Advertisement

International Journal of Clinical Pharmacy

, Volume 36, Issue 5, pp 943–952 | Cite as

Potential drug related problems detected by electronic expert support system in patients with multi-dose drug dispensing

  • Hammar ToraEmail author
  • Hovstadius Bo
  • Lidström Bodil
  • Petersson Göran
  • Eiermann Birgit
Research Article

Abstract

Background Drug related problems (DRPs) are frequent and cause suffering for patients and substantial costs for society. Multi-dose drug dispensing (MDDD) is a service by which patients receive their medication packed in bags with one unit for each dose occasion. The clinical decision support system (CDSS) electronic expert support (EES) analyses patients’ prescriptions in the Swedish national e-prescription repository and provides alerts if potential DRPs are detected, i.e. drug–drug interactions, duplicate therapy, drug-disease contraindications, high dose, gender warnings, geriatric, and paediatric alerts. Objective To analyse potential DRPs in patients with MDDD, detected by means of EES. Setting A register study of all electronically stored prescriptions for patients with MDDD in Sweden (n = 180,059) March 5–June 5, 2013. Method Drug use and potential DRPs detected in the study population during the 3 month study period by EES were analysed. The potential DRPs were analysed in relation to patients’ age, gender, number of drugs, and type of medication. Main outcome measure Prevalence of potential DRPs measured as EES alerts. Results The study population was on average 75.8 years of age (±17.5, range 1–110) and had 10.0 different medications (±4.7, range 1–53). EES alerted for potential DRPs in 76 % of the population with a mean of 2.2 alerts per patient (±2.4, range 0–27). The older patients received a lower number of alerts compared to younger patients despite having a higher number of drugs. The most frequent alert categories were drug–drug interactions (37 % of all alerts), duplicate therapy (30 %), and geriatric warnings for high dose or inappropriate drugs (23 %). Psycholeptics, psychoanaleptics, antithrombotic agents, anti-epileptics, renin-angiotensin system agents, and analgesics represented 71 % of all drugs involved in alerts. Conclusions EES detected potential DRPs in the majority of patients with MDDD. The number of potential DRPs was associated with the number of drugs, age, gender, and type of medication. A CDSS such as EES might be a useful tool for physicians and pharmacists to assist in the important task of monitoring patients with MDDD for potential DRPs.

Keywords

Clinical decision support system Drug–drug interactions Drug related problems Multi-dose drug dispensing Pharmacoepidemiology Sweden 

Notes

Acknowledgments

The authors would like to express their gratitude to Abdul Aziz Ali for advice on statistical analyses.

Funding

eHealth Agency, Medical Products Agency, Linnaeus University.

Conflicts of interest

The authors have no conflict of interest. At the time of the study, two of the authors (BL and BE) were employed at the government agency, the eHealth agency, managing the EES.

References

  1. 1.
    Juurlink DN, Mamdani M, Kopp A, Laupacis A, Redelmeier DA. Drug-drug interactions among elderly patients hospitalized for drug toxicity. JAMA. 2003;289(13):1652–8.PubMedCrossRefGoogle Scholar
  2. 2.
    Lazarou J, Pomeranz BH, Corey PN. Incidence of adverse drug reactions in hospitalized patients: a meta-analysis of prospective studies. JAMA. 1998;279(15):1200–5.PubMedCrossRefGoogle Scholar
  3. 3.
    Strandell J, Wahlin S. Pharmacodynamic and pharmacokinetic drug interactions reported to VigiBase, the WHO global individual case safety report database. Eur J Clin Pharmacol. 2011;67(6):633–41.PubMedCrossRefGoogle Scholar
  4. 4.
    Jonsson AK, Spigset O, Tjaderborn M, Druid H, Hagg S. Fatal drug poisonings in a Swedish general population. BMC Clin Pharmacol. 2009;9:7.PubMedCrossRefPubMedCentralGoogle Scholar
  5. 5.
    Tache SV, Sonnichsen A, Ashcroft DM. Prevalence of adverse drug events in ambulatory care: a systematic review. Ann Pharmacother. 2011;45(7–8):977–89.PubMedCrossRefGoogle Scholar
  6. 6.
    Westerlund T, Gelin U, Pettersson E, Skarlund F, Wagstrom K, Ringbom C. A retrospective analysis of drug-related problems documented in a national database. Int J Clin Pharm. 2013;35(2):202–9.PubMedCrossRefGoogle Scholar
  7. 7.
    Wester K, Jonsson AK, Spigset O, Druid H, Hagg S. Incidence of fatal adverse drug reactions: a population based study. Br J Clin Pharmacol. 2008;65(4):573–9.PubMedCrossRefPubMedCentralGoogle Scholar
  8. 8.
    Salvi F, Marchetti A, D’Angelo F, Boemi M, Lattanzio F, Cherubini A. Adverse drug events as a cause of hospitalization in older adults. Drug Saf. 2012;35(Suppl 1):29–45.PubMedCrossRefGoogle Scholar
  9. 9.
    Topinkova E, Baeyens JP, Michel JP, Lang PO. Evidence-based strategies for the optimization of pharmacotherapy in older people. Drugs Aging. 2012;29(6):477–94.PubMedCrossRefGoogle Scholar
  10. 10.
    Marcum ZA, Handler SM, Wright R, Hanlon JT. Interventions to improve suboptimal prescribing in nursing homes: a narrative review. Am J Geriatr Pharmacother. 2010;8(3):183–200.PubMedCrossRefPubMedCentralGoogle Scholar
  11. 11.
    Strandell J, Bate A, Lindquist M, Edwards IR. Drug-drug interactions—a preventable patient safety issue? Br J Clin Pharmacol. 2008;65(1):144–6.PubMedCrossRefPubMedCentralGoogle Scholar
  12. 12.
    Jonsson AK, Hakkarainen KM, Spigset O, Druid H, Hiselius A, Hagg S. Preventable drug related mortality in a Swedish population. Pharmacoepidemiol Drug Saf. 2010;19(2):211–5.PubMedCrossRefGoogle Scholar
  13. 13.
    Black AD, Car J, Pagliari C, Anandan C, Cresswell K, Bokun T, et al. The impact of eHealth on the quality and safety of health care: a systematic overview. PLoS Med. 2011;8(1):e1000387.PubMedCrossRefPubMedCentralGoogle Scholar
  14. 14.
    Bates DW, Cohen M, Leape LL, Overhage JM, Shabot MM, Sheridan T. White paper—reducing the frequency of errors in medicine using information technology. J Am Med Inform Assoc. 2001;8(4):299–308.PubMedCrossRefPubMedCentralGoogle Scholar
  15. 15.
    Cresswell KM, Bates DW, Sheikh A. Ten key considerations for the successful implementation and adoption of large-scale health information technology. J Am Med Inform Assoc. 2013;20(e1):e9–13.PubMedCrossRefPubMedCentralGoogle Scholar
  16. 16.
    Huckvale C, Car J, Akiyama M, Jaafar S, Khoja T, Bin Khalid A, et al. Information technology for patient safety. Qual Saf Health Care. 2010;19(Suppl 2):i25–33.PubMedCrossRefGoogle Scholar
  17. 17.
    Appari A, Carian EK, Johnson ME, Anthony DL. Medication administration quality and health information technology: a national study of US hospitals. J Am Med Inform Assoc. 2012;19(3):360–7.PubMedCrossRefPubMedCentralGoogle Scholar
  18. 18.
    McKibbon KA, Lokker C, Handler SM, Dolovich LR, Holbrook AM, O’Reilly D, et al. The effectiveness of integrated health information technologies across the phases of medication management: a systematic review of randomized controlled trials. J Am Med Inform Assoc. 2012;19(1):22–30.PubMedCrossRefPubMedCentralGoogle Scholar
  19. 19.
    Ojeleye O, Avery A, Gupta V, Boyd M. The evidence for the effectiveness of safety alerts in electronic patient medication record systems at the point of pharmacy order entry: a systematic review. BMC Med Inform Decis Mak. 2013;13:69.PubMedCrossRefPubMedCentralGoogle Scholar
  20. 20.
    Devine EB, Hansen RN, Wilson-Norton JL, Lawless NM, Fisk AW, Blough DK, et al. The impact of computerized provider order entry on medication errors in a multispecialty group practice. J Am Med Inform Assoc. 2010;17(1):78–84.PubMedCrossRefPubMedCentralGoogle Scholar
  21. 21.
    Saverno KR, Hines LE, Warholak TL, Grizzle AJ, Babits L, Clark C, et al. Ability of pharmacy clinical decision-support software to alert users about clinically important drug–drug interactions. J Am Med Inform Assoc. 2011;18(1):32–7.PubMedCrossRefPubMedCentralGoogle Scholar
  22. 22.
    Wong K, Yu SK, Holbrook A. A systematic review of medication safety outcomes related to drug interaction software. J Popul Ther Clin Pharmacol. 2010;17(2):e243–55.PubMedGoogle Scholar
  23. 23.
    Kuperman GJ, Bobb A, Payne TH, Avery AJ, Gandhi TK, Burns G, et al. Medication-related clinical decision support in computerized provider order entry systems: a review. J Am Med Inform Assoc. 2007;14(1):29–40.PubMedCrossRefPubMedCentralGoogle Scholar
  24. 24.
    Garg AX, Adhikari NK, McDonald H, Rosas-Arellano MP, Devereaux PJ, Beyene J, et al. Effects of computerized clinical decision support systems on practitioner performance and patient outcomes: a systematic review. JAMA. 2005;293(10):1223–38.PubMedCrossRefGoogle Scholar
  25. 25.
    Ucar A. Assessment of clinical relevance of alerts from EES used at an emergency department. Uppsala: Uppsala University; 2011 (In Swedish).Google Scholar
  26. 26.
    Hovstadius B, Astrand B, Petersson G. Dispensed drugs and multiple medications in the Swedish population: an individual-based register study. BMC Clin Pharmacol. 2009;9:11.PubMedCrossRefPubMedCentralGoogle Scholar
  27. 27.
    Rosholm JU, Bjerrum L, Hallas J, Worm J, Gram LF. Polypharmacy and the risk of drug–drug interactions among Danish elderly. A prescription database study. Dan Med Bull. 1998;45(2):210–3.PubMedGoogle Scholar
  28. 28.
    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.PubMedCrossRefPubMedCentralGoogle Scholar
  29. 29.
    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.PubMedCrossRefGoogle Scholar
  30. 30.
    Johnell Klarin. The relationship between number of drugs and potential drug–drug interactions in the elderly: a study of over 600,000 elderly patients from the swedish prescribed drug register. Drug Saf. 2007;30(10):911–8.PubMedCrossRefGoogle Scholar
  31. 31.
    Espinosa-Bosch M, Santos-Ramos B, Gil-Navarro MV, Santos-Rubio MD, Marin-Gil R, Villacorta-Linaza P. Prevalence of drug interactions in hospital healthcare. Int J Clin Pharm. 2012;34(6):807–17.PubMedCrossRefGoogle Scholar
  32. 32.
    Johnell K, Fastbom J. Multi-dose drug dispensing and inappropriate drug use: a nationwide register-based study of over 700000 elderly. Scand J Prim Health Care. 2008;26(2):86–91.PubMedCrossRefPubMedCentralGoogle Scholar
  33. 33.
    Sjoberg C, Edward C, Fastbom J, Johnell K, Landahl S, Narbro K, et al. Association between multi-dose drug dispensing and quality of drug treatment—a register-based study. PLoS One. 2011;6(10):e26574.PubMedCrossRefPubMedCentralGoogle Scholar
  34. 34.
    Wallerstedt SM, Fastbom J, Johnell K, Sjoberg C, Landahl S, Sundstrom A. Drug treatment in older people before and after the transition to a multi-dose drug dispensing system—a longitudinal analysis. PLoS One. 2013;8(6):e67088.PubMedCrossRefPubMedCentralGoogle Scholar
  35. 35.
    Sinnemaki J, Sihvo S, Isojarvi J, Blom M, Airaksinen M, Mantyla A. Automated dose dispensing service for primary healthcare patients: a systematic review. Syst Rev. 2013;2:1.PubMedCrossRefPubMedCentralGoogle Scholar
  36. 36.
    Gerber A, Stollenwerk B, Lauterbach KW, Stock S, Buscher G, Rath T, Lungen M. Evaluation of multi-dose repackaging for individual patients in long-term care institutions: savings from the perspective of statutory health insurance in Germany. Int J Pharm Pract. 2008;16:387–94.CrossRefGoogle Scholar
  37. 37.
    Sjoberg C, Ohlsson H, Wallerstedt SM. Association between multi-dose drug dispensing and drug treatment changes. Eur J Clin Pharmacol. 2012;68(7):1095–101.PubMedCrossRefGoogle Scholar
  38. 38.
    Coxe S, West SG, Aiken LS. The analysis of count data: a gentle introduction to poisson regression and its alternatives. J Pers Assess. 2009;91(2):121–36.PubMedCrossRefGoogle Scholar
  39. 39.
    Lao CK, Ho SC, Chan KK, Tou CF, Tong HH, Chan A. Potentially inappropriate prescribing and drug–drug interactions among elderly Chinese nursing home residents in Macao. Int J Clin Pharm. 2013;35(5):805–12.PubMedCrossRefGoogle Scholar
  40. 40.
    Johnell K, Weitoft GR, Fastbom J. Sex differences in inappropriate drug use: a register-based study of over 600,000 older people. Ann Pharmacother. 2009;43(7):1233–8.PubMedCrossRefGoogle Scholar
  41. 41.
    Olsson J, Bergman A, Carlsten A, Oke T, Bernsten C, Schmidt IK, et al. Quality of drug prescribing in elderly people in nursing homes and special care units for dementia: a cross-sectional computerized pharmacy register analysis. Clin Drug Investig. 2010;30(5):289–300.PubMedCrossRefGoogle Scholar
  42. 42.
    Ruggiero C, Lattanzio F, Dell’Aquila G, Gasperini B, Cherubini A. Inappropriate drug prescriptions among older nursing home residents: the Italian perspective. Drugs Aging. 2009;26(Suppl 1):15–30.PubMedCrossRefGoogle Scholar
  43. 43.
    Wahab MS, Nyfort-Hansen K, Kowalski SR. Inappropriate prescribing in hospitalised Australian elderly as determined by the STOPP criteria. Int J Clin Pharm. 2012;34(6):855–62.PubMedCrossRefGoogle Scholar
  44. 44.
    Heikkila T, Lekander T, Raunio H. Use of an online surveillance system for screening drug interactions in prescriptions in community pharmacies. Eur J Clin Pharmacol. 2006;62(8):661–5.PubMedCrossRefGoogle Scholar
  45. 45.
    Roughead EE, Kalisch LM, Barratt JD, Gilbert AL. Prevalence of potentially hazardous drug interactions amongst Australian veterans. Br J Clin Pharmacol. 2010;70(2):252–7.PubMedCrossRefPubMedCentralGoogle Scholar
  46. 46.
    Seidling HM, Schmitt SP, Bruckner T, Kaltschmidt J, Pruszydlo MG, Senger C, et al. Patient-specific electronic decision support reduces prescription of excessive doses. Qual Saf Health Care. 2010;19(5):e15.PubMedGoogle Scholar
  47. 47.
    Lindblad CI, Hanlon JT, Gross CR, Sloane RJ, Pieper CF, Hajjar ER, et al. Clinically important drug-disease interactions and their prevalence in older adults. Clin Ther. 2006;28(8):1133–43.PubMedCrossRefGoogle Scholar
  48. 48.
    Coleman JJ, van der Sijs H, Haefeli WE, Slight SP, McDowell SE, Seidling HM, et al. On the alert: future priorities for alerts in clinical decision support for computerized physician order entry identified from a European workshop. BMC Med Inform Decis Mak. 2013;13:111.PubMedCrossRefPubMedCentralGoogle Scholar

Copyright information

© Koninklijke Nederlandse Maatschappij ter bevordering der Pharmacie 2014

Authors and Affiliations

  • Hammar Tora
    • 1
    Email author
  • Hovstadius Bo
    • 1
  • Lidström Bodil
    • 2
  • Petersson Göran
    • 1
  • Eiermann Birgit
    • 2
    • 3
  1. 1.Department of Medicine and Optometry, eHealth InstituteLinnaeus UniversityKalmarSweden
  2. 2.Swedish eHealth AgencyStockholmSweden
  3. 3.Division of Clinical Pharmacology, Department of Laboratory MedicineKarolinska InstitutetStockholmSweden

Personalised recommendations