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This money saving package will include: Medical Coding Online for Step-by-Step Medical Coding 2010 (User Guide and Access Code) Step-by-Step Medical Coding 2010 Textbook 2010 ICD-9-CM for Hospitals, Volumes 1, 2 & 3 Standard Edition 2010 HCPCS Level II Standard Edition 2010 CPT Standard Edition
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This money-saving package include: Medical Coding Online for Step-by-Step Medical Coding 2011 (User Guide and Access Code) Step-by-Step Medical Coding 2011 Edition Textbook Step-by-Step Medical Coding 2011 Edition Workbook 2012 ICD-9-CM for Hospitals, Volumes 1, 2 & 3 Standard Edition 2011 HCPCS Level II Standard Edition 2011 CPT Standard Edition
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.
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.
This book examines how nine different health systems--U.S. Medicare, Australia, Thailand, Kyrgyz Republic, Germany, Estonia, Croatia, China (Beijing) and the Russian Federation--have transitioned to using case-based payments, and especially diagnosis-related groups (DRGs), as part of their provider payment mix for hospital care. It sheds light on why particular technical design choices were made, what enabling investments were pertinent, and what broader political and institutional issues needed to be considered. The strategies used to phase in DRG payment receive special attention. These nine systems have been selected because they represent a variety of different approaches and experiences in DRG transition. They include the innovators who pioneered DRG payment systems (namely the United States and Australia), mature systems (such as Thailand, Germany, and Estonia), and countries where DRG payments were only introduced within the past decade (such as the Russian Federation and China). Each system is examined in detail as a separate case study, with a synthesis distilling the cross-cutting lessons learned. This book should be helpful to those working on health systems that are considering introducing, or are in the early stages of introducing, DRG-based payments into their provider payment mix. It will enhance the reader's understanding of how other countries (or systems) have made that transition, give a sense of the decisions that lie ahead, and offer options that can be considered. It will also be useful to those working in health systems that already include DRG payments in the payment mix but have not yet achieved the anticipated results.
This money saving package will include: Medical Coding Online for Step-by-Step Medical Coding 2010 (User Guide and Access Code) Step-by-Step Medical Coding 2010 Textbook Step-by-Step Medical Coding 2010 Workbook 2010 ICD-9-CM, Volumes 1, 2 & 3 Professional Edition 2010 HCPCS Level II Professional Edition 2010 CPT Professional Edition
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