Impact of the Drug-drug Interaction Database SFINX on Prevalence of Potentially Serious Drug-drug Interactions in Primary Health Care

Overview

Journal Eur J Clin Pharmacol

Specialty Pharmacology

Date 2012 Jul 4

PMID 22752671

Citations 34

Authors

M L Andersson

Y Bottiger

J D Lindh

B Wettermark

B Eiermann

Affiliations

Soon will be listed here.

Abstract

Purpose: To investigate the impact of the integration of the drug-drug interaction database SFINX into primary health care records on the prevalence of potentially serious drug-drug interactions.

Methods: The study was a controlled before-and-after study on the prevalence of potential drug-drug interactions before and after the implementation of SFINX at 15 primary healthcare centres compared with 5 centres not receiving the intervention. Data on dispensed prescriptions from health care centres were retrieved from the Swedish prescribed drug register and analysed for September-December 2006 (pre-intervention) and September-December 2007 (post-intervention). All drugs dispensed during each 4 month period were regarded as potentially interacting.

Results: Use of SFINX was associated with a 17% decrease, to 1.81 × 10(-3) from 2.15 × 10(-3) interactions per prescribed drug-drug pair, in the prevalence of potentially serious drug-drug interactions (p = 0.042), whereas no significant effect was observed in the control group. The change in prevalence of potentially serious drug-drug interactions did not differ significantly between the two study groups. The majority of drug-drug interactions identified were related to chelate formation.

Conclusion: Prescriptions resulting in potentially serious drug-drug interactions were significantly reduced after integration of the drug-drug interaction database SFINX into electronic health records in primary care. Further studies are needed to demonstrate the effectiveness of drug-drug interaction warning systems.

Citing Articles

Pharmacotherapeutic actions related to drug interaction alerts - a questionnaire study among Swedish hospital interns and residents in family medicine.

Tukukino C, Parodi Lopez N, Lonnbro J, Wallerstedt S, Svensson S Eur J Clin Pharmacol. 2024; 81(2):301-308.

PMID: 39680076 PMC: 11717818. DOI: 10.1007/s00228-024-03785-4.

How intervention studies measure the effectiveness of medication safety-related clinical decision support systems in primary and long-term care: a systematic review.

Lampe D, Grosser J, Grothe D, Aufenberg B, Gensorowsky D, Witte J BMC Med Inform Decis Mak. 2024; 24(1):188.

PMID: 38965569 PMC: 11225126. DOI: 10.1186/s12911-024-02596-y.

Risk Factors for Potential Drug-Drug Interactions in Outpatients with Dyslipidemia.

Lalatovic N, Pantovic S, Nedovic-Vukovic M, Kostic M Iran J Public Health. 2023; 52(7):1466-1475.

PMID: 37593497 PMC: 10430412. DOI: 10.18502/ijph.v52i7.13248.

Epigenetic Mechanisms Contribute to Intraindividual Variations of Drug Metabolism Mediated by Cytochrome P450 Enzymes.

Jin J, Zhong X Drug Metab Dispos. 2023; 51(6):672-684.

PMID: 36973001 PMC: 10197210. DOI: 10.1124/dmd.122.001007.

TOP-PIC: a new tool to optimize pharmacotherapy and reduce polypharmacy in patients with incurable cancer.

Strassl I, Windhager A, Machherndl-Spandl S, Buxhofer-Ausch V, Stiefel O, Weltermann A J Cancer Res Clin Oncol. 2023; 149(10):7113-7123.

PMID: 36877279 PMC: 10374723. DOI: 10.1007/s00432-023-04671-9.

References

Moura C, Acurcio F, Belo N . Drug-drug interactions associated with length of stay and cost of hospitalization. J Pharm Pharm Sci. 2010; 12(3):266-72. DOI: 10.18433/j35c7z. View

Ko Y, Malone D, DAgostino J, Skrepnek G, Armstrong E, Brown M . Potential determinants of prescribers' drug-drug interaction knowledge. Res Social Adm Pharm. 2008; 4(4):355-66. DOI: 10.1016/j.sapharm.2007.10.004. View

Shah N, Seger A, Seger D, Fiskio J, Kuperman G, Blumenfeld B . Improving acceptance of computerized prescribing alerts in ambulatory care. J Am Med Inform Assoc. 2005; 13(1):5-11. PMC: 1380196. DOI: 10.1197/jamia.M1868. View

Langdorf M, Fox J, Marwah R, Montague B, Hart M . Physician versus computer knowledge of potential drug interactions in the emergency department. Acad Emerg Med. 2000; 7(11):1321-9. DOI: 10.1111/j.1553-2712.2000.tb00483.x. View

Yu D, Seger D, Lasser K, Karson A, Fiskio J, Seger A . Impact of implementing alerts about medication black-box warnings in electronic health records. Pharmacoepidemiol Drug Saf. 2011; 20(2):192-202. DOI: 10.1002/pds.2088. View

Bergkvist A, Midlov P, Hoglund P, Larsson L, Bondesson A, Eriksson T . Improved quality in the hospital discharge summary reduces medication errors--LIMM: Landskrona Integrated Medicines Management. Eur J Clin Pharmacol. 2009; 65(10):1037-46. DOI: 10.1007/s00228-009-0680-1. View

Wettermark B, Hammar N, Fored C, MichaelFored C, Leimanis A, Olausson P . The new Swedish Prescribed Drug Register--opportunities for pharmacoepidemiological research and experience from the first six months. Pharmacoepidemiol Drug Saf. 2006; 16(7):726-35. DOI: 10.1002/pds.1294. View

Bertsche T, Pfaff J, Schiller P, Kaltschmidt J, Pruszydlo M, Stremmel W . Prevention of adverse drug reactions in intensive care patients by personal intervention based on an electronic clinical decision support system. Intensive Care Med. 2010; 36(4):665-72. DOI: 10.1007/s00134-010-1778-8. View

Furu K, Wettermark B, Andersen M, Martikainen J, Almarsdottir A, Sorensen H . The Nordic countries as a cohort for pharmacoepidemiological research. Basic Clin Pharmacol Toxicol. 2009; 106(2):86-94. DOI: 10.1111/j.1742-7843.2009.00494.x. View

10.

Mannheimer B, Eliasson E . Drug-drug interactions that reduce the formation of pharmacologically active metabolites: a poorly understood problem in clinical practice. J Intern Med. 2010; 268(6):540-8. DOI: 10.1111/j.1365-2796.2010.02303.x. View

11.

Eliasson M, Bastholm P, Forsberg P, Henriksson K, Jacobson L, Nilsson A . Janus computerised prescribing system provides pharmacological knowledge at point of care - design, development and proof of concept. Eur J Clin Pharmacol. 2006; 62(4):251-8. DOI: 10.1007/s00228-006-0114-2. View

12.

Ko Y, Abarca J, Malone D, Dare D, Geraets D, Houranieh A . Practitioners' views on computerized drug-drug interaction alerts in the VA system. J Am Med Inform Assoc. 2006; 14(1):56-64. PMC: 2215077. DOI: 10.1197/jamia.M2224. View

13.

Wong K, Yu S, Holbrook A . A systematic review of medication safety outcomes related to drug interaction software. J Popul Ther Clin Pharmacol. 2010; 17(2):e243-55. View

14.

Hovstadius B, Hovstadius K, Astrand B, Petersson G . Increasing polypharmacy - an individual-based study of the Swedish population 2005-2008. BMC Clin Pharmacol. 2010; 10:16. PMC: 3014875. DOI: 10.1186/1472-6904-10-16. View

15.

Sweidan M, Reeve J, Brien J, Jayasuriya P, Martin J, Vernon G . Quality of drug interaction alerts in prescribing and dispensing software. Med J Aust. 2009; 190(5):251-4. DOI: 10.5694/j.1326-5377.2009.tb02832.x. View

16.

Becker M, Visser L, van Gelder T, Hofman A, Stricker B . Increasing exposure to drug-drug interactions between 1992 and 2005 in people aged > or = 55 years. Drugs Aging. 2008; 25(2):145-52. DOI: 10.2165/00002512-200825020-00006. View

17.

Ash J, Fournier L, Stavri P, Dykstra R . Principles for a successful computerized physician order entry implementation. AMIA Annu Symp Proc. 2004; :36-40. PMC: 1480169. View

18.

Paakkari I . Cardiotoxicity of new antihistamines and cisapride. Toxicol Lett. 2002; 127(1-3):279-84. DOI: 10.1016/s0378-4274(01)00510-0. View

19.

Astrand E, Astrand B, Antonov K, Petersson G . Potential drug interactions during a three-decade study period: a cross-sectional study of a prescription register. Eur J Clin Pharmacol. 2007; 63(9):851-9. DOI: 10.1007/s00228-007-0326-0. View

20.

Bottiger Y, Laine K, Andersson M, Korhonen T, Molin B, Ovesjo M . SFINX-a drug-drug interaction database designed for clinical decision support systems. Eur J Clin Pharmacol. 2009; 65(6):627-33. DOI: 10.1007/s00228-008-0612-5. View