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| examples of workflow analysis in healthcare: Patient Safety and Quality Ronda Hughes, 2008 Nurses play a vital role in improving the safety and quality of patient car -- not only in the hospital or ambulatory treatment facility, but also of community-based care and the care performed by family members. Nurses need know what proven techniques and interventions they can use to enhance patient outcomes. To address this need, the Agency for Healthcare Research and Quality (AHRQ), with additional funding from the Robert Wood Johnson Foundation, has prepared this comprehensive, 1,400-page, handbook for nurses on patient safety and quality -- Patient Safety and Quality: An Evidence-Based Handbook for Nurses. (AHRQ Publication No. 08-0043). - online AHRQ blurb, http://www.ahrq.gov/qual/nurseshdbk/ |
| examples of workflow analysis in healthcare: Textbook of Patient Safety and Clinical Risk Management Liam Donaldson, Walter Ricciardi, Susan Sheridan, Riccardo Tartaglia, 2020-12-14 Implementing safety practices in healthcare saves lives and improves the quality of care: it is therefore vital to apply good clinical practices, such as the WHO surgical checklist, to adopt the most appropriate measures for the prevention of assistance-related risks, and to identify the potential ones using tools such as reporting & learning systems. The culture of safety in the care environment and of human factors influencing it should be developed from the beginning of medical studies and in the first years of professional practice, in order to have the maximum impact on clinicians' and nurses' behavior. Medical errors tend to vary with the level of proficiency and experience, and this must be taken into account in adverse events prevention. Human factors assume a decisive importance in resilient organizations, and an understanding of risk control and containment is fundamental for all medical and surgical specialties. This open access book offers recommendations and examples of how to improve patient safety by changing practices, introducing organizational and technological innovations, and creating effective, patient-centered, timely, efficient, and equitable care systems, in order to spread the quality and patient safety culture among the new generation of healthcare professionals, and is intended for residents and young professionals in different clinical specialties. |
| examples of workflow analysis in healthcare: A Guide to Lean Healthcare Workflows Jerry Green, Amy Valentini, IBM Redbooks, 2016-10-11 Is Lean a fit for your healthcare organization? Various methodologies can be used to help organizations achieve their objectives depending on their criteria: lowest risk of failure, fast to resolution, or lowest cost for deployment. But what every organization should consider is which methodology will have the greatest impact. Lean, a systematic approach to understanding and optimizing processes, may be the fit for your organization. Learn more in this new IBM® RedpaperTM publication, A Guide to Lean Healthcare Workflows, by Jerry Green and Amy Valentini of Phytel (An IBM Company). The paper delves into the five steps of Lean: Define value from the patient's perspective Map the value stream, and identify issues and constraints Remove waste, and make the value flow without interruption Implement the solution, and allow patients to pull value Maintain the gain, and pursue perfection It describes each step in-depth and includes techniques, example worksheets, and materials that can be used during the overall analysis and implementation process. And it provides insights that are derived from the real-world experience of the authors. This paper is intended to serve as a guide for readers during a process-improvement project and is not necessarily intended to be read end-to-end in one sitting. It is written primarily for clinical practitioners to use as a step-by-step guide to lean out clinical workflows without having to rely on complex statistical hypothesis-testing tools. This guide can also be used by clinical or nonclinical practitioners in non-patient-centered workflows. The steps are based on a universal Lean language that uses industry-standard terms and techniques and, therefore, can be applied to almost any process. |
| examples of workflow analysis in healthcare: Process Mining in Healthcare Ronny S. Mans, Wil M. P. van der Aalst, Rob J. B. Vanwersch, 2015-03-12 What are the possibilities for process mining in hospitals? In this book the authors provide an answer to this question by presenting a healthcare reference model that outlines all the different classes of data that are potentially available for process mining in healthcare and the relationships between them. Subsequently, based on this reference model, they explain the application opportunities for process mining in this domain and discuss the various kinds of analyses that can be performed. They focus on organizational healthcare processes rather than medical treatment processes. The combination of event data and process mining techniques allows them to analyze the operational processes within a hospital based on facts, thus providing a solid basis for managing and improving processes within hospitals. To this end, they also explicitly elaborate on data quality issues that are relevant for the data aspects of the healthcare reference model. This book mainly targets advanced professionals involved in areas related to business process management, business intelligence, data mining, and business process redesign for healthcare systems as well as graduate students specializing in healthcare information systems and process analysis. |
| examples of workflow analysis in healthcare: Data Analytics in Medicine Information Resources Management Association, 2019-11-18 This book examines practical applications of healthcare analytics for improved patient care, resource allocation, and medical performance, as well as for diagnosing, predicting, and identifying at-risk populations-- |
| examples of workflow analysis in healthcare: Clinical Informatics Study Guide John T. Finnell, Brian E. Dixon, 2022-04-22 This completely updated study guide textbook is written to support the formal training required to become certified in clinical informatics. The content has been extensively overhauled to introduce and define key concepts using examples drawn from real-world experiences in order to impress upon the reader the core content from the field of clinical informatics. The book groups chapters based on the major foci of the core content: health care delivery and policy; clinical decision-making; information science and systems; data management and analytics; leadership and managing teams; and professionalism. The chapters do not need to be read or taught in order, although the suggested order is consistent with how the editors have structured their curricula over the years. Clinical Informatics Study Guide: Text and Review serves as a reference for those seeking to study for a certifying examination independently or periodically reference while in practice. This includes physicians studying for board examination in clinical informatics as well as the American Medical Informatics Association (AMIA) health informatics certification. This new edition further refines its place as a roadmap for faculty who wish to go deeper in courses designed for physician fellows or graduate students in a variety of clinically oriented informatics disciplines, such as nursing, dentistry, pharmacy, radiology, health administration and public health. |
| examples of workflow analysis in healthcare: Improving Diagnosis in Health Care National Academies of Sciences, Engineering, and Medicine, Institute of Medicine, Board on Health Care Services, Committee on Diagnostic Error in Health Care, 2015-12-29 Getting the right diagnosis is a key aspect of health care - it provides an explanation of a patient's health problem and informs subsequent health care decisions. The diagnostic process is a complex, collaborative activity that involves clinical reasoning and information gathering to determine a patient's health problem. According to Improving Diagnosis in Health Care, diagnostic errors-inaccurate or delayed diagnoses-persist throughout all settings of care and continue to harm an unacceptable number of patients. It is likely that most people will experience at least one diagnostic error in their lifetime, sometimes with devastating consequences. Diagnostic errors may cause harm to patients by preventing or delaying appropriate treatment, providing unnecessary or harmful treatment, or resulting in psychological or financial repercussions. The committee concluded that improving the diagnostic process is not only possible, but also represents a moral, professional, and public health imperative. Improving Diagnosis in Health Care, a continuation of the landmark Institute of Medicine reports To Err Is Human (2000) and Crossing the Quality Chasm (2001), finds that diagnosis-and, in particular, the occurrence of diagnostic errorsâ€has been largely unappreciated in efforts to improve the quality and safety of health care. Without a dedicated focus on improving diagnosis, diagnostic errors will likely worsen as the delivery of health care and the diagnostic process continue to increase in complexity. Just as the diagnostic process is a collaborative activity, improving diagnosis will require collaboration and a widespread commitment to change among health care professionals, health care organizations, patients and their families, researchers, and policy makers. The recommendations of Improving Diagnosis in Health Care contribute to the growing momentum for change in this crucial area of health care quality and safety. |
| examples of workflow analysis in healthcare: Cognitive Informatics Kai Zheng, Johanna Westbrook, Thomas G. Kannampallil, Vimla L. Patel, 2019-07-25 This timely book addresses gaps in the understanding of how health information technology (IT) impacts on clinical workflows and how the effective implementation of these workflows are central to the safe and effective delivery of care to patients. It features clearly structured chapters covering a range of topics, including aspects of clinical workflows relevant to both practitioners and patients, tools for recording clinical workflow data techniques for potentially redesigning health IT enabled care coordination. Cognitive Informatics: Reengineering Clinical Workflow for More Efficient and Safer Care enables readers to develop a deeper understanding of clinical workflows and how these can potentially be modified to facilitate greater efficiency and safety in care provision, providing a valuable resource for both biomedical and health informatics professionals and trainees. |
| examples of workflow analysis in healthcare: Artificial Intelligence in Healthcare Adam Bohr, Kaveh Memarzadeh, 2020-06-21 Artificial Intelligence (AI) in Healthcare is more than a comprehensive introduction to artificial intelligence as a tool in the generation and analysis of healthcare data. The book is split into two sections where the first section describes the current healthcare challenges and the rise of AI in this arena. The ten following chapters are written by specialists in each area, covering the whole healthcare ecosystem. First, the AI applications in drug design and drug development are presented followed by its applications in the field of cancer diagnostics, treatment and medical imaging. Subsequently, the application of AI in medical devices and surgery are covered as well as remote patient monitoring. Finally, the book dives into the topics of security, privacy, information sharing, health insurances and legal aspects of AI in healthcare. - Highlights different data techniques in healthcare data analysis, including machine learning and data mining - Illustrates different applications and challenges across the design, implementation and management of intelligent systems and healthcare data networks - Includes applications and case studies across all areas of AI in healthcare data |
| examples of workflow analysis in healthcare: Registries for Evaluating Patient Outcomes Agency for Healthcare Research and Quality/AHRQ, 2014-04-01 This User’s Guide is intended to support the design, implementation, analysis, interpretation, and quality evaluation of registries created to increase understanding of patient outcomes. For the purposes of this guide, a patient registry is an organized system that uses observational study methods to collect uniform data (clinical and other) to evaluate specified outcomes for a population defined by a particular disease, condition, or exposure, and that serves one or more predetermined scientific, clinical, or policy purposes. A registry database is a file (or files) derived from the registry. Although registries can serve many purposes, this guide focuses on registries created for one or more of the following purposes: to describe the natural history of disease, to determine clinical effectiveness or cost-effectiveness of health care products and services, to measure or monitor safety and harm, and/or to measure quality of care. Registries are classified according to how their populations are defined. For example, product registries include patients who have been exposed to biopharmaceutical products or medical devices. Health services registries consist of patients who have had a common procedure, clinical encounter, or hospitalization. Disease or condition registries are defined by patients having the same diagnosis, such as cystic fibrosis or heart failure. The User’s Guide was created by researchers affiliated with AHRQ’s Effective Health Care Program, particularly those who participated in AHRQ’s DEcIDE (Developing Evidence to Inform Decisions About Effectiveness) program. Chapters were subject to multiple internal and external independent reviews. |
| examples of workflow analysis in healthcare: Computational Technology for Effective Health Care National Research Council, Division on Engineering and Physical Sciences, Computer Science and Telecommunications Board, Committee on Engaging the Computer Science Research Community in Health Care Informatics, 2009-02-24 Despite a strong commitment to delivering quality health care, persistent problems involving medical errors and ineffective treatment continue to plague the industry. Many of these problems are the consequence of poor information and technology (IT) capabilities, and most importantly, the lack cognitive IT support. Clinicians spend a great deal of time sifting through large amounts of raw data, when, ideally, IT systems would place raw data into context with current medical knowledge to provide clinicians with computer models that depict the health status of the patient. Computational Technology for Effective Health Care advocates re-balancing the portfolio of investments in health care IT to place a greater emphasis on providing cognitive support for health care providers, patients, and family caregivers; observing proven principles for success in designing and implementing IT; and accelerating research related to health care in the computer and social sciences and in health/biomedical informatics. Health care professionals, patient safety advocates, as well as IT specialists and engineers, will find this book a useful tool in preparation for crossing the health care IT chasm. |
| examples of workflow analysis in healthcare: Health Care Comes Home National Research Council, Division of Behavioral and Social Sciences and Education, Board on Human-Systems Integration, Committee on the Role of Human Factors in Home Health Care, 2011-06-22 In the United States, health care devices, technologies, and practices are rapidly moving into the home. The factors driving this migration include the costs of health care, the growing numbers of older adults, the increasing prevalence of chronic conditions and diseases and improved survival rates for people with those conditions and diseases, and a wide range of technological innovations. The health care that results varies considerably in its safety, effectiveness, and efficiency, as well as in its quality and cost. Health Care Comes Home reviews the state of current knowledge and practice about many aspects of health care in residential settings and explores the short- and long-term effects of emerging trends and technologies. By evaluating existing systems, the book identifies design problems and imbalances between technological system demands and the capabilities of users. Health Care Comes Home recommends critical steps to improve health care in the home. The book's recommendations cover the regulation of health care technologies, proper training and preparation for people who provide in-home care, and how existing housing can be modified and new accessible housing can be better designed for residential health care. The book also identifies knowledge gaps in the field and how these can be addressed through research and development initiatives. Health Care Comes Home lays the foundation for the integration of human health factors with the design and implementation of home health care devices, technologies, and practices. The book describes ways in which the Agency for Healthcare Research and Quality (AHRQ), the U.S. Food and Drug Administration (FDA), and federal housing agencies can collaborate to improve the quality of health care at home. It is also a valuable resource for residential health care providers and caregivers. |
| examples of workflow analysis in healthcare: Crossing the Quality Chasm Institute of Medicine, Committee on Quality of Health Care in America, 2001-07-19 Second in a series of publications from the Institute of Medicine's Quality of Health Care in America project Today's health care providers have more research findings and more technology available to them than ever before. Yet recent reports have raised serious doubts about the quality of health care in America. Crossing the Quality Chasm makes an urgent call for fundamental change to close the quality gap. This book recommends a sweeping redesign of the American health care system and provides overarching principles for specific direction for policymakers, health care leaders, clinicians, regulators, purchasers, and others. In this comprehensive volume the committee offers: A set of performance expectations for the 21st century health care system. A set of 10 new rules to guide patient-clinician relationships. A suggested organizing framework to better align the incentives inherent in payment and accountability with improvements in quality. Key steps to promote evidence-based practice and strengthen clinical information systems. Analyzing health care organizations as complex systems, Crossing the Quality Chasm also documents the causes of the quality gap, identifies current practices that impede quality care, and explores how systems approaches can be used to implement change. |
| examples of workflow analysis in healthcare: Engineering a Learning Healthcare System National Academy of Engineering, Institute of Medicine, 2011-07-14 Improving our nation's healthcare system is a challenge which, because of its scale and complexity, requires a creative approach and input from many different fields of expertise. Lessons from engineering have the potential to improve both the efficiency and quality of healthcare delivery. The fundamental notion of a high-performing healthcare system-one that increasingly is more effective, more efficient, safer, and higher quality-is rooted in continuous improvement principles that medicine shares with engineering. As part of its Learning Health System series of workshops, the Institute of Medicine's Roundtable on Value and Science-Driven Health Care and the National Academy of Engineering, hosted a workshop on lessons from systems and operations engineering that could be applied to health care. Building on previous work done in this area the workshop convened leading engineering practitioners, health professionals, and scholars to explore how the field might learn from and apply systems engineering principles in the design of a learning healthcare system. Engineering a Learning Healthcare System: A Look at the Future: Workshop Summary focuses on current major healthcare system challenges and what the field of engineering has to offer in the redesign of the system toward a learning healthcare system. |
| examples of workflow analysis in healthcare: Fundamentals of Clinical Data Science Pieter Kubben, Michel Dumontier, Andre Dekker, 2018-12-21 This open access book comprehensively covers the fundamentals of clinical data science, focusing on data collection, modelling and clinical applications. Topics covered in the first section on data collection include: data sources, data at scale (big data), data stewardship (FAIR data) and related privacy concerns. Aspects of predictive modelling using techniques such as classification, regression or clustering, and prediction model validation will be covered in the second section. The third section covers aspects of (mobile) clinical decision support systems, operational excellence and value-based healthcare. Fundamentals of Clinical Data Science is an essential resource for healthcare professionals and IT consultants intending to develop and refine their skills in personalized medicine, using solutions based on large datasets from electronic health records or telemonitoring programmes. The book’s promise is “no math, no code”and will explain the topics in a style that is optimized for a healthcare audience. |
| examples of workflow analysis in healthcare: Improving Healthcare Quality in Europe Characteristics, Effectiveness and Implementation of Different Strategies OECD, World Health Organization, 2019-10-17 This volume, developed by the Observatory together with OECD, provides an overall conceptual framework for understanding and applying strategies aimed at improving quality of care. Crucially, it summarizes available evidence on different quality strategies and provides recommendations for their implementation. This book is intended to help policy-makers to understand concepts of quality and to support them to evaluate single strategies and combinations of strategies. |
| examples of workflow analysis in healthcare: Job and Work Analysis Michael T. Brannick, Edward L. Levine, Frederick P. Morgeson, 2007-02-15 Thoroughly updated and revised, this Second Edition is the only book currently on the market to present the most important and commonly used methods in human resource management in such detail. The authors clearly outline how organizations can create programs to improve hiring and training, make jobs safer, provide a satisfying work environment, and help employees to work smarter. Throughout, they provide practical tips on how to conduct a job analysis, often offering anecdotes from their own experiences. |
| examples of workflow analysis in healthcare: Handbook of Human Factors and Ergonomics in Health Care and Patient Safety Pascale Carayon, 2016-04-19 The first edition of Handbook of Human Factors and Ergonomics in Health Care and Patient Safety took the medical and ergonomics communities by storm with in-depth coverage of human factors and ergonomics research, concepts, theories, models, methods, and interventions and how they can be applied in health care. Other books focus on particular human |
| examples of workflow analysis in healthcare: Lean Healthcare Systems Engineering for Clinical Environments Bohdan Oppenheim, 2021-05-24 It has been almost 20 years since the Institute of Medicine released the seminal report titled, Crossing the Quality Chasm. In it, the IoM identified six domains of care quality (safe, timely, effective, efficient, equitable, and patient-centric) and noted a huge gap between the current state and the desired state. Although this report received a great deal of attention, sadly there has been little progress in these areas. In the U.S., healthcare still has huge disparities, is inefficient, and is fragmented with delays in care that are often unsafe. Most U.S. citizens are expected to suffer from a diagnostic error sometime during their lifetime, not receive a large fraction of recommended care, and pay for one of the most expensive systems in the world. Much has been written about quality improvement over the years but many prominent quality and safety experts. Yet progress has been slow. Some have called on the healthcare professions to look outside of healthcare to other industries using examples in nuclear power and airlines for safety, the hotel and entertainment industry for a ‘customer’ focus, and the automotive industry, particularly Toyota for efficiency (Lean). This book by Dr. Oppenheim on lean healthcare systems engineering (LHSE) is a fresh approach that brings forth concepts that systems engineers have used in huge national defense projects. What’s unique in this book is that these powerful system engineering tools are modified to be able to address smaller sized healthcare problems that still involve similar problems in fragmentation and poor communication and coordination. This book is an invaluable reference for a new powerful process named Lean Healthcare Systems Engineering (LHSE) for managing workflow and care improvement projects in all clinical environments. The book applies to ambulatory clinics and hospitals of all types including operating rooms, emergency departments, and ancillary departments, clinical and imaging laboratories, pharmacies, and population health. The book presents a generic rigorous but not mathematical step-by-step process of integrated healthcare, systems engineering and Lean. The book also contains the first major product created with the LHSE process, namely tabularized summaries of representative projects in healthcare delivery applications, called Lean Enablers for Healthcare Projects. Each full-page enabler table lists the challenges and wastes, powerful improvement goals, risks, and expected benefits, and some useful descriptions of the healthcare system of interest. The book provides user-friendly solutions to major problems in healthcare delivery operations in all clinical environments, addressing fragmentation, wastes, wrong incentives, ad-hoc and stove-piped management, lack of optimized processes, hierarchy gradient, lack of systems thinking, “blaming and shaming culture”, burnout of providers and many others. |
| examples of workflow analysis in healthcare: Informatics for Health Professionals Kathleen Mastrian, Dee McGonigle, 2019-12-19 Informatics for Health Professionals is an excellent resource to provide healthcare students and professionals with the foundational knowledge to integrate informatics principles into practice. |
| examples of workflow analysis in healthcare: Working Minds Beth Crandall, Gary A. Klein, Robert R. Hoffman, 2006-07-07 How to collect data about cognitive processes and events, how to analyze CTA findings, and how to communicate them effectively: a handbook for managers, trainers, systems analysts, market researchers, health professionals, and others. Cognitive Task Analysis (CTA) helps researchers understand how cognitive skills and strategies make it possible for people to act effectively and get things done. CTA can yield information people need—employers faced with personnel issues, market researchers who want to understand the thought processes of consumers, trainers and others who design instructional systems, health care professionals who want to apply lessons learned from errors and accidents, systems analysts developing user specifications, and many other professionals. CTA can show what makes the workplace work—and what keeps it from working as well as it might. Working Minds is a true handbook, offering a set of tools for doing CTA: methods for collecting data about cognitive processes and events, analyzing them, and communicating them effectively. It covers both the why and the how of CTA methods, providing examples, guidance, and stories from the authors' own experiences as CTA practitioners. Because effective use of CTA depends on some conceptual grounding in cognitive theory and research—on knowing what a cognitive perspective can offer—the book also offers an overview of current research on cognition. The book provides detailed guidance for planning and carrying out CTA, with chapters on capturing knowledge and capturing the way people reason. It discusses studying cognition in real-world settings and the challenges of rapidly changing technology. And it describes key issues in applying CTA findings in a variety of fields. Working Minds makes the methodology of CTA accessible and the skills involved attainable. |
| examples of workflow analysis in healthcare: Process Modeling and Management for Healthcare Carlo Combi, Giuseppe Pozzi, Pierangelo Veltri, 2017-11-09 From the Foreword: [This book] provides a comprehensive overview of the fundamental concepts in healthcare process management as well as some advanced topics in the cutting-edge research of the closely related areas. This book is ideal for graduate students and practitioners who want to build the foundations and develop novel contributions in healthcare process modeling and management. --Christopher Yang, Drexel University Process modeling and process management are traversal disciplines which have earned more and more relevance over the last two decades. Several research areas are involved within these disciplines, including database systems, database management, information systems, ERP, operations research, formal languages, and logic. Process Modeling and Management for Healthcare provides the reader with an in-depth analysis of what process modeling and process management techniques can do in healthcare, the major challenges faced, and those challenges remaining to be faced. The book features contributions from leading authors in the field. The book is structured into two parts. Part one covers fundamentals and basic concepts in healthcare. It explores the architecture of a process management environment, the flexibility of a process model, and the compliance of a process model. It also features a real application domain of patients suffering from age-related macular degeneration. Part two of the book includes advanced topics from the leading frontiers of scientific research on process management and healthcare. This section of the book covers software metrics to measure features of the process model as a software artifact. It includes process analysis to discover the formal properties of the process model prior to deploying it in real application domains. Abnormal situations and exceptions, as well as temporal clinical guidelines, are also presented in depth Pro. |
| examples of workflow analysis in healthcare: Healthcare Data Analytics Chandan K. Reddy, Charu C. Aggarwal, 2015-06-23 At the intersection of computer science and healthcare, data analytics has emerged as a promising tool for solving problems across many healthcare-related disciplines. Supplying a comprehensive overview of recent healthcare analytics research, Healthcare Data Analytics provides a clear understanding of the analytical techniques currently available |
| examples of workflow analysis in healthcare: Evidence-Based Practice in Action: Comprehensive Strategies, Tools, and Tips From University of Iowa Hospitals & Clinics, Second Edition Laura Cullen, Kirsten Hanrahan, Michele Farrington, Sharon Tucker, Stephanie Edmonds, 2022-07-27 “Building on extensive real-life experience with EBP, this expert team from University of Iowa Hospitals & Clinics provides vital guidance to clinicians at the cutting edge of care improvement.” –Kathleen R. Stevens, EdD, MS, RN, ANEF, FAAN Castella Endowed Distinguished Professor School of Nursing and Institute for Integration of Medicine & Science (CTSA) University of Texas Health Science Center San Antonio “This new edition is essential for all who want to deliver evidence-based care. Beautifully organized, it is readable, practical, and user-friendly.” –Kathleen C. Buckwalter, PhD, RN, FAAN Professor Emerita, University of Iowa College of Nursing Distinguished Nurse Scientist in Aging, Reynolds Center Oklahoma University Health Sciences Center, College of Nursing “Evidence-Based Practice in Action, Second Edition, will continue to ensure high-quality, evidence-based care is implemented in healthcare systems across the country — and the world. It should also be a well-worn tool in every implementation scientist’s toolkit. –Heather Schacht Reisinger, PhD Professor, Department of Internal Medicine Associate Director for Engagement, Integration and Implementation Institute for Clinical and Translational Science, University of Iowa Translate knowledge, research, and clinical expertise into action. The biggest barrier to effective evidence-based practice (EBP) is the failure to effectively translate available knowledge, research, and clinical expertise into action. This failure is rarely due to lack of information, understanding, or experience. In fact, it usually comes down to a simple lack of tools and absence of a clear plan to integrate EBP into care. Problem solved: Evidence-Based Practice in Action, Second Edition, is a time-tested, application-oriented EBP resource for any EBP process model and is organized based on The Iowa Model Revised: Evidence-Based Practice to Promote Excellence in Health Care. This book offers a proven, detailed plan to help nurses and healthcare professionals promote and achieve EBP implementation, adoption, sustained use. TABLE OF CONTENTS Chapter 1: Identify Triggering Issues/Opportunities Chapter 2: State the Question or Purpose Chapter 3: Is This Topic a Priority? Chapter 4: Form a Team Chapter 5: Assemble, Appraise, and Synthesize Body of Evidence Chapter 6: Is There Sufficient Evidence? Chapter 7: Design and Pilot the Practice Change Chapter 8: Evaluation Chapter 9: Implementation Chapter 10: Is Change Appropriate for Adoption in Practice? Chapter 11: Integrate and Sustain the Practice Change Chapter 12: Disseminate Results Appendix A: The Iowa Model Revised: Evidence-Based Practice to Promote Excellence in Health Care Appendix B: Iowa Implementation for Sustainability Framework Appendix C: Select Evidence-Based Practice Models Appendix D: Glossary |
| examples of workflow analysis in healthcare: Usability Evaluation Handbook for Electronic Health Records Linda Harrington, PhD, DNP, RN-BC, CNS, CPHQ, CENP,CPHIMS,FHIMSS, Craig Harrington, MS, LMSW, CPHIMS, |
| examples of workflow analysis in healthcare: Lean Thinking for Healthcare Nilmini Wickramasinghe, Latif Al-Hakim, Chris Gonzalez, Joseph Tan, 2013-10-04 A growing, aging population; the rise to epidemic proportions of various chronic diseases; competing, often overlapping medical technologies; and of course, skyrocketing costs compounded by waste and inefficiency - these are just a few of the multifarious challenges currently facing healthcare delivery. An unexpected source of solutions is being imported from the manufacturing sector: lean thinking. Lean Principles for Healthcare presents a conceptual framework, management principles, and practical tools for professionals tasked with designing and implementing modern, streamlined healthcare systems or overhauling faulty ones. Focusing on core components such as knowledge management, e-health, patient-centeredness, and collaborative care, chapters illustrate lean concepts in action across specialties (as diverse as nursing, urology, and emergency care) and around the globe. Extended case examples show health systems responding to consumer needs and provider realities with equal efficiency and effectiveness, and improved quality and patient outcomes. Further, contributors tackle the gamut of technological, medical, cultural, and business issues, among them: Initiatives of service-oriented architecture towards performance improvement Adapted lean thinking for emergency departments Lean thinking in dementia care through smart assistive technology Supporting preventive healthcare with persuasive services Value stream mapping for lean healthcare A technology mediated solution to reduce healthcare disparities Geared toward both how lean ideas can be carried out and how they are being used successfully in the real world, Lean Principles for Healthcare not only brings expert knowledge to healthcare managers and health services researchers but to all who have an interest in superior healthcare delivery. |
| examples of workflow analysis in healthcare: Healthcare Analytics for Quality and Performance Improvement Trevor L. Strome, 2013-10-07 Improve patient outcomes, lower costs, reduce fraud—all with healthcare analytics Healthcare Analytics for Quality and Performance Improvement walks your healthcare organization from relying on generic reports and dashboards to developing powerful analytic applications that drive effective decision-making throughout your organization. Renowned healthcare analytics leader Trevor Strome reveals in this groundbreaking volume the true potential of analytics to harness the vast amounts of data being generated in order to improve the decision-making ability of healthcare managers and improvement teams. Examines how technology has impacted healthcare delivery Discusses the challenge facing healthcare organizations: to leverage advances in both clinical and information technology to improve quality and performance while containing costs Explores the tools and techniques to analyze and extract value from healthcare data Demonstrates how the clinical, business, and technology components of healthcare organizations (HCOs) must work together to leverage analytics Other industries are already taking advantage of big data. Healthcare Analytics for Quality and Performance Improvement helps the healthcare industry make the most of the precious data already at its fingertips for long-overdue quality and performance improvement. |
| examples of workflow analysis in healthcare: CT of the Heart U. Joseph Schoepf, 2019-04-01 This book is a comprehensive and richly-illustrated guide to cardiac CT, its current state, applications, and future directions. While the first edition of this text focused on what was then a novel instrument looking for application, this edition comes at a time where a wealth of guideline-driven, robust, and beneficial clinical applications have evolved that are enabled by an enormous and ever growing field of technology. Accordingly, the focus of the text has shifted from a technology-centric to a more patient-centric appraisal. While the specifications and capabilities of the CT system itself remain front and center as the basis for diagnostic success, much of the benefit derived from cardiac CT today comes from avant-garde technologies enabling enhanced visualization, quantitative imaging, and functional assessment, along with exciting deep learning, and artificial intelligence applications. Cardiac CT is no longer a mere tool for non-invasive coronary artery stenosis detection in the chest pain diagnostic algorithms; cardiac CT has proven its value for uses as diverse as personalized cardiovascular risk stratification, prediction, and management, diagnosing lesion-specific ischemia, guiding minimally invasive structural heart disease therapy, and planning cardiovascular surgery, among many others. This second edition is an authoritative guide and reference for both novices and experts in the medical imaging sciences who have an interest in cardiac CT. |
| examples of workflow analysis in healthcare: BPMN Modeling and Reference Guide Stephen A. White, Derek Miers, 2008 Business Process Modeling Notation (BPMN) is a standard, graphical modeling representation for business processes. It provides an easy to use, flow-charting notation that is independent of the implementation environment. An underlying rigor supports the notation-facilitating the translation of business level models into executable models that BPM Suites and workflow engines can understand. Over recent years, BPMN has been widely adopted by Business Process Management (BPM) related products-both the Business Process Analysis and Modeling tool vendors and the BPM Suites. This book is for business users and process modeling practitioners alike. Part I provides an easily understood introduction to the key components of BPMN (put forward in a user-friendly fashion). Starting off with simple models, it progresses into more sophisticated patterns. Exercises help cement comprehension and understanding (with answers available online). Part II provides a detailed and authoritative reference on the precise semantics and capabilities of the standard. |
| examples of workflow analysis in healthcare: Cognitive and Soft Computing Techniques for the Analysis of Healthcare Data Akash Kumar Bhoi, Victor Hugo Costa de Albuquerque, Parvathaneni Naga Srinivasu, Goncalo Marques, 2022-01-22 Cognitive and Soft Computing Techniques for the Analysis of Healthcare Data discusses the insight of data processing applications in various domains through soft computing techniques and enormous advancements in the field. The book focuses on the cross-disciplinary mechanisms and ground-breaking research ideas on novel techniques and data processing approaches in handling structured and unstructured healthcare data. It also gives insight into various information-processing models and many memories associated with it while processing the information for forecasting future trends and decision making. This book is an excellent resource for researchers and professionals who work in the Healthcare Industry, Data Science, and Machine learning. - Focuses on data-centric operations in the Healthcare industry - Provides the latest trends in healthcare data analytics and practical implementation outcomes of the proposed models - Addresses real-time challenges and case studies in the Healthcare industry |
| examples of workflow analysis in healthcare: SAFER Electronic Health Records Dean F. Sittig, Hardeep Singh, 2015-04-14 This important volume provide a one-stop resource on the SAFER Guides along with the guides themselves and information on their use, development, and evaluation. The Safety Assurance Factors for EHR Resilience (SAFER) guides, developed by the editors of this book, identify recommended practices to optimize the safety and safe use of electronic heal |
| examples of workflow analysis in healthcare: Human Computer Interaction in Healthcare Andre W. Kushniruk, |
| examples of workflow analysis in healthcare: Teamwork in Healthcare Michael S. Firstenberg, Stanislaw P. Stawicki, 2021-04-21 One of the most important advances in the delivery of healthcare has been recognition of the need for developing highly functioning multi-disciplinary teams. Such teams, when structured in a cohesive fashion, can function more effectively and efficiently than the sum of their parts. The benefits of teamwork extend from the delivery of care to a single patient to the overall structure and function of entire care delivery systems. Recognizing the value of collaborative approaches for improving all aspects of healthcare delivery and having champions, leaders, structure, function, goals, and accountability are paramount to success, regardless of how defined. Another important pillar of teamwork is excellent communication with clearly defined information flows and cross-verification mechanisms. This book outlines how to work together for shared goals in a complex, diverse, and constantly evolving health care system. |
| examples of workflow analysis in healthcare: ADKAR Jeff Hiatt, 2006 In his first complete text on the ADKAR model, Jeff Hiatt explains the origin of the model and explores what drives each building block of ADKAR. Learn how to build awareness, create desire, develop knowledge, foster ability and reinforce changes in your organization. The ADKAR Model is changing how we think about managing the people side of change, and provides a powerful foundation to help you succeed at change. |
| examples of workflow analysis in healthcare: Digital Supply Networks: Transform Your Supply Chain and Gain Competitive Advantage with Disruptive Technology and Reimagined Processes Amit Sinha, Ednilson Bernardes, Rafael Calderon, Thorsten Wuest, 2020-07-21 Deliver unprecedented customer value and seize your competitive edge with a transformative digital supply network Digital tech has disrupted life and business as we know it, and supply chain management is no exception. But how exactly does digital transformation affect your business? What are the breakthrough technologies and their capabilities you need to know about? How will digital transformation impact skills requirements and work in general? Do you need to completely revamp your understanding of supply chain management? And most importantly: How do you get started? Digital Supply Networks provides clear answers to these and many other questions. Written by an experienced team comprised of Deloitte consultants and leading problem-driven scholars from a premier research university, this expert guide leads you through the process of improving operations building supply networks, increasing revenue, reimagining business models, and providing added value to customers, stakeholders, and society. You’ll learn everything you need to know about: Stages of development, roles, capabilities, and the benefits of DSN Big data analytics including its attributes, security, and authority Machine learning, Artificial Intelligence, Blockchain, robotics, and the Internet of Things Synchronized planning, intelligent supply, and digital product development Vision, attributes, technology, and benefits of smart manufacturing, dynamic logistics, and fulfillment A playbook to guide the digital transformation journey Drawing from real world-experience and problem-driven academic research, the authors provide an in-depth account of the transformation to digitally connected supply networks. They discuss the limitations of traditional supply chains and the underlying capabilities and potential of digitally-enabled supply flows. The chapters burst with expert insights and real-life use cases grounded in tomorrow’s industry needs. Success in today’s hyper-competitive, fast-paced business landscape, characterized by the risk of black swan events, such as the 2020 COVID-19 global pandemic, requires the reimagination and the digitalization of complex demand-supply systems, more collaborative and connected processes, and smarter, more dynamic data-driven decision making―which can only be achieved through a fully integrated Digital Supply Network. |
| examples of workflow analysis in healthcare: Big Data For Dummies Judith S. Hurwitz, Alan Nugent, Fern Halper, Marcia Kaufman, 2013-04-02 Find the right big data solution for your business or organization Big data management is one of the major challenges facing business, industry, and not-for-profit organizations. Data sets such as customer transactions for a mega-retailer, weather patterns monitored by meteorologists, or social network activity can quickly outpace the capacity of traditional data management tools. If you need to develop or manage big data solutions, you'll appreciate how these four experts define, explain, and guide you through this new and often confusing concept. You'll learn what it is, why it matters, and how to choose and implement solutions that work. Effectively managing big data is an issue of growing importance to businesses, not-for-profit organizations, government, and IT professionals Authors are experts in information management, big data, and a variety of solutions Explains big data in detail and discusses how to select and implement a solution, security concerns to consider, data storage and presentation issues, analytics, and much more Provides essential information in a no-nonsense, easy-to-understand style that is empowering Big Data For Dummies cuts through the confusion and helps you take charge of big data solutions for your organization. |
| examples of workflow analysis in healthcare: Taking Action Against Clinician Burnout National Academies of Sciences, Engineering, and Medicine, National Academy of Medicine, Committee on Systems Approaches to Improve Patient Care by Supporting Clinician Well-Being, 2020-01-02 Patient-centered, high-quality health care relies on the well-being, health, and safety of health care clinicians. However, alarmingly high rates of clinician burnout in the United States are detrimental to the quality of care being provided, harmful to individuals in the workforce, and costly. It is important to take a systemic approach to address burnout that focuses on the structure, organization, and culture of health care. Taking Action Against Clinician Burnout: A Systems Approach to Professional Well-Being builds upon two groundbreaking reports from the past twenty years, To Err Is Human: Building a Safer Health System and Crossing the Quality Chasm: A New Health System for the 21st Century, which both called attention to the issues around patient safety and quality of care. This report explores the extent, consequences, and contributing factors of clinician burnout and provides a framework for a systems approach to clinician burnout and professional well-being, a research agenda to advance clinician well-being, and recommendations for the field. |
| examples of workflow analysis in healthcare: Health Informatics: Practical Guide for Healthcare and Information Technology Professionals (Fifth Edition) Robert E Hoyt, Nora Bailey, Ann Yoshihashi, 2012 Health Informatics (HI) focuses on the application of information technology (IT) to the field of medicine to improve individual and population healthcare delivery, education and research. This extensively updated fifth edition reflects the current knowledge in Health Informatics and provides learning objectives, key points, case studies and references. Topics include: HI Overview; Healthcare Data, Information, and Knowledge; Electronic Health Records, Practice Management Systems; Health Information Exchange; Data Standards; Architectures of Information Systems;Health Information Privacy and Security; HI Ethics; Consumer HI; Mobile Technology; Online Medical Resources; Search Engines; Evidence-Based Medicine and Clinical Practice Guidelines; Disease Management and Registries; Quality Improvement Strategies; Patient Safety; Electronic Prescribing; Telemedicine; Picture Archiving and Communication Systems; Bioinformatics; Public HI; E-Research. Available as a printed copy and E-book. |
| examples of workflow analysis in healthcare: Improving Outcomes with Clinical Decision Support Jerome A. Osheroff, MD, FACP, FACMI, Jonathan M. T, 2012 |
| examples of workflow analysis in healthcare: Better EHR Jiajie Zhang (Professor of biomedical informatics), Muhammad Walji, 2014-10-01 Electronic Health Records (EHR) offer great potential to increase healthcare efficiency, improve patient safety, and reduce health costs. The adoption of EHRs among office-based physicians in the US has increased from 20% ten years ago to over 80% in 2014. Among acute care hospitals in US, the adoption rate today is approaching 100%. Finding relevant patient information in electronic health records' (EHRs) large datasets is difficult, especially when organized only by data type and time. Automated clinical summarization creates condition-specific displays, promising improved clinician efficiency. However, automated summarization requires new kinds of clinical knowledge (e.g., problem-medication relationships). |
Examples - Apache ECharts
Apache ECharts，一款基于JavaScript的数据可视化图表库，提供直观，生动，可交互，可个性化定制的数据可视化图表。
Examples - Apache ECharts
Examples; Resources. Spread Sheet Tool; Theme Builder; Cheat Sheet; More Resources; Community. Events; …
Examples - Apache ECharts
Examples; Resources. Spread Sheet Tool; Theme Builder; Cheat Sheet; More Resources; Community. Events; Committers; Mailing List; How to Contribute; Dependencies; Code …
Apache ECharts
ECharts: A Declarative Framework for Rapid Construction of Web-based Visualization. 如果您在科研项目、产品、学术论文、技术报告、新闻报告、教育、专利以及其他相关活动中使用了 Apache …
Events - Apache ECharts
Examples; Resources. Spread Sheet Tool; Theme Builder; Cheat Sheet; More Resources; Community. Events; …
Examples - Apache ECharts
Apache ECharts，一款基于JavaScript的数据可视化图表库，提供直观，生动，可交互，可个性化定制的数据可视化图表。
Examples - Apache ECharts
Examples; Resources. Spread Sheet Tool; Theme Builder; Cheat Sheet; More Resources; Community. Events; Committers; Mailing List; How to Contribute; Dependencies; Code …
Examples - Apache ECharts
Examples; Resources. Spread Sheet Tool; Theme Builder; Cheat Sheet; More Resources; Community. Events; Committers; Mailing List; How to Contribute; Dependencies; Code …
Apache ECharts
ECharts: A Declarative Framework for Rapid Construction of Web-based Visualization. 如果您在科研项目、产品、学术论文、技术报告、新闻报告、教育、专利以及其他相关活动中使用了 …
Events - Apache ECharts
Examples; Resources. Spread Sheet Tool; Theme Builder; Cheat Sheet; More Resources; Community. Events; Committers; Mailing List; How to Contribute; Dependencies; Code …
