Literature DB >> 11604796

ASTI: a guideline-based drug-ordering system for primary care.

B Séroussi1, J Bouaud, H Dréau, H Falcoff, C Riou, M Joubert, C Simon, G Simon, A Venot.   

Abstract

Existing computer-based ordering systems for physicians provide effective drug-centered checks but offer little assistance for optimizing the overall patient-centered treatment strategy. Evidence-based clinical practice guidelines have been developed to disseminate state-of-the-art information concerning treatment strategy but these guidelines are poorly used in routine practice. The ASTI project aims to design a guideline-based ordering system to enable general practitioners to avoid prescription errors and to improve compliance with best therapeutic practices. The " critic mode " operates as a background process and corrects the physician's prescription on the basis of automatically triggered elementary rules that account for isolated guideline recommendations. The " guided mode " directs the physician to the best treatment by browsing a comprehensive guideline knowledge base represented as a decision tree. A first prototype, applied to hypertension, is currently under development.

Entities:  

Mesh:

Year:  2001        PMID: 11604796

Source DB:  PubMed          Journal:  Stud Health Technol Inform        ISSN: 0926-9630


  10 in total

1.  Does GEM-encoding clinical practice guidelines improve the quality of knowledge bases? A study with the rule-based formalism.

Authors:  Georg Georg; Brigitte Séroussi; Jacques Bouaud
Journal:  AMIA Annu Symp Proc       Date:  2003

2.  Consequences of the verification of completeness in clinical practice guideline modeling: a theoretical and empirical study with hypertension.

Authors:  J Bouaud; B Séroussi; H Falcoff; J Julien; C Simon; D L Denké
Journal:  AMIA Annu Symp Proc       Date:  2009-11-14

3.  Use of the C4.5 machine learning algorithm to test a clinical guideline-based decision support system.

Authors:  Jean-Baptiste Lamy; Anis Ellini; Vahid Ebrahiminia; Jean-Daniel Zucker; Hector Falcoff; Alain Venot
Journal:  Stud Health Technol Inform       Date:  2008

4.  A generic system for critiquing physicians' prescriptions: usability, satisfaction and lessons learnt.

Authors:  Jean-Baptiste Lamy; Vahid Ebrahiminia; Brigitte Seroussi; Jacques Bouaud; Christia Simon; Madeleine Favre; Hector Falcoff; Alain Venot
Journal:  Stud Health Technol Inform       Date:  2011

5.  Mapping ASTI patient's therapeutic-data model to virtual Medical Record: can VMR represent therapeutic data elements used by ASTI in clinical guideline implementations?

Authors:  Vahid Ebrahiminia; Mobin Yasini; Jean Baptiste Lamy
Journal:  AMIA Annu Symp Proc       Date:  2013-11-16

6.  Role of physicians' reactance in e-iatrogenesis: a case study with ASTI guiding mode on the management of hypertension.

Authors:  B Séroussi; H Falcoff; D Sauquet; J Julien; J Bouaud
Journal:  AMIA Annu Symp Proc       Date:  2010-11-13

7.  Design factors for success or failure of guideline-based decision support systems: an hypothesis involving case complexity.

Authors:  J Bouaud; B Séroussi; H Falcoff; A Venot
Journal:  AMIA Annu Symp Proc       Date:  2006

8.  How to translate therapeutic recommendations in clinical practice guidelines into rules for critiquing physician prescriptions? Methods and application to five guidelines.

Authors:  Jean-Baptiste Lamy; Vahid Ebrahiminia; Christine Riou; Brigitte Seroussi; Jacques Bouaud; Christian Simon; Stéphane Dubois; Antoine Butti; Gérard Simon; Madeleine Favre; Hector Falcoff; Alain Venot
Journal:  BMC Med Inform Decis Mak       Date:  2010-05-28       Impact factor: 2.796

9.  Algorithms for optimizing drug therapy.

Authors:  Peter Wanger; Lene Martin
Journal:  BMC Med Inform Decis Mak       Date:  2004-07-20       Impact factor: 2.796

10.  Coupling computer-interpretable guidelines with a drug-database through a web-based system--The PRESGUID project.

Authors:  Jean-Charles Dufour; Dominique Fieschi; Marius Fieschi
Journal:  BMC Med Inform Decis Mak       Date:  2004-03-02       Impact factor: 2.796

  10 in total

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