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Drugs & Aging

, Volume 20, Issue 10, pp 769–776 | Cite as

Identification of Adverse Drug Reactions in Geriatric Inpatients Using a Computerised Drug Database

  • Tobias EggerEmail author
  • Harald Dormann
  • Gabi Ahne
  • Ulrich Runge
  • Antje Neubert
  • Manfred Criegee-Rieck
  • Karl G. Gassmann
  • Kay Brune
Original Research Article

Abstract

Introduction and objective

Geriatric patients with multiple comorbidities are at high risk of experiencing an adverse drug reaction (ADR) during hospitalisation. The aim of the study was to compare the rate of ADRs as predicted by a computerised pharmacological database to the actual rate determined by direct observation in a sample of geriatric patients.

Study design

During a 4-month period, geriatric patients were monitored using prospective observation. Patients were intensively screened for ADRs by a pharmacoepidemiological team (PET), consisting of two pharmacists and a physician. Actual ADRs detected by the PET were compared with those predicted by a computerised drug database. Furthermore, the set of actual ADRs, which resulted from drug-drug interactions (DDIs), were contrasted with potential DDIs signalled by the database. The main outcome measures were the incidence of actual ADRs. For the detection rate of the database we focused on frequent ADRs (>1% according to product information and database) and all DDIs indicated automatically by the database.

Results

163 patients (121 female), mean age 79.8 ± 7.1 years (range 60–98), were included in the study which was conducted on a geriatric rehabilitation hospital ward. The mean duration of hospitalisation was 24.3 ± 8.4 days. Elderly patients received an average of 14.0 drugs (range 2–35) during their hospital stay.

Of all patients, 60.7% experienced at least one ADR. The PET detected a total of 153 ADRs, with a mean of 0.9 ADRs per patient (range 0–5). The computerised drug database predicted an average of 309 potential ADRs for each patient; however, only 21 ADRs per patient were of high frequency. In 48% of ADR-positive patients (defined by PET) at least one of these frequent ADRs occurred.

DDIs were detected by the PET in 14.7% of patients. Our database indicated a mean of 12 potential DDIs per patient. In 14 out of 24 DDI-positive patients, at least one signal indicated a real DDI. The database sensitivity was consequently 58.3%.

Conclusion

In geriatric patients the incidence of ADRs is high. Computerised drug databases are a useful tool for detecting and avoiding ADRs. Our software, however, also produced a large number of signals that did not relate to actual ADRs found by the PET. The sheer number of these ‘false’ signals shows the need for refinement and optimisation of databases for daily clinical use.

Keywords

Adverse Drug Reaction Glimepiride Nadroparin Potential DDIs Geriatric Rehabilitation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgements

This study was supported by grants from Bundesministerium für Bildung und Forschung (BMBF) 01EC940317, BMBF 08NM061D and German Israeli Fundation No. G 690221.912000, health initiative “Bayern Aktiv” No 3.8/8600. The authors have provided no information on conflicts of interest directly relevant to the content of this study.

References

  1. 1.
    Leape LL, Brennan TA, Laird N, 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): 377–84PubMedCrossRefGoogle Scholar
  2. 2.
    Bates DW, Leape LL, Petrycki S. Incidence and preventability of adverse drug events in hospitalized adults. J Gen Intern Med 1993; 8(6): 289–94PubMedCrossRefGoogle Scholar
  3. 3.
    Lazarou J, Pomeranz BH, Corey PN. Incidence of adverse drug reactions in hospitalized patients: a meta-analysis of prospective studies. JAMA 1998; 279(15): 1200–5PubMedCrossRefGoogle Scholar
  4. 4.
    Atkin PA, Veitch PC, Veitch EM, et al. The epidemiology of serious adverse drug reactions among the elderly. Drugs Aging 1999; 14(2): 141–52PubMedCrossRefGoogle Scholar
  5. 5.
    Beyth RJ, Shorr RI. Epidemiology of adverse drug reactions in the elderly by drug class. Drugs Aging 1999; 14(3): 231–9PubMedCrossRefGoogle Scholar
  6. 6.
    Classen DC, Pestotnik SL, Evans RS, et al. Adverse drug events in hospitalized patients: excess length of stay, extra costs, and attributable mortality. JAMA 1997; 277(4): 301–6PubMedCrossRefGoogle Scholar
  7. 7.
    Bates DW, Spell N, Cullen DJ, et al. The costs of adverse drug events in hospitalized patients: Adverse Drug Events Prevention Study Group. JAMA 1997; 277(4): 307–11PubMedCrossRefGoogle Scholar
  8. 8.
    Bates DW, Teich JM, Lee J, et al. The impact of computerized physician order entry on medication error prevention. J Am Med Inform Assoc 1999; 6(4): 313–21PubMedCrossRefGoogle Scholar
  9. 9.
    Jha AK, Kuperman GJ, Teich JM, et al. Identifying adverse drug events: development of a computer-based monitor and comparison with chart review and stimulated voluntary report. J Am Med Inform Assoc 1998; 5(3): 305–14PubMedCrossRefGoogle Scholar
  10. 10.
    Dormann H, Muth-Selbach U, Krebs S, et al. Incidence and costs of adverse drug reactions during hospitalisation: computerised monitoring versus stimulated spontaneous reporting. Drug Saf 2000; 22(2): 161–8PubMedCrossRefGoogle Scholar
  11. 11.
    Azaz-Livshits T, Levy M, Sadan B, et al. Computerized survelliance of adverse drug reactions in hospital: pilot study. Br J Clin Pharmacol 1998; 45(3): 309–14PubMedCrossRefGoogle Scholar
  12. 12.
    Langdorf MI, Fox JC, Marwah RS, et al. Physician versus computer knowledge of potential drug interactions in the emergency department. Acad Emerg Med 2000; 7(11): 1321–9PubMedCrossRefGoogle Scholar
  13. 13.
    Del Fiol G, Rocha BH, Kuperman GJ, et al. Comparison of two knowledge bases on the detection of drug-drug interactions. Proc AMIA Symp 2000, 171–5Google Scholar
  14. 14.
    Goldberg RM, Mabee J, Mammone M, et al. A comparison of drug interaction software programs: applicability to the emergency department. Ann Emerg Med 1994; 24(4): 619–25PubMedCrossRefGoogle Scholar
  15. 15.
    Jankel CA, Martin BC. Evaluation of six computerized drug interaction screening programs. Am J Hosp Pharm 1992; 49(6): 1430–5PubMedGoogle Scholar
  16. 16.
    Bates DW, Leape LL, Cullen DJ, et al. Effect of computerized physician order entry and a team intervention on prevention of serious medication errors. JAMA 1998; 280(15): 1311–6PubMedCrossRefGoogle Scholar
  17. 17.
    Raschke RA, Gollihare B, Wunderlich TA, et al. A computer alert system to prevent injury from adverse drug events: development and evaluation in a community teaching hospital [published erratum appears in JAMA 1999 Feb 3; 281 (5): 420]. JAMA 1998; 280(15): 1317–20PubMedCrossRefGoogle Scholar
  18. 18.
    Fricke U, Günther J. Anatomisch-therapeutisch-chemische Klassifikation mit Tagesdosen für den deutschen Arzneimittelmarkt. 2002Google Scholar
  19. 19.
    WHO. International statistical classification of diseases and related health problems. 10th rev ed. Geneva: WHO, 1992Google Scholar
  20. 20.
    Edward IR, Aronson JK. Adverse drug reactions: definitions, diagnosis and management. Lancet 2000; 356(9237): 1255–9CrossRefGoogle Scholar
  21. 21.
    Naranjo CA, Busto U, Sellers EM, et al. A method for estimating the probability of adverse drug reactions. Clin Pharmacol Ther 1981; 30(2): 239–45PubMedCrossRefGoogle Scholar
  22. 22.
    Rieder MJ. Mechanisms of unpredictable adverse drug reactions. Drug Saf 1994; 11(3): 196–212PubMedCrossRefGoogle Scholar
  23. 23.
    Schumock GT, Thornton JP. Focusing on the preventability of adverse drug reactions [letter]. Hosp Pharm 1992; 27(6): 538PubMedGoogle Scholar
  24. 24.
    Hanlon JT, Schmader KE, Koronkowski MJ, et al. Adverse drug events in high risk older outpatients. J Am Geriatr Soc1997; 45(8): 945–8PubMedGoogle Scholar
  25. 25.
    Bates DW. Drugs and adverse drug reactions: how worried should we be? JAMA 1998; 279(15): 1216–7PubMedCrossRefGoogle Scholar
  26. 26.
    Gurwitz JH, Avorn J. Old age: is it a risk for adverse drug reactions? Agents Actions Suppl 1990; 29: 13–25PubMedGoogle Scholar
  27. 27.
    Dormann H, Criegee-Rieck M, Neubert A, et al. Lack of awareness of community-acquired adverse drug reactions upon hospital admission: dimensions and consequences of a dilemma. Drug Saf 2003; 26(5): 353–62PubMedCrossRefGoogle Scholar

Copyright information

© Adis Data Information BV 2003

Authors and Affiliations

  • Tobias Egger
    • 1
    Email author
  • Harald Dormann
    • 2
  • Gabi Ahne
    • 1
  • Ulrich Runge
    • 3
  • Antje Neubert
    • 1
  • Manfred Criegee-Rieck
    • 1
  • Karl G. Gassmann
    • 3
  • Kay Brune
    • 1
  1. 1.Department of Experimental and Clinical Pharmacology and ToxicologyUniversity Erlangen-NurembergErlangenGermany
  2. 2.Department of Internal MedicineUniversity Erlangen-NurembergErlangenGermany
  3. 3.Department of Geriatric RehabilitationErlangenGermany

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