| Clinical applications projects |
 ASTI
Aide à la Stratégie Thérapeutique Informatisée |
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Guideline-based decision support for prescribing.
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| keywords |
main objectives |
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Decision support, knowledge representation, clinical practice guidelines, prescribing, Physician order entry, XML, markup, decision trees
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Implementation and evaluation of a decision support system for prescribing in general practice.
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| clinical domains |
| primary care prescribing, chronic diseases, hypertension, diabetes |
| description |
The ASTI project has been focused on the design of a guideline-based decision support
system to help general practitioners avoid
prescription errors and comply with best
therapeutic practice, specifically in the treatment of chronic diseases including hypertension.
The system has two modes of use:
- A critiquing mode which operates in the background. In this mode,
a potential prescribing error by a physician can
cause an alert to be automatically triggered and the error corrected.
- A "Guided mode" which directs the physician to the best treatment by browsing a comprehensive guideline knowledge base represented as a decision tree.
The ASTI system is integrated with a French national drugs database, the "Banque Claude Bernard", to enable it to provide online prescribing assistance at the point of care. ASTI is being evaluated in the treatment of hypertension and diabetes.
 " Ce projet a pour objectif le développement de méthodes et outils logiciels destinés à aider le médecin dans le choix des meilleures thérapeutiques médicamenteuses adaptées au cas d’un patient donné. Il pose le problème de la représentation des connaissances sur les stratégies thérapeutiques telles que décrites dans les guides de bonnes pratiques cliniques et de la conception de moteurs d’inférences génériques pour l’utilisation de ces connaissances. Une première phase (1999-2002) soutenue financièrement par le Ministère de la Recherche et de la Technologie et coordonnée par A. Venot, a conduit à la conception d’un système illustré par un logiciel prototype développé dans le domaine du traitement médicamenteux de l’hypertension artérielle essentielle de l’adulte. Ces travaux ont été réalisés par un consortium comprenant quatre laboratoires d’informatique Médicale, deux industriels et la Société de Formation Thérapeutique du Généraliste. Une étude d’acceptabilité a été conduite en Médecine générale. L’extension d’ASTI a d’autres domaines, son amélioration pour le cas spécifique des maladies chroniques et une étude d’impact sont en projet. La valorisation d’ASTI doit conduire à la diffusion industrielle de bases de connaissances de stratégies thérapeutiques et d’outils d’aide à la prescription interfaçables facilement avec les logiciels de gestion de cabinet médical." [Laboratoire LIM&BIO, Université Paris 13].
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| references |
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Séroussi B, Bouaud J, Dreau H et al.
ASTI: a guideline-based drug-ordering system for primary care.
Medinfo. 2001;10(Pt 1):528-32.
[PubMed]
[]
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"
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.
"
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Séroussi B, Bouaud J, Chatellier G, Venot A.
Development of Computerized Guidelines for the Management of Chronic Diseases Allowing to Position any Patient within Recommended Therapeutic Strategies.
Medinfo. 2004;2004:154-8.
[PubMed]
[Paper]
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"
Chronic diseases are complex to manage. One reason comes from the difficulty to synchronize a patient's therapeutic his-tory with the guideline-based sequence of treatments. We pro-pose to represent guideline knowledge as a two-level decision tree, a clinical level describing theoretical clinical situations and a therapeutic level formalizing the different steps of cor-responding recommended therapeutic strategies. Guideline-based strategies are first represented as bidimensional matri-ces structured in lines of therapy and levels of therapeutic intention. A revised version introducing levels of therapeutic combination is then developed. The therapeutic level is opera-tionalized for any patient therapeutic history to provide the next best step of treatment. Evaluated on actual patient re-cords, our system proved to impact physicians' decisions in 78% of the cases and led to a significant improvement of their compliance with recommendations.
" |
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Séroussi B., Bouaud J.
Reminder-based or on-demand guideline-based decision support systems: a preliminary study in primary care with the management of hypertension. In: Eds. K. Kaiser, S. Miksch and S.W. Tu. Computer-based Support for Clinical Guidelines and Protocols. Proceedings of the Symposiom on Computerized Guidelines and Protocols (CGP 2004), Volume 101 Studies in Health Technology and Informatics, 2004, 196 pp., hardcover. ISBN: 1 58603 412
[] [Presentation [OC]]
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"
ASTI is a guideline-based decision support system for therapeutic prescribing in primary care with two modes of interaction. The "critic mode" operates as a reminder system to detect non guideline-compliant physician drug orders, whereas the "guided mode" operates on demand and provides physician guidance to help her establishing best recommended drug prescriptions for the management of hypertension. A preliminary evaluation study was conducted with 10 GPs to test the complementary nature of both modes of decision support. Results tend to validate our assumption that reminder-based interaction is appropriate for simple cases and that physicians are willing to use on-demand systems as clinical situations become more complex.
"
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| start date
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end date
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location |
support |
November 1999.
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French national project. |
Ministère de l'Education Nationale, de la Recherche et de la Technologie (MENRT) under the programme: "Télémédecine et Technologies pour la Santé".
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| contact |
links |
Partners include: Laboratoire d'Enseignement et de Recherche en Traitement de l'Information Médicale (LERTIM), Faculté De Médecine, Université De La Méditerranée, Marseille; Laboratoire LIM&BIO, Université Paris 13; Service d'Informatique Médicale de l'Assistance Publique-Hôpitaux de Paris.
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| acknowledgements |
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Entry in directory: October 1 2004
Last main update: October 1 2004 |
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Laboratoire d'Enseignement et de Recherche en Traitement de l'Information Médicale (LERTIM), Faculté De Médecine, Université De La Méditerranée, Marseille