IALH Research Fellows Roudsari, Abdul and Courtney, Karen have co-authored a new conference paper entitled Data Preparation for Supervised Learning: Improving Nursing Situation Awareness to Reduce Healthcare-Acquired Urinary Tract Infection. Collaborating authors include Alqarrain Yaser and Tanaka, Jim. This research was presented at the 16th International Congress on Nursing Informatics in Manchester, July 2024.
Abstract: Situation awareness (SA) is an important non-technical skill for nurses. Nurses interact directly with patients and review their clinical signs. If we improve nurses’ SA, they will likely detect clinical changes and prevent patient harm. A clinical endeavor that can benefit from improved nurses’ SA is the prevention of Healthcare-Acquired Urinary Tract Infection (HAUTI). Electronic Health Records contain comprehensive nursing assessment data that researchers can use to analyze trends and provide a context-based understanding of the infection risk factors. We conducted a study that involved extracting nursing assessment data and preparing it for supervised learning algorithms and predicting HAUTI. In this paper, we share the methods we used to prepare the data for supervised learning algorithms and present the challenges related to data missingness.
To read the full article, see doi 10.3233/SHTI240158