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DOI: 10.1055/s-0038-1634615
Modeling Drug Information for a Prescription – Oriented Knowledge Base on Drugs
Publication History
Publication Date:
16 February 2018 (online)
Abstract:
There exists little theoretical analysis how to represent knowledge on drugs required for computerized drug-prescription applications. A work package drug information modeling is described which was part of the European GPADE project. We describe the content and structure of a Drug Knowledge Base (DKB) designed to meet the requirements of decision-support systems in the domain of drug therapy, and to facilitate data transfer from various information sources. The definition of the DKB content is derived from the analysis of information requirements at the various stages of the process of the clinical usage of drugs (prescribing, administration, and follow-up). The DKB structure results from the classification of the various data items along two dimensions: (1) entities in the pharmaco-therapeutic domain for which information must be defined (the Pharmaco-Therapeutic Group, the Component, the Manufactured Preparation, and the Presentation), and (2) the validity score of the pharmaco-therapeutic information (international, national, or local).
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References
- 1 Blaschke TF. Hospital information systems and the quality of therapeutics. Meth Inform Med 1990; 29: 163-6.
- 2 Prokosch HU, Wong TW, Pryor TA. Medication ordering based on a predictive knowledge base. Artif Intell Med 1989; 1: 41-8.
- 3 Pinciroli F, Combi C, Pozzi G, Rossi R. MS2/Cardio: towards a multi-service medical software for cardiology. Meth Inform Med 1992; 31: 18-28.
- 4 Linnarsson R. Decision support for drug prescription integrated with computer-based patient records in primary care. Med Inform 1993; 18: 131-42.
- 5 De Zegher I, Venot A, Milstein C, Séné B, De Carolis B, Pizzutilo S. OPADE: optimization of drug prescription using advanced informatics. Comput Meth Progr Biomed 1994; 45: 131-6
- 6 Segal R, Hepler C. Prescribers’ beliefs and values as predictors of drug choices. Am J Hosp Pharm 1982; 39: 1891-7.
- 7 Raisch DW. A model of methods for influencing prescribing: part I. A review of prescribing models, persuasion theories, and administrative and educational methods. DICP, The Annals of Pharmacotherapy 1990; 24: 417-2l.
- 8 Covell DG, Uman GC, Manning PR. Information needs in office practice: are they being met?. Ann Intern Med 1985; 103: 596-9.
- 9 Herxheimer A, Lionel NDW. Minimum information needed by prescribers. BMJ 1978; 2: 1129-32.
- 10 Hermann F, Herxheimer A, Lionel NDW. Package inserts for prescribed medicines: what minimum information do patients need?. BMJ 1978; 2: 1132-5.
- 11 ASHP report. ASHP guidelines on pharmacist-conducted patient counseling. Am J Hosp Pharm 1993; 50: 505-6.
- 12 Le Roux MGJ, Russel I. The anatomical therapeutic chemical (ATC) drug classification system; possible new applications. Internat Pharm J 1990; 4 (04) 150-3.
- 13 Coad P, Yourdon E. Object-oriented Analysis. New York: Prentice-Hall; 1991
- 14 Jeliffe RW. Clinical applications of pharmacokinetics and control theory: Planning, monitoring, and adjusting dosage regimens of aminoglycosides, lidocaine, digitoxin and digoxin. In: Maronde R. ed. Selected Topics in Clinical Pharmacology. New York: Springer-Verlag; 1986: 27-82.
- 15 Mallet A, Mentre F, Gilles J. et al. Handling covariates in population pharmacokinetics, with an application to Gentamicin. Biomed Meas Inform Contr 1988; 2: 673-83.
- 16 De Zegher I, Milstein C, Pietri P, Venot A. Construction et maintenance d’une base de connaissances sur les médicaments par Télématique. In: Technologie et Sante 1993; 14: 28-34.
- 17 Yamamoto M, Negi H, Tamura M. et al. The development and practical use of information systems in the pharmaceutical industry. Meth Inform Med 1993; 32: 400-6.