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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.
Commissioned by the Department of Health and Human Services, Key Capabilities of an Electronic Health Record System provides guidance on the most significant care delivery-related capabilities of electronic health record (EHR) systems. There is a great deal of interest in both the public and private sectors in encouraging all health care providers to migrate from paper-based health records to a system that stores health information electronically and employs computer-aided decision support systems. In part, this interest is due to a growing recognition that a stronger information technology infrastructure is integral to addressing national concerns such as the need to improve the safety and the quality of health care, rising health care costs, and matters of homeland security related to the health sector. Key Capabilities of an Electronic Health Record System provides a set of basic functionalities that an EHR system must employ to promote patient safety, including detailed patient data (e.g., diagnoses, allergies, laboratory results), as well as decision-support capabilities (e.g., the ability to alert providers to potential drug-drug interactions). The book examines care delivery functions, such as database management and the use of health care data standards to better advance the safety, quality, and efficiency of health care in the United States.
One of the hottest political issues today concerns ways to improve national healthcare systems without incurring further costs. An extensive study by the Institute of Medicine (IOM) in the United States formally reported that computer-based patient records are absolutely necessary to help contain the cost explosion in health care. The information obtained from experts, the studies conducted, and the conclusions that went into the IOM's report have now been collected in Aspects of the Computer-Based Patient Record. A large portion of the volume discusses the state-of-the-art in existing computer-based systems as well as the essential needs which must be addressed by future computer-based patients' records. A final section in the book discusses implementation strategies for changing to the electronic system and practical issues: Who will bear the final cost? How and when will healthcare providers who use the system be trained? This volume contains the concise, valuable information which hospital administrators, hospital systems designers, third-party payer groups, and medical technology providers will need if they hope to successfully transit to hospital systems which use a computer-based patient record.
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.
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.
The practice of modern medicine and biomedical research requires sophisticated information technologies with which to manage patient information, plan diagnostic procedures, interpret laboratory results, and carry out investigations. Biomedical Informatics provides both a conceptual framework and a practical inspiration for this swiftly emerging scientific discipline at the intersection of computer science, decision science, information science, cognitive science, and biomedicine. Now revised and in its third edition, this text meets the growing demand by practitioners, researchers, and students for a comprehensive introduction to key topics in the field. Authored by leaders in medical informatics and extensively tested in their courses, the chapters in this volume constitute an effective textbook for students of medical informatics and its areas of application. The book is also a useful reference work for individual readers needing to understand the role that computers can play in the provision of clinical services and the pursuit of biological questions. The volume is organized so as first to explain basic concepts and then to illustrate them with specific systems and technologies.
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.
In-depth study of internet-enhanced healthcare services Complete and thorough survey of the most promising e-health technologies Presents numerous real world examples Emphasis on international health-informatics topics, such as better access of states / countries to modern e-health technologies developed by leading centers
Discover How Electronic Health Records Are Built to Drive the Next Generation of Healthcare Delivery The increased role of IT in the healthcare sector has led to the coining of a new phrase "health informatics," which deals with the use of IT for better healthcare services. Health informatics applications often involve maintaining the health records of individuals, in digital form, which is referred to as an Electronic Health Record (EHR). Building and implementing an EHR infrastructure requires an understanding of healthcare standards, coding systems, and frameworks. This book provides an overview of different health informatics resources and artifacts that underlie the design and development of interoperable healthcare systems and applications. Electronic Health Record: Standards, Coding Systems, Frameworks, and Infrastructures compiles, for the first time, study and analysis results that EHR professionals previously had to gather from multiple sources. It benefits readers by giving them an understanding of what roles a particular healthcare standard, code, or framework plays in EHR design and overall IT-enabled healthcare services along with the issues involved. This book on Electronic Health Record: Offers the most comprehensive coverage of available EHR Standards including ISO, European Union Standards, and national initiatives by Sweden, the Netherlands, Canada, Australia, and many others Provides assessment of existing standards Includes a glossary of frequently used terms in the area of EHR Contains numerous diagrams and illustrations to facilitate comprehension Discusses security and reliability of data
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.