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Exploiting the rich information found in electronic health records (EHRs) can facilitate better medical research and improve the quality of medical practice. Until now, a trivial amount of research has been published on the challenges of leveraging this information. Addressing these challenges, Information Discovery on Electronic Health Records exp
Developed as a comprehensive learning resource, this hands-on course for Integrated Electronic Health Records is offered through McGraw Hill's Connect. Connect uses the latest technology and learning techniques to better connect professors to their students, and students to the information and customized resources they need to master a subject. Both the worktext and the online course include coverage of EHRclinic, an education-based EHR solution for online electronic health records, practice management applications, and interoperable physician-based functionality. EHRclinic will be used to demonstrate the key applications of electronic health records. Attention is paid to providing the "why"behind each task, so that the reader can accumulate transferable skills. The coverage is focused on using an EHR program in a doctor's office, while providing additional information on how tasks might also be completed in a hospital setting.
This book trains the next generation of scientists representing different disciplines to leverage the data generated during routine patient care. It formulates a more complete lexicon of evidence-based recommendations and support shared, ethical decision making by doctors with their patients. Diagnostic and therapeutic technologies continue to evolve rapidly, and both individual practitioners and clinical teams face increasingly complex ethical decisions. Unfortunately, the current state of medical knowledge does not provide the guidance to make the majority of clinical decisions on the basis of evidence. The present research infrastructure is inefficient and frequently produces unreliable results that cannot be replicated. Even randomized controlled trials (RCTs), the traditional gold standards of the research reliability hierarchy, are not without limitations. They can be costly, labor intensive, and slow, and can return results that are seldom generalizable to every patient population. Furthermore, many pertinent but unresolved clinical and medical systems issues do not seem to have attracted the interest of the research enterprise, which has come to focus instead on cellular and molecular investigations and single-agent (e.g., a drug or device) effects. For clinicians, the end result is a bit of a “data desert” when it comes to making decisions. The new research infrastructure proposed in this book will help the medical profession to make ethically sound and well informed decisions for their patients.
"This book discusses the elements of EHR implementation in a clear, chronological format from planning to execution. Along the way, readers receive a solid background in EHR history, trends, and common pitfalls and gain the skills they will need for a successful implementation."
The purpose of the book is to provide an overview of clinical research (types), activities, and areas where informatics and IT could fit into various activities and business practices. This book will introduce and apply informatics concepts only as they have particular relevance to clinical research settings.
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.
Most industries have plunged into data automation, but health care organizations have lagged in moving patients' medical records from paper to computers. In its first edition, this book presented a blueprint for introducing the computer-based patient record (CPR). The revised edition adds new information to the original book. One section describes recent developments, including the creation of a computer-based patient record institute. An international chapter highlights what is new in this still-emerging technology. An expert committee explores the potential of machine-readable CPRs to improve diagnostic and care decisions, provide a database for policymaking, and much more, addressing these key questions: Who uses patient records? What technology is available and what further research is necessary to meet users' needs? What should government, medical organizations, and others do to make the transition to CPRs? The volume also explores such issues as privacy and confidentiality, costs, the need for training, legal barriers to CPRs, and other key topics.
Revised and updated to include the latest trends and applications in electronic health records, this fifth edition of Electronic Health Records: A Practical Guide for Professionals and Organizations offers step-by-step guidelines for developing and implementing EHR strategies for healthcare organizations. New to This Edition: 2013 Update Addresses the expanded interaction among HIM professionals and system users, IT professionals, vendors, patients and their family, and others. Additions and updates include: Meaningful use (MU) definitions, objectives, standards, and measures Digital appendix on meaningful use stages ONC EHR certification programs Vision for health reform and enhanced HIPAA administrative simplification requirements under ACA Workflow, thoughtflow, and process management Strategies for managing e-discovery and the legal health record in an EHR environment Tools for cost-benefit analysis and benefits realization for EHR Update on hospital resources for core EHR components, medical device integration, and beyond Update on physician practice resources Final Rule update on ARRA/HITECH privacy and security guidelines Update on risk analysis and medical identity theft Practical uses of SNOMED-encoded data Expanded coverage on HIE, PHRs, and consumer empowerment New chapter on specialty-specific EHRs New and expanded downloadable resources Instructor access to online EHR simulation modules
The use of Electronic Health Records (EHR)/Electronic Medical Records (EMR) data is becoming more prevalent for research. However, analysis of this type of data has many unique complications due to how they are collected, processed and types of questions that can be answered. This book covers many important topics related to using EHR/EMR data for research including data extraction, cleaning, processing, analysis, inference, and predictions based on many years of practical experience of the authors. The book carefully evaluates and compares the standard statistical models and approaches with those of machine learning and deep learning methods and reports the unbiased comparison results for these methods in predicting clinical outcomes based on the EHR data. Key Features: Written based on hands-on experience of contributors from multidisciplinary EHR research projects, which include methods and approaches from statistics, computing, informatics, data science and clinical/epidemiological domains. Documents the detailed experience on EHR data extraction, cleaning and preparation Provides a broad view of statistical approaches and machine learning prediction models to deal with the challenges and limitations of EHR data. Considers the complete cycle of EHR data analysis. The use of EHR/EMR analysis requires close collaborations between statisticians, informaticians, data scientists and clinical/epidemiological investigators. This book reflects that multidisciplinary perspective.
The authors of this practical guide share the expertise they have gleaned from helping more than 100 hospitals transition from the world of paper to the world of information technology. They provide advice both for healthcare executives involved in implementing a new system and for those who wish to optimize their existing system. This book is a comprehensive reference for the design, implementation, and optimization of electronic health records (EHRs). The authors offer a detailed road map for avoiding common pitfalls during conversion and achieving higher-quality care after system implementation. A glossary of important terms and references to additional resources are also included in the book. Key topics covered include: Budgeting for the design and implementation of an EHR system Selecting and deploying new hardware and software Organizing your governance model for EHR implementation Training clinical staff on the new EHR system and procedures Ensuring compliance with HIPAA and other privacy measures Managing formularies, order sets, and documentation in the changing electronic world