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Original article

Vol. 142 No. 0506 (2012)

Frequency and nature of drug-drug interactions in a Swiss primary and secondary acute care hospital

  • Marc Oertle
DOI
https://doi.org/10.4414/smw.2012.13522
Cite this as:
Swiss Med Wkly. 2012;142:w13522
Published
29.01.2012

Summary

QUESTIONS UNDER STUDY: Drug-drug interactions (DDI) are considered a risk factor in medication safety and computerised alerting tools are increasingly promoted and implemented in order to detect and minimise DDI. As only little is known about the frequency and nature of DDI in hospitalised patients in Switzerland as well as about the usefulness of current alerting systems, this analysis based on a computerised medication record in a typical regional hospital setting was performed.

METHODS: All inpatients with at least one drug prescription between 2006 and 2010 were included. A total of 1,654,987 prescriptions were analysed with regard to the maximal seriousness level of DDI between each added prescription versus the existing prescription and with regard to all underlying DDI.

RESULTS: On average, each inpatient received 16 different drugs including on-demand prescriptions and encountered 5 DDI. A total of 27% of all prescriptions caused DDI. Within the last 12 months, 5% of all DDI were classified in category 1 (contraindicated), 3% in category 2, 53% in category 3, 8% in category 4 and 31% in category 5. The vast majority of DDI were caused by a very limited number of drugs.

DISCUSSION: Drug-drug interactions were very frequent and were very stable over the years studied, involving on average 27% of all prescriptions and 44% in internal medicine. Only a very limited amount of drugs were responsible for the vast majority of DDI, especially when the most severe categories of DDI were considered. Most of the severe DDI alerts could be automatically handled, if for example laboratory values could be taken into account. The DDI database should ideally be supplemented by information enabling more sophisticated computerised support in order to deliver more reasonable results from DDI checks.

References

  1. Brennan TA, Leape LL, Laird NM, Hebert L, Localio AR, Lawthers AG, et al. Incidence of adverse events and negligence in hospitalized patients. Results of the Harvard Medical Practice Study I. N Engl J Med. 1991;325(3):210.
  2. Leape LL, Bates DW, Cullen DJ, Cooper J, Demonaco HJ, Gallivan T, et al. Systems analysis of adverse drug events. ADE Prevention Study Group. JAMA. 1995;274(1):35–43.
  3. Hug BL, Witkowski DJ, Sox CM, Keohane CA, Seger DL, Yoon C, et al. Adverse drug event rates in six community hospitals and the potential impact of computerized physician order entry for prevention. J Gen Intern Med. 2010;25(1):31–8.
  4. McDonnell PJ, Jacobs MR. Hospital admissions resulting from preventable adverse drug reactions. Ann Pharmacother. 2002;36(9):1331–6.
  5. Sanchez Munoz-Torrero JF, Barquilla P, Velasco R, Fernandez Capitan Mdel C, Pacheco N. Adverse drug reactions in internal medicine units and associated risk factors. Eur J Clin Pharmacol. 2010;66(12):1257–64.
  6. Zwart-van Rijkom JE, Uijtendaal EV, ten Berg MJ, van Solinge WW, Egberts AC. Frequency and nature of drug-drug interactions in a Dutch university hospital. Br J Clin Pharmacol. 2010;70(4):619–20.
  7. Moura CS, Acurcio FA, Belo NO. Drug-drug interactions associated with length of stay and cost of hospitalization. J Pharm Pharm Sci. 2009;12(3):266–72.
  8. van der Sijs H, Mulder A, van Gelder T, Aarts J, Berg M, Vulto A. Drug safety alert generation and overriding in a large Dutch university medical centre. Pharmacoepidemiol Drug Saf. 2009;18(10):941–7.
  9. Weingart SN, Toth M, Sands DZ, Aronson MD, Davis RB, Phillips RS. Physicians’ decisions to override computerized drug alerts in primary care. Arch Intern Med. 2003;163(21):2625–31.
  10. Hansten PD, Horn JR, Hazlet TK. ORCA: OpeRational ClassificAtion of drug interactions. J Am Pharm Assoc (Wash). 2001;41(2):161–5.
  11. Leape LL, Brennan TA, Laird N, Lawthers AG, Localio AR, Barnes BA, et al. The nature of adverse events in hospitalized patients. Results of the Harvard Medical Practice Study II. N Engl J Med. 1991;324(6):377–84.
  12. Morimoto T, Gandhi TK, Seger AC, Hsieh TC, Bates DW. Adverse drug events and medication errors: detection and classification methods. Qual Saf Health Care. 2004;13(4):306–14.
  13. Jylha V, Saranto K, Bates DW. Preventable adverse drug events and their causes and contributing factors: the analysis of register data. Int J Qual Health Care. 2011;23(2):187–97.
  14. Kongkaew C, Noyce PR, Ashcroft D. Hospital admissions associated with adverse drug reactions: a systematic review of prospective observational studies. Ann Pharmacother. 2008;42(7):1017–25.
  15. Bates DW, Cullen DJ, Laird N, Petersen LA, Small SD, Servi D, et al. Incidence of adverse drug events and potential adverse drug events. Implications for prevention. ADE Prevention Study Group. JAMA. 1995;274(1):29–34.
  16. Fijn R, Van den Bemt PM, Chow M, De Blaey CJ, De Jong-Van den Berg LT, Brouwers JR. Hospital prescribing errors: epidemiological assessment of predictors. Br J Clin Pharmacol. 2002;53(3):326–31.
  17. Fokter N, Mozina M, Brvar M. Potential drug-drug interactions and admissions due to drug-drug interactions in patients treated in medical departments. Wien Klin Wochenschr. 2010;122(3–4):62–4.
  18. Vonbach P, Dubied A, Krahenbuhl S, Beer JH. Prevalence of drug-drug interactions at hospital entry and during hospital stay of patients in internal medicine. Eur J Intern Med. 2008;19(6):413–20.
  19. Egger SS, Drewe J, Schlienger RG. Potential drug-drug interactions in the medication of medical patients at hospital discharge. Eur J Clin Pharmacol. 2003;58(11):773–8.
  20. Bertoli R, Bissig M, Caronzolo D, Odorico M, Pons M, Bernasconi E. Assessment of potential drug-drug interactions at hospital discharge. Swiss Med Wkly. 2010;140:w13043.
  21. Paterno MD, Maviglia SM, Gorman PN, Seger DL, Yoshida E, Seger AC, et al. Tiering drug-drug interaction alerts by severity increases compliance rates. J Am Med Inform Assoc. 2009;16(1):40–6.
  22. Bonnabry P, Despont-Gros C, Grauser D, Casez P, Despond M, Pugin D, et al. A risk analysis method to evaluate the impact of a computerized provider order entry system on patient safety. J Am Med Inform Assoc. 2008;15(4):453–60.

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