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  • Book
    Martha L. Sylvia, Mary F. Terhaar.
    Summary: "When we first conceived of this book, our intent was to create a resource that would introduce the theory, processes, and tools needed by professionals to achieve impactful clinical scholarship. We described improvement processes that originated with data from practice which pointed to opportunities to improve and concluded with data that helped to determine if the evidence-based solutions implemented had been effective. We are excited by the number of programs that have adopted this book as a course text, by the quality of the clinical scholarship that has employed this process, and by our conversations with faculty, students, and DNPs like you at conferences where you have shared the pride you feel in the success you have achieved. It is again time to refresh this resource in order to continue to advance high-quality, high-impact clinical scholarship in the context of a great many developments in policy, analytics, and innovation. In this third edition, we intend to help you stay in the groove with the world of big data, value-based care, and data-driven decision making. We maintain our bright focus on prevention, population health, and the contribution of DNPs to clinical scholarship and practice leadership"-- Provided by publisher.

    Contents:
    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.
    Digital Access R2Library [2024]