First published in 1989. Routledge is an imprint of Taylor & Francis, an informa company.

First Published in 1989. Routledge is an imprint of Taylor & Francis, an informa company.

This handbook provides library and information professionals with the information they need to undertake research projects in the workplace in order to inform their own practice and improve service delivery. Whether you are a complete novice or have experience of undertaking evaluations, audits or research, this book will guide you step-by-step through the key phases of planning, doing and disseminating research. The text is divided into three sections: • Part 1: Getting started introduces the concepts, ethics and planning stages. • Part 2: Doing research, evaluation and audit explores the fundamentals of projects, including the literature review, qualitative and quantitative research methods, data analysis and research tools. • Part 3: Impact of research, evaluation and audit guides you through writing up your project, putting the results of your project findings into practice and dissemination to the wider community. Written by academics and practitioners from a diverse range of sectors throughout the world, the book offers a thorough but common sense approach. Each chapter is structured to begin with a comprehensive introduction to a discrete topic area complemented with case studies drawn from a broad range of LIS contexts to illustrate the issues raised and provide transferable lessons to your own context. Whatever your experience, this book will support your project development and explain how evidence-based library and information practice is relevant to you. Readership: This is the essential handbook for any librarian or information professional who wants to undertake research in the workplace in order to inform their own practice and the wider evidence base for library and information science. It’s also a useful guide for undergraduate and postgraduate LIS students undertaking their final year research project.

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.

Recent scandals and controversies, such as data fabrication in federally funded science, data manipulation and distortion in private industry, and human embryonic stem cell research, illustrate the importance of ethics in science. Responsible Conduct of Research, now in a completely updated second edition, provides an introduction to the social, ethical, and legal issues facing scientists today.

Clinical audit is at the heart of clinical governance. Provides the mechanisms for reviewing the quality of everyday care provided to patients with common conditions like asthma or diabetes. Builds on a long history of doctors, nurses and other healthcare professionals reviewing case notes and seeking ways to serve their patients better. Addresses the quality issues systematically and explicitly, providing reliable information. Can confirm the quality of clinical services and highlight the need for improvement. Provides clear statements of principle about clinical audit in the NHS.