Abstract
Drugs interfere with laboratory diagnostics. This interference is not only confusing for clinicians but may lead to wrong diagnoses or treatments as well as unnecessary further tests. However, at the moment the drug-laboratory interferences are usually ignored in patient care because clinicians do not know or remember these properties of drugs. In Turku University Central Hospital we are now able to bring this information automatically available for clinicians by using a computerized system for linking individual patient medication data with laboratory information system. For this purpose, we are building a rule base containing the effects of drugs on laboratory tests. In order that the rule base would give the maximum benefit for all users, even other hospitals, the data included have to be classified and coded properly taking into account the various requirements and needs of all users. In this paper we introduce a coding scheme for classification and coding of drug effects on laboratory tests.
Full text
PDF
Selected References
These references are in PubMed. This may not be the complete list of references from this article.
- Berman J. J., Moore G. W., Donnelly W. H., Massey J. K., Craig B. A SNOMED analysis of three years' accessioned cases (40,124) of a surgical pathology department: implications for pathology-based demographic studies. Proc Annu Symp Comput Appl Med Care. 1994:188–192. [PMC free article] [PubMed] [Google Scholar]
- Classen D. C., Pestotnik S. L., Evans R. S., Burke J. P. Description of a computerized adverse drug event monitor using a hospital information system. Hosp Pharm. 1992 Sep;27(9):774, 776-9, 783. [PubMed] [Google Scholar]
- Evans R. S., Classen D. C., Pestotnik S. L., Lundsgaarde H. P., Burke J. P. Improving empiric antibiotic selection using computer decision support. Arch Intern Med. 1994 Apr 25;154(8):878–884. [PubMed] [Google Scholar]
- Evans R. S., Pestotnik S. L., Classen D. C., Horn S. D., Bass S. B., Burke J. P. Preventing adverse drug events in hospitalized patients. Ann Pharmacother. 1994 Apr;28(4):523–527. doi: 10.1177/106002809402800417. [DOI] [PubMed] [Google Scholar]
- Gardner R. M., Maack B. B., Evans R. S., Huff S. M. Computerized medical care: the HELP system at LDS Hospital. J AHIMA. 1992 Jun;63(6):68–78. [PubMed] [Google Scholar]
- Grönroos P., Irjala K., Heiskanen J., Torniainen K., Forsström Using computerized individual medication data to detect drug effects on clinical laboratory tests. Scand J Clin Lab Invest Suppl. 1995;222:31–36. doi: 10.3109/00365519509088448. [DOI] [PubMed] [Google Scholar]
- Kennedy R. L., Griffiths H., Gray T. A. Amiodarone and the thyroid. Clin Chem. 1989 Sep;35(9):1882–1887. [PubMed] [Google Scholar]
- Linnarsson R. Drug interactions in primary health care. A retrospective database study and its implications for the design of a computerized decision support system. Scand J Prim Health Care. 1993 Sep;11(3):181–186. doi: 10.3109/02813439308994827. [DOI] [PubMed] [Google Scholar]
- Marshall T., Williams K. M. Drug interference in the Bradford and 2,2'-bicinchoninic acid protein assays. Anal Biochem. 1991 Nov 1;198(2):352–354. doi: 10.1016/0003-2697(91)90438-y. [DOI] [PubMed] [Google Scholar]
- Pryor T. A., Gardner R. M., Clayton P. D., Warner H. R. The HELP system. J Med Syst. 1983 Apr;7(2):87–102. doi: 10.1007/BF00995116. [DOI] [PubMed] [Google Scholar]
- Skinner R., Caldwell J., Vitale P. Computerized screening for appropriate dosing of renally eliminated medications. Proc Annu Symp Comput Appl Med Care. 1994:971–971. [PMC free article] [PubMed] [Google Scholar]