Intended for family physicians and others in primary care delivery. Compatible with International classification of diseases, 9th ed.

In response to a request by the Health Care Financing Administration (HCFA), the Institute of Medicine proposed a study to examine definitions of serious or complex medical conditions and related issues. A seven-member committee was appointed to address these issues. Throughout the course of this study, the committee has been aware of the fact that the topic addressed by this report concerns one of the most critical issues confronting HCFA, health care plans and providers, and patients today. The Medicare+Choice regulations focus on the most vulnerable populations in need of medical care and other services-those with serious or complex medical conditions. Caring for these highly vulnerable populations poses a number of challenges. The committee believes, however, that the current state of clinical and research literature does not adequately address all of the challenges and issues relevant to the identification and care of these patients.

Part of the highly respected Requisites series, Radiology Noninterpretive Skills, by Drs. Hani H. Abujudeh and Michael A. Bruno, is a single-volume source of timely information on all of the non-imaging aspects of radiology such as quality and safety, ethics and professionalism, and error management in radiology. Residents and radiologists preparing for the boards and recertification will find this book invaluable, as well as those practitioners wanting to broaden their knowledge and skills in this increasingly important area. - Offers a readable and concise introduction to the essential noninterpretive skills as defined by the IOM, ACR, and other national organizations. - Covers what you need to know about quality and safety; leadership and management; health economics; legal, business, ethics and professionalism; statistical tools; error reporting and prevention; evidence-based imaging; health IT and internet applications; "Image Wisely" and "Imaging 3.0" ACR initiatives; legal issues and malpractice; current and future payment models in radiology; and much more. - Summarizes key information with numerous outlines, tables, ''pearls,'' and boxed material for easy reference. - Provides comprehensive coverage of key "milestones" in training identified by the Accreditation Council for Graduate Medical Education (ACGME). - Fills an important gap for those preparing for the current MOC and ABR exams, covering the many topics touched upon in a major section of the examinations. - Brings together in one source the experience of leading national experts and a select team of expert contributors. - Expert ConsultTM eBook version included with purchase. This enhanced eBook experience allows you to search all of the text, figures, Q&As, and references from the book on a variety of devices.

Reprint of the original, first published in 1872. The publishing house Anatiposi publishes historical books as reprints. Due to their age, these books may have missing pages or inferior quality. Our aim is to preserve these books and make them available to the public so that they do not get lost.

This open access book describes the results of natural language processing and machine learning methods applied to clinical text from electronic patient records. It is divided into twelve chapters. Chapters 1-4 discuss the history and background of the original paper-based patient records, their purpose, and how they are written and structured. These initial chapters do not require any technical or medical background knowledge. The remaining eight chapters are more technical in nature and describe various medical classifications and terminologies such as ICD diagnosis codes, SNOMED CT, MeSH, UMLS, and ATC. Chapters 5-10 cover basic tools for natural language processing and information retrieval, and how to apply them to clinical text. The difference between rule-based and machine learning-based methods, as well as between supervised and unsupervised machine learning methods, are also explained. Next, ethical concerns regarding the use of sensitive patient records for research purposes are discussed, including methods for de-identifying electronic patient records and safely storing patient records. The book’s closing chapters present a number of applications in clinical text mining and summarise the lessons learned from the previous chapters. The book provides a comprehensive overview of technical issues arising in clinical text mining, and offers a valuable guide for advanced students in health informatics, computational linguistics, and information retrieval, and for researchers entering these fields.

Reprint of the original, first published in 1874.