergencies and the implications for designing CDSSs used by these teams.
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Details
- Title
- Designing computerized support for identifying and treating patients with life-threatening injuries during medical emergencies
- Creators
- Angela Xaviera Mastrianni
- Contributors
- Aleksandra Sarcevic (Advisor)
- Awarding Institution
- Drexel University
- Degree Awarded
- Doctor of Philosophy (Ph.D.)
- Publisher
- Drexel University; Philadelphia, Pennsylvania
- Number of pages
- xi, [219] pages
- Resource Type
- Dissertation
- Language
- English
- Academic Unit
- Information Science (Informatics) (2013-2026); College of Computing and Informatics (2013-2026); Drexel University
- Other Identifier
- 991021901914204721