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Original article

Vol. 149 No. 3940 (2019)

Drug prescription patterns, polypharmacy and potentially inappropriate medication in Swiss nursing homes: a descriptive analysis based on claims data

  • Rahel Schneider
  • Daphne Reinau
  • Nadine Schur
  • Eva Blozik
  • Mathias Früh
  • Andri Signorell
  • Christoph R. Meier
  • Matthias Schwenkglenks
Cite this as:
Swiss Med Wkly. 2019;149:w20126



To date, comprehensive data on drug utilisation in Swiss nursing homes are lacking.


To describe drug prescription patterns, polypharmacy and potentially inappropriate medication (PIM) in Swiss nursing home residents (NHR).


Using administrative claims data provided by the Swiss health insurance company Helsana, we assessed drug claims and drug costs in 2016 in individuals aged ≥65 years and insured with Helsana, who were either NHR or living in the community (reference group, RG). In particular, we analysed the prevalence of polypharmacy (≥5 claims for different drugs during a 3-month period) and PIM use according to the 2015 Beers criteria and the PRISCUS list. We standardised the results to the Swiss population.


In 2016, NHR had on average nearly twice as many drug claims per capita as individuals in the RG (NHR 58.8; RG 30.8). The average per capita drug costs per day for NHR were low, but higher than in the RG (NHR CHF 8.55; RG CHF 5.45). The same pattern applied to the prevalence of polypharmacy (NHR 85.5%; RG 50.4%). Standardisation by age and sex did not materially alter these observations. Overall, 79.1% of NHR received ≥1 PIM, and 56.2% were long-term users (≥3 claims) of at least one PIM (based on the combined PRISCUS list and Beers criteria). Among all PIMs in nursing homes, quetiapine (antipsychotic agent), lorazepam (anxiolytic agent) and zolpidem (hypnotic agent) were the most prevalent (22.4, 20.2 and 13.0%, respectively).


The high prevalence of polypharmacy and PIM in Swiss nursing homes may indicate a need for interventions aiming at de-prescribing drugs with an unfavourable benefit-risk profile.


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