Cover -- Title -- Copyright -- Contents -- Contributors -- Foreword -- References -- Preface -- References -- Share Clinical Analytics and Data Management for the DNP, Second Edition -- Chapter 1: Introduction to Clinical Data Management -- Problem Solving -- Translation -- The Doctor of Nursing Practice as Problem Solver, Translator, and Analyst -- The Context of Discovery and Innovation -- Clinical Data Management (CDM) -- Chapter 2: Basic Statistical Concepts and Power Analysis -- Thoughtful Planning -- Chapter 3: Value-Based Purchasing -- Chapter 4: Using Data to Support the Problem Statement -- Chapter 5: Selecting Quality Measures -- Chapter 6: Preparing for Data Collection -- Chapter 7: Secondary Data Collection -- Chapter 8: Primary Data Collection -- Chapter 9: Developing the Analysis Plan -- Accountability and Approval -- Chapter 10: Data Governance and Stewardship -- Chapter 11: Best Practices for Submission to the Institutional Review Board -- Careful and Effective Analysis -- Chapter 12: Creating the Analysis Data Set -- Chapter 13: Exploratory Data Analysis -- Chapter 14: Outcomes Data Analysis -- Evaluation -- Chapter 15: Summarizing the Results of the Project Evaluation -- Chapter 16: Ongoing Monitoring -- Reporting -- Chapter 17: Data Visualization -- Chapter 18: Nursing Excellence Recognition and Benchmarking Programs -- Special Considerations -- Chapter 19: Risk Adjustment -- Chapter 20: Big Data, Data Science, and Analytics -- Chapter 21: Predictive Modeling -- Conclusion -- References -- Chapter 2: Basic Statistical Concepts and Power Analysis -- 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 -- References -- Chapter 3: Value-Based Purchasing -- What is Value-Based Purchasing? -- Conditions Driving VBP -- Policy Perspective -- Facilitators and Barriers -- Broad Adoption -- Carrots and Stick -- Understanding the Measures -- Data Demands -- Competency and Capacity Demands -- Outpatient Services and Primary Care -- Unintended Consequences -- References -- Chapter 4: Using Data to Support the Problem Statement -- Problem Statements in DNP Quality Improvement Projects -- Why Use Data to Support the Problem Statement? -- Where to Find Data to Support the Problem Statement -- Local Data -- State, Regional, and National Data -- Problem Statement Exemplar -- Evidence-Based Sedation Management and Early Physical Activity in the ICU -- References -- Chapter 5: Selecting Quality Measures -- Definitions -- Why Measure Quality? -- Structure, Process, Outcome -- Considerations for the Selection of Measures -- References -- Chapter 6: Preparing for Data Collection -- Primary and Secondary Data -- Benefits and Limitations -- The Decision to Us.
e Primary or Secondary Data -- Chapter 7: Secondary Data Collection -- Secondary Data -- Definition -- Sources for Secondary Data -- Health Information Exchange -- Electronic Health Record -- Health Risk Assessment -- Administrative Medical Claims Data) -- Administrative Pharmacy Claims Data -- Billing Data -- Laboratory Vendor Data -- Device Monitoring Data -- Research Databases -- National Health and Nutrition Examination Survey -- Behavioral Risk Factor Surveillance System -- Methods for Obtaining Secondary Data -- Requesting Secondary Data from Organizations -- Examples of Secondary Data Sets -- Quality (Reliability and Validity) of Secondary Data -- Defining Concepts of Secondary Data -- Storing Secondary Data -- Exemplar -- Project Overview -- Project Aims -- Clinical Data Management Evaluation Plan -- Overall Project Purpose Statement -- Population Description Tables -- Demographic Variables -- Aim 1: Increase the Number of Baby Boomers (Individuals Born from 1945 to 1965) Receiving Appropriate Screening for HCV -- Update February Year 2 -- Demographic Variables -- Update February Year 2 -- Evidence From the Literature for This Outcome Selection and Expectation -- Demographic Variables -- Aim 2: Increase the Number of Individuals With HCV Who Receive Appropriate Referral for Treatment to Project Echo or Other Appropriate Treatment Source -- Update February Year 2 -- Evidence From the Literature for This Outcome Selection and Expectation -- Aim 3: Increase the Percentage of CHCI Providers Who Utilize Project Echo, A Telehealth Model of Knowledge Transfer -- Overall Status Update February Year 2 -- References -- Chapter 8: Primary Data Collection -- Primary Data -- Methods of Collecting Primary Data -- Analyzing the Quality of Primary Data -- Exemplar -- Project Overview -- Data Collection -- References -- Chapter 9: Developing the Analysis Plan -- 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 Set -- Descriptive Information -- Outcomes Information -- Exemplar -- Overall Project Purpose Statement -- Events Description -- Descriptive Variables -- Aim 1: Implement a Standardized Intershift Handoff Tool -- Evidence from the Literature for This Outcome Selection and Expectation -- Aim 2: Train RNS on Effective Handoff Communication Skills -- Population Definitions -- Demographic Variables -- Aim 3: Reorganize Interconnected Processes that Occur During the Intershift Handoffs -- Event Description -- Demographic Variables -- References -- Chapter 10: Data Governance and Stewardship -- Background -- Definitions -- Organizational Data Governance Policy -- Health Insurance Portability and Accountability Act -- Developing Organizational Policy -- Data Stewardship, Governance Structures, and Processes Within the Organization -- Meaningful Use -- Patient Identifiers -- References -- Chapter 11: Best Practices for S.
ubmission to the Institutional Review Board -- The Work of the IRB -- Laws Relevant to Human Subjects Research -- Food and Drug Regulations -- Nuremberg Code -- Declaration of Helsinki -- Research, Translation, and Quality Improvement -- Proposals that Require IRB Review -- Best Practices for Smooth Submission -- References -- Chapter 12: Creating the Analysis Data Set -- Preliminary Data Preparation -- Initial and Interim Data Sets -- Maintaining Integrity During the Data Collection Process -- Importing Data Into the Statistical Software -- Documenting the Steps of Data Analysis Using Syntax -- Data Cleansing -- Common Types of Data Errors and Their Assessment -- Methods for Assessing Data Cleanliness/Quality -- Managing Data Errors -- File and Data Manipulation -- File Manipulation -- Data Manipulation -- Final Analysis Data Set and Data Dictionary -- The Data Dictionary -- References -- Chapter 13: Exploratory Data Analysis -- Exploring Distributions of Values for Each Variable -- Nominal Variables -- Dichotomous Variables -- Ordinal Variables -- Continuous Variables -- References -- Chapter 14: Outcomes Data Analysis -- Bivariate Statistical Testing -- Independent t-Test -- Anova -- Chi-Square -- Paired t-Test -- Correlation -- p Values -- Describing the Unit of Analysis and Differences Between Groups -- Describing Uncertainty -- Recognizing Confounding -- Performing Bivariate Statistical Testing of Outcome Measures -- Performing Multivariate Testing of Outcomes -- Multiple Linear Regression -- Multiple Logistic Regression -- Other Considerations When Measuring Outcomes -- Nonparametric Testing -- Complex Statistical Models -- References -- Chapter 15: Summarizing the Results of the Project Evaluation -- Reporting Results -- Summarizing the Data Management Plan -- Flow Diagrams -- Data Collection Processes -- Data Governance -- Data Cleansing and Manipulation -- Exploratory Data Analysis -- Outcomes Results -- Summary of Results -- Describing Data-Related Limitations -- Important Aspects of Visualization and Display of Results -- Graphs -- Tables -- References -- Chapter 16: Ongoing Monitoring -- The Need for Ongoing Monitoring -- Goals of Ongoing Monitoring -- Challenges in Ongoing Monitoring -- Run Charts and SPC -- Defining Variation -- Run Charts -- SPC Charts -- Benefits and Limitations of SPC -- Creating and Interpreting SPC Charts -- Understanding Run Charts and SPC Charts -- Benchmarks -- What Is Benchmarking? -- Choosing a Benchmark -- Choosing Measures for Benchmarking -- Challenges in Benchmarking -- Sources of Healthcare Benchmarks -- Displaying Benchmark Data -- Continuous Quality Improvement -- CQI and Ongoing Monitoring -- Types of CQI Models -- One Example of a QI Method: PDSA -- References -- Chapter 17: Data Visualization -- Introduction and Background -- Data Visualization Concepts and Techniques -- Data Visualization Software and Tools -- The Data Story -- References -- Chapter 18: Nursing Excellence Recognition and Benchm.
