University of Kansas
Enhancement and Implementation of an Abdominal Pain Algorithm for Gestational-Age Women: A Quality Improvement Project
Abstract
dc:description.abstractAbdominal pain constitutes 8% of annual ER cases, posing diagnostic challenges, especially in women of childbearing age. Traditional methods often miss pregnancy-related issues. We developed an algorithmic approach for abdominal pain assessment and pregnancy testing to address this. We conducted a Quality Improvement project involving problem identification, algorithm development, implementation, and evaluation. Pre- and post-intervention data revealed significant increases in pregnancy testing, notably in ages 15-25 (99.8% rise). Our algorithm elevates early pregnancy detection, minimizing missed diagnoses. It offers a valuable tool for healthcare providers to improve patient safety and outcomes.
Degree
thesis:*- Grantor dc:publisher
- University of Kansas
- Year dc:date.issued
- 2023
Author and committee
dc:creator, dc:contributor.*- Author dc:creator
-
- Stephenson, Jennifer
- Advisor dc:contributor.advisor
-
- Gray, Jason
Subjects
dc:subject × 1Rights
dc:rights- Statement dc:rights
-
- Copyright held by the author.
- Language dc:language.iso
- en
Identifiers
dc:identifier.*- Dc Identifier Other
- http://dissertations.umi.com/ku:19245
- OAI identifier oai:identifier
- oai:kuscholarworks.ku.edu:1808/38643