Clinical Decision Support: The Road Ahead

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Overview

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.

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Product Details

  • ISBN-13: 9780123693778
  • Publisher: Elsevier Science
  • Publication date: 11/24/2006
  • Edition description: New Edition
  • Pages: 544
  • Product dimensions: 7.50 (w) x 10.30 (h) x 1.50 (d)

Table of Contents

Introduction: Clinical decision support
What it is and why important
A brief history of the field
Types of computer-aided decision making

Case studies
Regenstrief experience
Brigham experience
LDS HELP experience
Lessons learned, summary

Where are we now?
Penetration
Limitations
New motivations and interest

Where does the knowledge come from?
Expert knowledge
Data mining and predictive modeling
Evidence-based medicine

Problems in developing decision support applications
Representation of the knowledge
Integration with host environments
Managing the knowledge: authoring and update

Standards efforts
Arden syntax
Guidelines
GELLO
Vocabularies and data models
Process/workflow models

Issues
Top-down vs. bottom-up approaches
Legacy investments
Differences among models and purposes
Institutional KM challenges

Getting a handle on the problem
Content management and collaborative authoring/editing
Common representation
Common interfaces/transaction services
Tools for knowledge management

A timetable of opportunities
Rules knowledge
General expressions/calculation/logic
Knowledge element groups
Order sets
Reports and data entry forms

Prospects for dissemination and sharing
Knowledge as a universal commodity not a proprietary resource
Attempts to establish consortia
What is needed to overcome barriers

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