Clinical Analytics and Data Management for the DNP

Nonfiction, Health & Well Being, Medical, Nursing, Research & Theory, Management & Leadership
Cover of the book Clinical Analytics and Data Management for the DNP by Martha L. Sylvia, PhD, MBA, RN, Springer Publishing Company
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Author: Martha L. Sylvia, PhD, MBA, RN ISBN: 9780826129741
Publisher: Springer Publishing Company Publication: May 5, 2014
Imprint: Springer Publishing Company Language: English
Author: Martha L. Sylvia, PhD, MBA, RN
ISBN: 9780826129741
Publisher: Springer Publishing Company
Publication: May 5, 2014
Imprint: Springer Publishing Company
Language: English

"DNP students may struggle with data management, since their projects are not research, but quality improvement, and this book covers the subject well. I recommend it for DNP students for use during their capstone projects." Score: 98, 5 Stars.--Doody's Medical Reviews

Strong data management knowledge and skills are a requirement for every DNP. This unique text focuses on fostering the rigorous, meticulous data management skills that can improve care experience, health outcomes, and cost savings worldwide. It provides a knowledge base, describes the regulatory and ethical context, outlines a process to guide evaluation, presents a compendium of resources, and includes examples of evaluation of translation. It takes the DNP student step by step through the complete process of data management, including planning, data collection, data governance and cleansing, analysis, and data presentation. Moreover, the text continues the process of establishing a sturdy clinical data management (CDM) skill base by presenting techniques for ongoing project monitoring after analysis and evaluation are concluded.

A progressive case study illustrates multiple techniques throughout each chapter, enabling students to apply what they have learned to their own DNP projects. The book features information from professors who are highly experienced in teaching CDM as well as a renowned scholar of population health analytics. The text provides very specific examples of techniques using SPSSÆ software that is familiar to graduate nursing students. Chapters include objectives, references, and examples from translation projects to assist students to learn and apply chapter content. Appendices describe numerous tools and practical strategies compiled by the authors over several years of teaching CDM to DNP students.

Key Features:

  • Meets the specific data management needs of the DNP student from planning to presentation
  • Presents a wide selection of data display options through frequent illustrations of SPSS data
  • Uses a progressive case study to illustrate multiple techniques and methods throughout chapters
  • Provides substantial content necessary for the DNP student to rigorously evaluate DNP innovations/projects
  • Includes very specific examples of the application and utility of these techniques using software that is familiar to graduate nursing students
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"DNP students may struggle with data management, since their projects are not research, but quality improvement, and this book covers the subject well. I recommend it for DNP students for use during their capstone projects." Score: 98, 5 Stars.--Doody's Medical Reviews

Strong data management knowledge and skills are a requirement for every DNP. This unique text focuses on fostering the rigorous, meticulous data management skills that can improve care experience, health outcomes, and cost savings worldwide. It provides a knowledge base, describes the regulatory and ethical context, outlines a process to guide evaluation, presents a compendium of resources, and includes examples of evaluation of translation. It takes the DNP student step by step through the complete process of data management, including planning, data collection, data governance and cleansing, analysis, and data presentation. Moreover, the text continues the process of establishing a sturdy clinical data management (CDM) skill base by presenting techniques for ongoing project monitoring after analysis and evaluation are concluded.

A progressive case study illustrates multiple techniques throughout each chapter, enabling students to apply what they have learned to their own DNP projects. The book features information from professors who are highly experienced in teaching CDM as well as a renowned scholar of population health analytics. The text provides very specific examples of techniques using SPSSÆ software that is familiar to graduate nursing students. Chapters include objectives, references, and examples from translation projects to assist students to learn and apply chapter content. Appendices describe numerous tools and practical strategies compiled by the authors over several years of teaching CDM to DNP students.

Key Features:

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