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from office, hospital and community settings. This book is the companion volume to Learning from Medical Errors: Clinical Problems which;
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Is the reporting of medical errors changing? This book shows with real cases from health care and beyond that most errors come from flaws;
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people die from the consequences of mistreatment. The intensive care units record 1.7 medical errors per patient and day. The most affected;
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error occurs. Potential medical errors are described and discussed in a clinical case-based learning format to effectively illustrate the;
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Medical Device Use Error: Root Cause Analysis offers practical guidance on how to methodically discover and explain the root cause of a use;
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and how medical error can happen. The lifelong process of learning that is a medical career requires healthcare workers to find a way to live;
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illustrate patient safety ethics: medical malpractice suits. Providing professional perspective with insights from prominent patient safety;
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Learning by erring Is it possible to learn from your mistakes? While there is evidence to the positive, there is also evidence suggesting;
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The evidence-based medicine movement is gaining influence in many medical specialties. This issue will cover topics from patient safety;
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categories including, but not limited to, medical error, hospital-acquired infections, medication errors, deaths from misdiagnosis, deaths from;
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Providing a clear explanation of the relevant medical science behind the individual medical specialties, Basic Science for Core Medical;
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Safe is the story of the rise of the patient-safety movement - and how an epidemic of medical errors was derived from a reality that didn't;
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Learning from professional errors in social work is vital for successful reflective practice. This important book presents a theoretical;
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The detection, reporting, measurement, and minimization of medical errors and harms is now a core requirement in clinical organizations;
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and Expert Label Synthesis, LABELS 2016, and the Second International Workshop on Deep Learning in Medical Image Analysis, DLMIA 2016. The 28;
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Based on the IOM's estimate of 44,000 deaths annually, medical errors rank as the eighth leading cause of death in the U.S. Clearly medical;
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Based on the IOM's estimate of 44,000 deaths annually, medical errors rank as the eighth leading cause of death in the U.S. Clearly medical;
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This book constitutes the proceedings of the 10th International Workshop on Machine Learning in Medical Imaging, MLMI 2019, held;
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Now revised and updated-the landmark patient safety primer written by the world's leading authorities Medical errors are the;
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Experts estimate that as many as 98,000 people die in any given year from medical errors that occur in hospitals. That's more than die from;
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Some of the most important and best lessons in a doctor s career are learnt from mistakes. However, an awareness of the common causes;
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This book constitutes the refereed proceedings of the 5th International Workshop on Machine Learning in Medical Imaging, MLMI 2014, held;
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This book constitutes the refereed proceedings of the First International Workshop on Graph Learning in Medical Imaging, GLMI 2019, held;
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This book constitutes the proceedings of the 6th International Workshop on Machine Learning in Medical Imaging, MLMI 2015, held;
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healthcare. Medical data from different sources can also be analyzed via Artificial Intelligence techniques for more effective results.;
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The mistakes children make in mathematics are usually not just 'mistakes' - they are often intelligent generalizations from previous;
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, insurance, and billing. In addition, effective learning tools help you master medical and pharmaceutical terminology and avoid today's most common;
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