NURS 6512 Assignment DCE Health History Assessment 

NURS 6512 Assignment DCE Health History Assessment

NURS 6512 Assignment DCE Health History Assessment

A comprehensive health history is essential to providing quality care for patients across the lifespan, as it helps to properly identify health risks, diagnose patients, and develop individualized treatment plans. To effectively collect these heath histories, you must not only have strong communication skills, but also the ability to quickly establish trust and confidence with your patients. For this DCE Assignment, you begin building your communication and assessment skills as you collect a health history from a volunteer “patient.”

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NURS 6512 Digital Clinical Experience (DCE) Health History Assessment 
NURS 6512 Digital Clinical Experience (DCE) Health History Assessment

To Prepare

Review this week’s Learning Resources as well as the Taking a Health History media program, and consider how you might incorporate these strategies. Download and review the Student Checklist: Health History Guide and the History Subjective Data Checklist, provided in this week’s Learning Resources, to guide you through the necessary components of the assessment.

Access and login to Shadow Health using the link in the left-hand navigation of the Blackboard classroom.

Review the Shadow Health Student Orientation media program and the Useful Tips and Tricks document provided in the week’s Learning Resources to guide you through Shadow Health.

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Review the Week 4 DCE Health History Assessment Rubric, provided in the Assignment submission area, for details on completing the Assignment.

DCE Health History Assessment:

Complete the following in Shadow Health:


DCE Orientation (15 minutes)

Conversation Concept Lab (50 minutes)

Health History

Health History of Tina Jones (180 minutes)

A numerical description of dry non-crimp fabrics is proposed at the scale of the filaments using a commercially available finite element software package. Deviations in the filament orientation of the fibrous layer is a dominant factor in the occurrence of local defects, which influences the mechanical response of the textile. Therefore, the introduction of variability in the orientation distribution is proposed in this paper. This approach enables to capture the entanglement of the filaments and models all interaction mechanisms. A stepwise generation of the numerical non-crimp fabric is proposed considering the main manufacturing steps to reproduce the local defects in the fibrous mat appropriately. Averaged periodic boundary conditions are developed ensuring an overall periodicity of the model while allowing reorientation at the scale of the filaments. Two various non-crimp fabrics are investigated and modelled. The distribution of the filaments in the simulation results correlate well with measurements of the filament orientation performed on the textiles. Moreover, a detailed comparison of the local defects shows a good agreement with measurements on the specimens. The presented approach can be used to generate geometries for subsequent virtual characterization.