Clinical Decision Support
The Road AheadEdited by
- Robert Greenes, Harvard Medical School, Brigham & Women's Hospital, Boston, Massachusetts, U.S.A.
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.
Hardbound, 544 Pages
Published: December 2006
Imprint: Academic Press
- Introduction: Clinical decision supportWhat it is and why importantA brief history of the fieldTypes of computer-aided decision makingCase studiesRegenstrief experienceBrigham experienceLDS HELP experienceLessons learned, summaryWhere are we now?PenetrationLimitationsNew motivations and interestWhere does the knowledge come from?Expert knowledgeData mining and predictive modelingEvidence-based medicineProblems in developing decision support applicationsRepresentation of the knowledgeIntegration with host environmentsManaging the knowledge: authoring and updateStandards effortsArden syntaxGuidelinesGELLOVocabularies and data modelsProcess/workflow modelsIssuesTop-down vs. bottom-up approachesLegacy investmentsDifferences among models and purposesInstitutional KM challengesGetting a handle on the problemContent management and collaborative authoring/editingCommon representationCommon interfaces/transaction servicesTools for knowledge management A timetable of opportunitiesRules knowledgeGeneral expressions/calculation/logicKnowledge element groups Order sets Reports and data entry formsProspects for dissemination and sharingKnowledge as a universal commodity not a proprietary resourceAttempts to establish consortiaWhat is needed to overcome barriers