MOMENTAN AUSVERKAUFT
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Product Identifiers
PublisherSpringer Publishing Company, Incorporated
ISBN-100826163238
ISBN-139780826163233
eBay Product ID (ePID)17058630772
Product Key Features
Number of Pages496 Pages
LanguageEnglish
Publication NameClinical Analytics and Data Management for the Dnp
SubjectNursing / Research & Theory, Nursing / General
Publication Year2023
FeaturesNew Edition
TypeTextbook
Subject AreaMedical
AuthorMary F. Terhaar
FormatTrade Paperback
Dimensions
Item Weight32.1 Oz
Item Length10 in
Item Width7 in
Additional Product Features
Edition Number3
Intended AudienceCollege Audience
LCCN2022-052135
Dewey Edition23
Dewey Decimal610.73072
Edition DescriptionNew Edition
Table Of ContentContributors Foreword for the Third Edition Preface Instructor Resources PART I: INTRODUCTION Chapter 1. Introduction to Clinical Data Management Chapter 2. Analytics and Evidence-Based Practice PART II: DATA PLANNING AND PREPARATION Chapter 3. Using Data to Support the Problem Statement Chapter 4. Preparing for Data Collection Chapter 5. Secondary Data Collection Chapter 6. Primary Data Collection Chapter 7. Using EHR Data for the DNP Project PART III: PREPARING FOR PROJECT IMPLEMENTATION Chapter 8. Determining the Project Measures Chapter 9. Using Statistical Techniques to Plan the DNP Project Chapter 10. Using Workflow Mapping to Plan the DNP Project Implementation Chapter 11. Developing the Analysis Plan Chapter 12. Best Practices for Submission to the Institutional Review Board PART IV: IMPLEMENTING AND EVALUATING PROJECT RESULTS Chapter 13. Creating the Analysis Data Set Chapter 14. Exploratory Data Analysis Chapter 15. Outcomes Data Analysis Chapter 16. Summarizing the Results of the Project Chapter 17. Ongoing Monitoring PART V: KEY COMPETENCIES FOR DNP PRACTICE Chapter 18. Data Governance and Stewardship Chapter 19. Value-Based Care Chapter 20. Nursing Excellence Recognition and Benchmark Programs PART VI: ADVANCED ANALYTIC TECHNIQUES Chapter 21. Data Visualization Chapter 22. Risk Adjustment Chapter 23. Big Data, Data Science, and Analytics Chapter 24. Predictive Modeling Index
SynopsisPraise for the first edition: " 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 This unique text and reference--the only book to address the full spectrum of clinical data management for the DNP student--instills a fundamental understanding of how clinical data is gathered, used, and analyzed, and how to incorporate this data into a quality DNP project. The new third edition is updated to reflect changes in national health policy such as quality measurements, bundled payments for specialty care, and Advances to the Affordable Care Act (ACA) and evolving programs through the Centers for Medicare and Medicaid Services (CMS). The third edition reflects the revision of 2021 AACN Essentials and provides data sets and other examples in Excel and SPSS format, along with several new chapters. This resource takes the DNP student step-by-step through the complete process of data management, from planning through presentation, clinical applications of data management that are discipline-specific, and customization of statistical techniques to address clinical data management goals. Chapters are brimming with descriptions, resources, and exemplars that are helpful to both faculty and students. Topics spotlight requisite competencies for DNP clinicians and leaders such as phases of clinical data management, statistics and analytics, assessment of clinical and economic outcomes, value-based care, quality improvement, benchmarking, and data visualization. A progressive case study highlights multiple techniques and methods throughout the text. Purchase includes online access via most mobile devices or computers. New to the Third Edition: New Chapter: Using EMR Data for the DNP Project New chapter solidifies link between EBP and Analytics for the DNP project New chapter highlights use of workflow mapping to transition between current and future state, while simultaneously visualizing process measures needed to ensure success of the DNP project Includes more examples to provide practical application exercises for students Key Features: Disseminates robust strategies for using available data from everyday practice to support trustworthy evaluation of outcomes Uses multiple tools to meet data management objectives [SPSS, Excel®, Tableau] Presents case studies to illustrate multiple techniques and methods throughout chapters Includes specific examples of the application and utility of these techniques using software that is familiar to graduate nursing students Offers real world examples of completed DNP projects Provides Instructor's Manual, PowerPoint slides, data sets in SPSS and Excel, and forms for completion of data management and evaluation plan, This unique text and reference-the only book to address the full spectrum of clinical data management for the DNP student-instills a fundamental understanding of how clinical data is gathered, used, and analyzed, and how to incorporate this data into a quality DNP project., This unique text and reference-the only book to address the full spectrum of clinical data management for the DNP student-instills a fundamental understanding of how clinical data is gathered, used, and analyzed, and how to incorporate this data into a quality DNP project. The new third edition is updated to reflect changes in national health policy such as quality measurements, bundled payments for specialty care, and Advances to the Affordable Care Act (ACA) and evolving programs through the Centers for Medicare and Medicaid Services (CMS). The third edition reflects the revision of 2021 AACN Essentials and provides data sets and other examples in Excel and SPSS format, along with several new chapters. This resource takes the DNP student step-by-step through the complete process of data management, from planning through presentation, clinical applications of data management that are discipline-specific, and customization of statistical techniques to address clinical data management goals. Chapters are brimming with descriptions, resources, and exemplars that are helpful to both faculty and students. Topics spotlight requisite competencies for DNP clinicians and leaders such as phases of clinical data management, statistics and analytics, assessment of clinical and economic outcomes, value-based care, quality improvement, benchmarking, and data visualization. A progressive case study highlights multiple techniques and methods throughout the text. Purchase includes online access via most mobile devices or computers. New to the Third Edition: New Chapter: Using EMR Data for the DNP Project New chapter solidifies link between EBP and Analytics for the DNP project New chapter highlights use of workflow mapping to transition between current and future state, while simultaneously visualizing process measures needed to ensure success of the DNP project Includes more examples to provide practical application exercises for students Key Features: Disseminates robust strategies for using available data from everyday practice to support trustworthy evaluation of outcomes Uses multiple tools to meet data management objectives [SPSS, Excel (R), Tableau] Presents case studies to illustrate multiple techniques and methods throughout chapters Includes specific examples of the application and utility of these techniques using software that is familiar to graduate nursing students Offers real world examples of completed DNP projects Provides Instructors Manual, PowerPoint slides, data sets in SPSS and Excel, and forms for completion of data management and evaluation plan, Praise for the first edition: "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 This unique text and reference--the only book to address the full spectrum of clinical data management for the DNP student--instills a fundamental understanding of how clinical data is gathered, used, and analyzed, and how to incorporate this data into a quality DNP project. The new third edition is updated to reflect changes in national health policy such as quality measurements, bundled payments for specialty care, and Advances to the Affordable Care Act (ACA) and evolving programs through the Centers for Medicare and Medicaid Services (CMS). The third edition reflects the revision of 2021 AACN Essentials and provides data sets and other examples in Excel and SPSS format, along with several new chapters. This resource takes the DNP student step-by-step through the complete process of data management, from planning through presentation, clinical applications of data management that are discipline-specific, and customization of statistical techniques to address clinical data management goals. Chapters are brimming with descriptions, resources, and exemplars that are helpful to both faculty and students. Topics spotlight requisite competencies for DNP clinicians and leaders such as phases of clinical data management, statistics and analytics, assessment of clinical and economic outcomes, value-based care, quality improvement, benchmarking, and data visualization. A progressive case study highlights multiple techniques and methods throughout the text. Purchase includes online access via most mobile devices or computers. New to the Third Edition: New Chapter: Using EMR Data for the DNP Project New chapter solidifies link between EBP and Analytics for the DNP project New chapter highlights use of workflow mapping to transition between current and future state, while simultaneously visualizing process measures needed to ensure success of the DNP project Includes more examples to provide practical application exercises for students Key Features: Disseminates robust strategies for using available data from everyday practice to support trustworthy evaluation of outcomes Uses multiple tools to meet data management objectives [SPSS, Excel(R), Tableau] Presents case studies to illustrate multiple techniques and methods throughout chapters Includes specific examples of the application and utility of these techniques using software that is familiar to graduate nursing students Offers real world examples of completed DNP projects Provides Instructor's Manual, PowerPoint slides, data sets in SPSS and Excel, and forms for completion of data management and evaluation plan
LC Classification NumberRT81.5S97 2024
