Using Predictive Analytics to Improve Healthcare Outcomes. Группа авторов
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Jacqueline Brown Clinical Educator Golden Jubilee National Hospital Clydebank, Scotland
Dawna Cato Chief Executive Officer Arizona Nurses Association Mesa, AZ, US
Sally Dampier Professor Confederation College Thunder Bay, Ontario, Canada
Inge DiPasquale Manager Division of Palliative Care and Geriatric Medicine St. Joseph’s Health Paterson, NJ, US
Melissa D’Mello Congestive Heart Failure Coordinator St. Joseph’s Health Paterson, NJ, US
Ana Esteban Associate Director Quality Regulatory Compliance Columbia Doctors – The Faculty Practice Organization of Columbia University Irving Medical Center New York, NY, US
Jayne Felgen President Emeritus and Consultant Creative Health Care Management Minneapolis, MN, US
Irit Gantz Coordinator Woman‐Health Division School of Nursing Meir Hospital Kfar‐Saba, Israel
Kary Gillenwaters Chief Executive Officer Solidago Ventures and Consulting Elk River, MN, US
Sebahat Gözüm Dean, School of Nursing Professor, Department of Public Health Nursing Akdeniz University Antalya, Turkey
Lidia Guandalini Cardiology Nurse Federal University São Paulo – Escola Paulista de Enfermagem São Paulo, Brazil
Alicia House Executive Director Steve Rummler Hope Network Minneapolis, MN, US
Mary Ann Hozak Administrative Director Department of Cardiology St. Joseph’s Health Paterson, NJ, US
Michal Itzhaki Senior Lecturer Department of Nursing Tel Aviv University Tel Aviv, Israel
Benson Kahiu Nurse Manager Mount Sinai Health East Orange, NJ, US
Ayla Kaya Research Assistant Director Pediatric Nursing Akdeniz University Antalya, Turkey
Gay L. Landstrom Senior Vice President and Chief Nursing Officer Trinity Health Livonia, MI, US
Marissa Manhart Performance, Safety, and Improvement Coordinator St. Joseph’s Health Paterson, NJ, US
John W. Nelson Chief Executive Officer Healthcare Environment St. Paul, MN, US
Tara Nichols Chief Executive Officer and Clinician Maters of Comfort Mason City, IA, US
Kenneth Oja Research Scientist Denver Health
Assistant Professor
University of Colorado
Denver, Colorado, US
Dawna Maria Perry Chief Nursing Officer Thunder Bay Regional Health Science Center Thunder Bay, Ontario, Canada
Lance Podsiad Manager Helios Epic
Nurse Manager
Henry Ford Health System
Detroit, Michigan, US
Karen Poole Associate Professor Lakehead University School of Nursing Thunder Bay, Ontario, Canada
Rebecca Smith Writer/Editor Minneapolis, MN, US
Susan Smith Chief Executive Officer Choice Dynamic International Leeds, England
Kay Takes President Eastern Iowa Region of MercyOne Dubuque, IA, US
Patricia Thomas Manager – Associate Dean Nursing Faculty Affairs Wayne State University College of Nursing Detroit, MI, US
Anna Trtchounian Emergency Medicine Resident Good Samaritan Hospital Medical Center West Islip, Long Island, NY, US
Sebin Vadasserril Manager Innovative Nursing Practice and Quality St. Joseph’s Health Paterson, NJ, US
Linda Valentino Vice President Nursing Operations Mount Sinai Hospital New York, NY, US
Dominika Vrbnjak Assistant Professor University of Maribor Faculty of Health Sciences Maribor, Slovenia
Josephine (Jo) Sclafani Wahl Associate Director BRG/Prism MI, US
Jacklyn Whitaker Nurse Manager St. Joseph’s Health Paterson, NJ, US
Theresa Williamson Associate Nurse Director Golden Jubilee National Hospital Clydebank, Scotland
Foreword
John W. Nelson and his colleagues are to be congratulated for creating this distinctive book. A very special feature of the book is the use of predictive analytics to explain, amplify, and validate caring theory. All too often, publications focusing on methods such as predictive analytics ignore the theoretical frameworks that guide the collection of data to which analytics are applied. The reader is then left with the thought, “Perhaps interesting results, but so what?” This book provides the answer to “so what?” by presenting the very interesting results, within the contexts of caring theory, specifically Relation‐Based Care®, the Caring Behaviors Assurance System©, and Watson’s Theory of Transpersonal Caring.
The book’s content emphasizes quality improvement, which might be considered the most appropriate application of predictive analytics in healthcare. Determining how, when, and why to improve the quality of healthcare, as a way to improve individual‐level and organization‐level outcomes, is a major challenge for all healthcare team members and researchers. Theory‐based predictive analytics is an innovative approach to meeting this challenge.
A challenge for the authors of the chapters of this book, and for its readers, is to determine the most appropriate place for theory in the triad of data, theory, and operations. Given my passion for the primacy of theory, I recommend that the starting point be theory, which determines what data is to be collected and how the data can be applied to operations.
The case studies that make up the several chapters of Sections Two and Four of this book, the contents of which are as interesting as they are informative, help readers to appreciate the value of theory‐based predictive analytics. The case studies, which range from individual‐level problems to department‐level problems to health system‐level problems, underscore the wide reach of theory‐based predictive analytics.
I contend that the ultimate challenge of predictive analytics will be to carry out the theoretical and empirical work needed to test the book editors’ claim, in the Preface of this book, that the same formulas helping people in the trucking and mining industries to create profiles of risk that enable them to prevent unwanted outcomes before they happen, can be applied successfully to improve healthcare outcomes. Meeting this challenge will undoubtedly extend the knowledge of our discipline, which many of us now refer to as nursology (see https://nursology.net).
Jacqueline