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dc.contributor.advisorKim, Jung Hyupeng
dc.contributor.authorSong, Xuefeieng
dc.date.issued2017eng
dc.date.submitted2017 Summereng
dc.description.abstract[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT REQUEST OF AUTHOR.] The object of this study is to understand the workflow of nurses in the Intensive Care Unit (ICU). The nurses in an ICU experience a high workload every day. It is hard to improve their working processes due to the dynamic uncertainty of their tasks. To advance our understanding of the ICU nurses' workflow, we used the Near-Field Electromagnetic Ranging (NFER) sensors as a real-time location tracking system to improve the accuracy of nurse movements. The data from NFER was combined with manual observation data. This novel approach allowed us analyzing the workflow of the clinical processes in a clearer and more straight way. By using the time-motion studies data from NFER sensors, we could get the accurate standard time of clinical activities and create a clear sequence diagram for each nurse. Based on the time-motion study results, a hierarchical task analysis (HTA) chart was developed which provided us a multi-levels tasks processes for workflow analysis. Then, by comparing with the Sequential Organ Failure Assessment (SOFA) score, Charlson Comorbidity Index, and nurse experience, we tried to figure out whether patient severity level and nurse experience would influence nurses' workflows. The study was conducted in a medical ICU at the University of Missouri Hospital and collected data from 37 registered nurses. According to the time distribution spent on each category, the nurses spent 42.4% on the primary care, 25.6% on the out-of-room activities, 10.8% for peer support, 4.8% on the verbal report and 16.4% on non-nursing activities. In the category of primary care, nurses spent 7.57% of total time on EMR charting in the patient room, 6.87% on assessment, 8.17% on patient care, and 3.95% on preparing/administering medication. Among the out-of-room activities, 8.69% of the total time was spent on EMR charting in the nurse station, and 6.64% was devoted to the conversation between the nurses who participated in the study and others. Furthermore, the results from HTA analysis showed that 1) CCI influence the workflow pattern of in-room activities, the usage of in-room EMR and average process time of out-of-room activities; 2) SOFA score has impact on the workflow pattern of in-room activities, the usage of out-of-room EMR and average process time on nurse handoff and out-of-room activities; 3) nurse experience influence the frequency of performing out-of-room non-nursing activities, workflow pattern of conversations and the usage of out-of-room EMR. The outcomes of this study can provide a detailed workflow of ICU nurses and give nurse managers a deeper understanding of patient care delivery processes. Based on the results of this study, managers could improve current nurse-patient allocation based on patient severity level and nurse work experience, which may reduce the delayed and missed care delivery.eng
dc.identifier.urihttps://hdl.handle.net/10355/65440
dc.languageEnglisheng
dc.publisherUniversity of Missouri--Columbiaeng
dc.relation.ispartofcommunityUniversity of Missouri--Columbia. Graduate School. Theses and Dissertationseng
dc.rightsAccess is limited to the University of Missouri--Columbiaeng
dc.sourceSubmitted by the University of Missouri--Columbia Graduate School.eng
dc.titleHierarchical task analysis for intensive care nursingeng
dc.typeThesiseng
thesis.degree.disciplineIndustrial and manufacturing systems engineering (MU)eng
thesis.degree.grantorUniversity of Missouri--Columbiaeng
thesis.degree.levelMasterseng
thesis.degree.nameM.S.eng


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