Clinical Analytics and Data Management for the DNP, Second Edition

2018-03-28

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Author: Martha L. Sylvia, PhD, MBA, RN
Publisher: Springer Publishing Company
ISBN: 0826142788
Category : Medical
Languages : en
Pages : 396

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 is the only text to deliver the strong data management knowledge and skills that are required competencies for all DNP students. It enables readers to design data tracking and clinical analytics in order to rigorously evaluate clinical innovations/programs for improving clinical outcomes, and to document and analyze change. The second edition is greatly expanded and updated to address major changes in our health care environment. Incorporating faculty and student input, it now includes modalities such as SPSS, Excel, and Tableau to address diverse data management tasks. Eleven new chapters cover the use of big data analytics, ongoing progress towards value-based payment, the ACA and its future, shifting of risk and accountability to hospitals and clinicians, advancement of nursing quality indicators, and new requirements for Magnet certification. The text takes the DNP student step by step through the complete process of data management from planning to presentation, and encompasses the scope of skills required for students to apply relevant analytics to systematically and confidently tackle the clinical interventions data obtained as part of the DNP student project. Of particular value is a progressive case study illustrating multiple techniques and methods throughout the chapters. Sample data sets and exercises, along with objectives, references, and examples in each chapter, reinforce information. Key Features: Provides extensive content for rigorously evaluating DNP innovations/projects Takes DNP students through the complete process of data management from planning through presentation Includes a progressive case study illustrating multiple techniques and methods Offers very specific examples of application and utility of techniques Delivers sample data sets, exercises, PowerPoint slides and more, compiled in Supplemental Materials and an Instructor Manual

Clinical Analytics and Data Management for the DNP

2023-01-18

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Author: Martha L. Sylvia, PhD, MBA, RN
Publisher: Springer Publishing Company
ISBN: 0826163246
Category : Medical
Languages : en
Pages : 495

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. 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

Proposal Writing for Clinical Nursing and DNP Projects, Second Edition

2017-07-28

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Author: Dr. Wanda Bonnel, PhD, RN
Publisher: Springer Publishing Company
ISBN: 0826144438
Category : Medical
Languages : en
Pages : 280

Amazon, 11 reviews for 5-star average: "Excellent, very helpful, to the point, concise without leaving out important details." "Really helps and is easy to understand." This practical, concise, and accessible guide for graduate students and advanced clinicians delivers step-by-step guidelines for integrating research and best evidence to produce concise, well-written project proposals. Health care professionals in advanced practice are increasingly being asked to be able to deliver clinical project proposals using best evidence for advancing quality patient care. With the same “must know” clinical scholarship tools of the first edition, this revision provides practical guidelines of common project models for developing and writing a tight proposal from start to finish while leaving room for the unique nature of most clinical project topics. The second edition includes a completely new chapter on quality improvement concepts, new project proposal abstracts, and new information specific to the DNP project from the AACN. Using the same three-part organization to walk through the intricacies of planning, writing, and completing scholarly project proposals, this new edition also adds new key features to keep readers engaged with the text and their own ongoing or forthcoming proposal. Chapters have been updated to include websites for additional learning, as well as advice from DNP students who have themselves successfully completed project proposals. Reflective questions, tips for completing proposals, exemplars, and reader activities throughout the book facilitate readers’ greater understanding of projects and subsequent proposals. New to the Second Edition: A new chapter on quality improvement concepts Advice from DNP students who have themselves completed proposals Chapter updates and edits for enhanced clarity Websites for additional learning New information specific to the DNP project based on guidance from the AACN Increased emphasis on the Project Triangle, an important foundational structure Key Features: Provides topflight guidance in proposal writing for DNP and other nursing clinical projects Details parameters for integrating scholarship with clearly communicated professional objectives Contains numerous writing prompts and questions that guide students in reflective scholarly writing Offers examples of good writing, reflective questions, and tools for self-assessment Offers helpful tips for making proposals concise yet complete

Healthcare Business Intelligence, + Website

2012-09-04

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Author: Laura Madsen
Publisher: John Wiley & Sons
ISBN: 1118217802
Category : Business & Economics
Languages : en
Pages : 336

Solid business intelligence guidance uniquely designed for healthcare organizations Increasing regulatory pressures on healthcare organizations have created a national conversation on data, reporting and analytics in healthcare. Behind the scenes, business intelligence (BI) and data warehousing (DW) capabilities are key drivers that empower these functions. Healthcare Business Intelligence is designed as a guidebook for healthcare organizations dipping their toes into the areas of business intelligence and data warehousing. This volume is essential in how a BI capability can ease the increasing regulatory reporting pressures on all healthcare organizations. Explores the five tenets of healthcare business intelligence Offers tips for creating a BI team Identifies what healthcare organizations should focus on first Shows you how to gain support for your BI program Provides tools and techniques that will jump start your BI Program Explains how to market and maintain your BI Program The risk associated with doing BI/DW wrong is high, and failures are well documented. Healthcare Business Intelligence helps you get it right, with expert guidance on getting your BI program started and successfully keep it going.

Population Health Analytics

2021-08-02

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Author: Martha L. Sylvia
Publisher: Jones & Bartlett Learning
ISBN: 1284251101
Category : Medical
Languages : en
Pages : 576

As the focus of the health care delivery system continues to move toward a coordinated and accountable system, there is an increasing need for a single resource that focuses on analytics for population health. Population Health Analytics addresses that need by providing detailed information and a “how to” guide for achieving population health analytics. Comprehensive, current, and practical, this logically organized text builds from understanding data sources, to contextualizing data, modeling data, and gleaning insights from that data, which is a natural progression for organizations in progressing to higher levels of analytic capabilities. Furthermore, these frameworks for the population health process and analytics are grounded in an evidence base that is also aligned with theories and processes used in healthcare disciplines. This first of its kind text will prepare students to improve health outcomes, understand patterns of health behavior and more.

Population Health Analytics

2021-03

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Author: Martha L. Sylvia
Publisher: Jones & Bartlett Learning
ISBN: 1284182479
Category : Education
Languages : en
Pages : 576

"Binding: PB"--

Translation of Evidence Into Nursing and Health Care, Second Edition

2016-03-17

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Author: Kathleen M. White, PhD, RN, NEA-BC, FAAN
Publisher: Springer Publishing Company
ISBN: 082611783X
Category : Medical
Languages : en
Pages : 430

Designed as a textbook for the DNP curriculum and as a practical resource for more seasoned health professionals, this acclaimed text encompasses an interprofessional approach to translating evidence into nursing and health care practice that is useful for both clinical and nonclinical environments. The second edition presents new chapters, three of which feature additional approaches for translating evidence into practice, new methods of information technology for translation, and interprofessional collaboration and practice for translation and three that offer 19 exemplars that illustrate actual translation work within the areas of population health and specialty practice, and in the health care system. Consistently woven throughout are the themes of integration and application of knowledge into practice, leadership and evaluating change, leadership strategies for translation, and interprofessional applications across settings. Also included is new information about outcomes management for improvement of direct and indirect care. The second edition continues to deliver applicable theory and strategies to achieve improved outcomes, and meets the DNP core competency requirements. It features a variety of models for change as they relate to translation of research into practice. The text underscores the importance of translating evidence for use in practice to improve health care and health care delivery, and presents strategies to achieve this. It addresses the use of evidence to improve nursing education, discusses how to reduce the divide between researchers and policy makers, and presents expedients for overcoming resistance to change. Extensive lists of references, web links, and other resources enhance learning and support the development of the DNP core competencies. NEW TO THE SECOND EDITION: Addition of an esteemed co-editor Reorganized and revised for enhanced comprehension New chapters: Methods for Translation, Information Technology and Decision Support, Interprofessional Collaboration and Practice for Translation, and Data Management and Evaluation of Translation Three new exemplar chapters: Population Health Exemplars, Specialty Practice Exemplars, and Health Care System Exemplars Updated information on integration and application of knowledge into practice, leading and evaluating change, leadership strategies for translation, and interprofessional application across settings New coverage of outcomes management for improvement of direct and indirect care KEY FEATURES: Offers an in-depth guide for planning, implementing, and translating evidence Includes extensive references necessary for doctoral study Provides the perfect supplement for evidence-based practice materials that often have limited information or value for translation/implementation activities

Healthcare Data Analytics and Management

2018-11-15

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Author: Nilanjan Dey
Publisher: Academic Press
ISBN: 0128156368
Category : Science
Languages : en
Pages : 340

Healthcare Data Analytics and Management help readers disseminate cutting-edge research that delivers insights into the analytic tools, opportunities, novel strategies, techniques and challenges for handling big data, data analytics and management in healthcare. As the rapidly expanding and heterogeneous nature of healthcare data poses challenges for big data analytics, this book targets researchers and bioengineers from areas of machine learning, data mining, data management, and healthcare providers, along with clinical researchers and physicians who are interested in the management and analysis of healthcare data. Covers data analysis, management and security concepts and tools in the healthcare domain Highlights electronic medical health records and patient information records Discusses the different techniques to integrate Big data and Internet-of-Things in healthcare, including machine learning and data mining Includes multidisciplinary contributions in relation to healthcare applications and challenges

Statistics for Advanced Practice Nurses and Health Professionals

2014-06-09

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Author: Manfred Stommel, PhD
Publisher: Springer Publishing Company
ISBN: 0826198252
Category : Medical
Languages : en
Pages : 352

This comprehensive, graduate-level text for advanced practice nurses and other health care professionals provides state-of-the-art tools that facilitate the reading and interpretation of clinical research articles that use increasingly complex statistical techniques. It addresses clinically relevant topics in biostatistics beyond the usual introduction to linear models, such as survival analysis and evaluation of screening tests. The text emphasizes the importance of understanding the underlying logic of statistical inference and statistical models to support correct interpretation and effective translation into practice. It promotes appropriate statistical method selection for conducting translational research. With a focus on disseminating information in easily understandable language, the text addresses basic statistical reasoning and four different classes of statistical models. The appendix provides refreshers on the algebraic underpinnings of statistics. More complex algebraic derivations are highlighted in boxes throughout the text chapters. The text explains how to work with the exponential expressions and logarithms necessary for the interpretation of logistic and hazard regression models and features clear explanations of more sophisticated statistical models, inference, and analyses. Chapters include examples from current research and multiple exercises designed to reinforce learning. Key Features: End-of-chapter exercises include both problems of interpretation and numerical problems that can be solved via hand calculations. For instructors and students interested in practical data analysis, data sets and practice problems are available from Springer Publishing Companyís website with instructions in SPSS, STATA, and SAS formats. At the end of each chapter is a ìLiterature Applicationî text box with interpretation questions about a recent research article that highlights the statistical model discussed in the chapter. Throughout the book, text boxes highlight the most important algebraic formulas useful in interpreting statistical methods. A chapter on data management practices and ethical issues of privacy maintenance is included. Nine appendices provide tables of major probability distributions, for example, normal, t- and F-distributions, and algebraic derivations of some of the most important results in statistics.

Models and Frameworks for Implementing Evidence-Based Practice

2011-09-07

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Author: Jo Rycroft-Malone
Publisher: John Wiley & Sons
ISBN: 1444358731
Category : Medical
Languages : en
Pages : 288

The Evidence-Based Nursing Series is co-published with Sigma Theta Tau International (STTI). The series focuses on implementing evidence-based practice in nursing and mirrors the remit of Worldviews on Evidence-Based Nursing, encompassing clinical practice, administration, research and public policy. Models and Frameworks for Implementing Evidence- Based Practice: Linking Evidence to Action looks at ways of implementing evidence gained through research and factors that influence successful implementation. It acknowledges the gap that exists between obtaining evidence and the practicalities of putting it into practice and provides direction to help to close this gap. This, the first book in the series, helps the reader to make decisions about the appropriateness of using various models and frameworks. A selection of models and frameworks are examined in detail including examples of their use in practice. The book concludes with an analysis and synthesis of the included models and frameworks. The models and frameworks that have been included are based on a number of criteria: that they are internationally recognised, have undergone widespread evaluation and testing, are transferable across different settings, and can be used by different disciplines. Models and frameworks include: Stetler Model Ottowa Model of Research Use IOWA model of evidence-based practice Advancing Research and Clinical Practice through Close Collaboration (ARCC) model Dobbins’ dissemination and use of research evidence for policy and practice framework Joanna Briggs Institute model Knowledge to Action framework Promoting Action on Research Implementation in Health Services (PARIHS) Key Points: Includes an overview of implementation issues and the use of theory and frameworks in implementing evidence into practice Chapters are written by the developers of the model or framework Each chapter provides background on an implementation model or framework, suitable applications, underlying theory and examples of use Each chapter examines strengths and weaknesses of each model alongside barriers and facilitators for its implementation