Clinical Decision Support Books

Click Get Book Button To Download or read online Clinical Decision Support books, Available in PDF, ePub, Tuebl and Kindle. This site is like a library, Use search box in the widget to get ebook that you want.

Clinical Decision Support


Clinical Decision Support
  • Author : Robert A. Greenes
  • Publisher : Elsevier
  • Release : 2011-04-28
  • ISBN : 0080467695
  • Language : En, Es, Fr & De
GET BOOK

This book examines the nature of medical knowledge, how it is obtained, and how it can be used for decision support. It provides complete coverage of computational approaches to clinical decision-making. Chapters discuss data integration into healthcare information systems and delivery to point of care for providers, as well as facilitation of direct to consumer access. A case study section highlights critical lessons learned, while another portion of the work examines biostatistical methods including data mining, predictive modelling, and analysis. This book additionally addresses organizational, technical, and business challenges in order to successfully implement a computer-aided decision-making support system in healthcare delivery.

Fundamentals of Clinical Data Science


Fundamentals of Clinical Data Science
  • Author : Pieter Kubben
  • Publisher : Springer
  • Release : 2018-12-21
  • ISBN : 9783319997131
  • Language : En, Es, Fr & De
GET BOOK

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.

Clinical Decision Support Systems


Clinical Decision Support Systems
  • Author : Eta S. Berner
  • Publisher : Springer Science & Business Media
  • Release : 2013-06-29
  • ISBN : 9781475739039
  • Language : En, Es, Fr & De
GET BOOK

Written by nationally and internationally recognised experts on the design, evaluation and application of such systems, this book examines the impact of practitioner and patient use of computer-based diagnostic tools. It serves simultaneously as a resource book on diagnostic systems for informatics specialists; a textbook for teachers or students in health or medical informatics training programs; and as a comprehensive introduction for clinicians, with or without expertise in the applications of computers in medicine, who are interested in learning about current developments in computer-based diagnostic systems. Designed for a broad range of clinicians in need of decision support.

Improving Outcomes with Clinical Decision Support


Improving Outcomes with Clinical Decision Support
  • Author : Jerome. A Osheroff
  • Publisher : CRC Press
  • Release : 2021-02-28
  • ISBN : 9781498757461
  • Language : En, Es, Fr & De
GET BOOK

Winner of the 2012 HIMSS Book of the Year Award! Co-published by HIMSS, the Scottsdale Institute, AMIA, AMDIS and SHM, this second edition of the authoritative guide to CDS implementation has been substantially enhanced with expanded and updated guidance on using CDS interventions to improve care delivery and outcomes. This edition has been reorganized into parts that help readers set up (or refine) a successful CDS program in a hospital, health system or physician practice; and configure and launch specific CDS interventions. Two detailed case studies illustrate how a "real-life" CDS program and specific CDS interventions might evolve in a hypothetical community hospital and small physician practice. This updated edition includes enhanced worksheets--with sample data--that help readers to document and use information needed for their CDS program and interventions. Sections in each chapter present considerations for health IT software suppliers to effectively support their CDS implementer clients.

Reinventing Clinical Decision Support


Reinventing Clinical Decision Support
  • Author : Paul Cerrato
  • Publisher : Taylor & Francis
  • Release : 2020-01-15
  • ISBN : 9781000055559
  • Language : En, Es, Fr & De
GET BOOK

This book takes an in-depth look at the emerging technologies that are transforming the way clinicians manage patients, while at the same time emphasizing that the best practitioners use both artificial and human intelligence to make decisions. AI and machine learning are explored at length, with plain clinical English explanations of convolutional neural networks, back propagation, and digital image analysis. Real-world examples of how these tools are being employed are also discussed, including their value in diagnosing diabetic retinopathy, melanoma, breast cancer, cancer metastasis, and colorectal cancer, as well as in managing severe sepsis. With all the enthusiasm about AI and machine learning, it was also necessary to outline some of criticisms, obstacles, and limitations of these new tools. Among the criticisms discussed: the relative lack of hard scientific evidence supporting some of the latest algorithms and the so-called black box problem. A chapter on data analytics takes a deep dive into new ways to conduct subgroup analysis and how it’s forcing healthcare executives to rethink the way they apply the results of large clinical trials to everyday medical practice. This re-evaluation is slowly affecting the way diabetes, heart disease, hypertension, and cancer are treated. The research discussed also suggests that data analytics will impact emergency medicine, medication management, and healthcare costs. An examination of the diagnostic reasoning process itself looks at how diagnostic errors are measured, what technological and cognitive errors are to blame, and what solutions are most likely to improve the process. It explores Type 1 and Type 2 reasoning methods; cognitive mistakes like availability bias, affective bias, and anchoring; and potential solutions such as the Human Diagnosis Project. Finally, the book explores the role of systems biology and precision medicine in clinical decision support and provides several case studies of how next generation AI is transforming patient care.