1.

Record Nr.

UNINA9910458010903321

Autore

Sylvia Martha L.

Titolo

Clinical analytics and data management for the DNP / / Martha L. Sylvia, Mary F. Terhaar ; Margaret Zuccarini, acquisition editor

Pubbl/distr/stampa

New York : , : Springer Publishing Company, , 2014

©2014

ISBN

0-8261-2974-9

Descrizione fisica

1 online resource (239 p.)

Disciplina

610.73072

Soggetti

Nursing - Research

Nursing - Research - Methodology

Electronic books.

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Note generali

Description based upon print version of record.

Nota di bibliografia

Includes bibliographical references at the end of each chapters and index.

Nota di contenuto

Cover; Title; Copyright; Contents; Contributors; Foreword; Preface; Acknowledgments; Chapter 1: Introduction to Clinical Data Management; Translation; The Doctor of Nursing Practice as Translator and Analyst; The Context of Discovery and Innovation; Clinical Data Management; Chapter 2: Basic Statistical Concepts and Power Analysis; Thoughtful Planning; Chapter 3: Preparing for Data Collection; Chapter 4: Developing the Analysis Plan; Chapter 5: Data Governance and Stewardship; Careful and Effective Action; Chapter 6: Creating the Analysis Data Set; Chapter 7: Exploratory Data Analysis

Chapter 8: Outcomes Data AnalysisChapter 9: Summarizing the Results of the Project Evaluation; Chapter 10: Ongoing Monitoring; Conclusion; References; Chapter 2: Basic Statistical Concepts and Power Analysis; Learning Objectives; Review of Variable Concepts; Types of Variables; Basic Statistical Tests and Choosing Appropriately; Sample Size Calculation Using Power Analysis; Components of Power Analysis; Sample Size Determination for Paired Data; Sample Size Determination for Proportions; Influence of Other Factors on Sample Size; Using Sample Size Calculators; Summary; References

Chapter 3: Preparing for Data CollectionLearning Objectives; Primary and Secondary Data; Definition; Deciding Which Data Sources to Use;



Using Primary Data; Reliability and Validity of Data Collection Instruments; Data Collection Mechanisms; Using Secondary Data; Sources of Secondary Data; Requesting Secondary Data From an Organization; Summary; References; Chapter 4: Developing the Analysis Plan; Learning Objectives; Applying the Analysis Question; Determining the Unit of Analysis; Creating Comparison Groups; Elements Used to Describe the Unit of Analysis

Determining the Variables of the Data SetDescriptive Information; Outcomes Information; Summary; References; Case Study; Case Study Example: Complete Evaluation Plan; Outcomes, Measures, Calculations , and Variables; Outcomes, Measures, Calculations , and Variables; Case Study Example: Power Analysis; Chapter 5: Data Governance and Stewardship; Learning Objectives; Background; Definitions; Historical Context of Data Governance and Stewardship; Laws Relevant to Human Subjects Research; Food and Drug Regulations; Nuremberg Code; Declaration of Helsinki; National Research Service Award Act

Belmont ReportCommon Rule; Regulation of Data Management in Health Care Organizations; Health Insurance Portability and Accountability Act; Data Governance and Analytics Today; Quality Improvement (QI); The Role of the Institutional Review Board (IRB) in Translation and QI; Organization-Specific Data Governance Processes; Data Stewardship, Governance Structures, and Processes Within the Organization; Meaningful Use; Privacy; Ownership; Access; Planning for Data Governance; Level of Patient Identification Within Data Sets; The Institutional Review Board; Summary; References

Chapter 6: Creating the Analysis Data Set

Sommario/riassunto

Strong data management knowledge and skills are a requirement for every DNP graduate. 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 effects. It takes the DNP student step-by-step through the complete process of data management including planning, data collection, data governanc