Main description:

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.

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