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dc.contributor.advisorKim, Jung Hyupeng
dc.contributor.authorParameshwara, Nithineng
dc.date.issued2016eng
dc.date.submitted2016 Falleng
dc.description.abstract[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT REQUEST OF AUTHOR.] The aim of this thesis is to develop and calculate workload using a natural goal operator method and selection rules language (NGOMSL) model to evaluate interaction between emergency staff members and to explore factors influencing the duration and quality of nursing care activities. The importance of proactive and timely patient care in the emergency department (ED) has become evident in the last few years because of the service gap between what the patient needs and the health team provides. For example, advanced technologies and smart devices assist the care providers in delivering disease diagnosis and treatment, but the ability to provide the appropriate clinical services at the right time is limited. Especially when the ED healthcare team has a high workload for a prolonged period, the gulfs between the clinical services needed for the patients and the required services from the ED team widen. These gaps significantly influence the quality of patient care. This study advances our understanding of time and workload related to the clinical processes in an ED. To understand the current ED workflow and observe physicians and nurses' behavior, we visited the ED at Mayo Clinic, Minnesota, collaborating with scientists in systems engineering and conducting a time and motion study on the nurses and physicians working in the ED. Based on the collected data, hierarchical task analysis (HTA) charts were developed. The HTA charts were used as an analytic evaluation technique to understand the detailed process mappings of both physicians and nurses in the ED. Based on the multi-level analyses of the HTA charts, the NGOMSL model was developed. The model advanced our understanding of the care provider's cognitive behavior in the dynamic ED environment. The model also facilitated an understanding of proximal workflow in the ED and the cognitive workload related to managing ED clinical processes. The benefits of conducting this study were (a) improved understanding of the relevant form factors of the clinical process that contribute to a heavy workload in the ED and (b) prevention of potential errors caused by the workload.eng
dc.identifier.urihttps://hdl.handle.net/10355/62575
dc.languageEnglisheng
dc.publisherUniversity of Missouri--Columbiaeng
dc.relation.ispartofcollectionUniversity of Missouri--Columbia. Graduate School. Theses and Dissertationseng
dc.rightsAccess to files is limited to the University of Missouri--Columbia.eng
dc.titleNGOMSL simulation model in an emergency departmenteng
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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