title: [Potentially inappropriate medication in elderly primary care patients : A retrospective, longitudinal analysis].
abstract: BACKGROUND
  Elderly people are often burdened by several diseases. This accounts for a higher medication intake and increases the risk of adverse drug events. To minimize this risk, several lists (Beers, PRISCUS) have been published of drugs that elderly patients should not take. We present a longitudinal analysis of the use of potentially inappropriate medication (PIM) over a period 4.5 years in a cohort of patients aged 75 years or more.
  
  
  METHODS
  Data were collected from the prospective, multicenter, observational study "German Study on Ageing, Cognition and Dementia in Primary Care Patients (AgeCoDe)," initially enrolling 3,327 patients. We investigated the prevalence of PIM by checking medications during visits to patients' homes. Furthermore, we analyzed the use of individual PIM agents over time.
  
  
  RESULTS
  At baseline, we found a PIM prevalence of 29 % according to the PRISCUS list, which decreased to 25.0 % 4.5 years later (χ(2): 7.87, p = 0.004). The Beers list yielded a prevalence of 21 % at baseline, decreasing after 4.5 years to 17.1 % (χ(2): 10.77, p = 0.000). A time-dependent multilevel model confirmed these results. Older age, depression, and the use of numerous prescribed agents are independent risk factors for using a PRISCUS-PIM.
  
  
  CONCLUSIONS
  Our results seem to support a trend toward a more rational drug therapy because fewer patients were prescribed PIM. Thus, for the individual patient, the risk of adverse effects and side effects is reduced as are the costs of these effects.
authors.affiliation: Institut für Allgemeinmedizin, Universitätsklinikum Hamburg-Eppendorf, Martinistr. 52, 20246, Hamburg, Deutschland. t.zimmermann@uke.de
authors.forename: T
authors.initials: T
authors.lastname: Zimmermann
authors.forename: H
authors.initials: H
authors.lastname: Kaduszkiewicz
authors.forename: H
authors.initials: H
authors.lastname: van den Bussche
authors.forename: G
authors.initials: G
authors.lastname: Schön
authors.forename: C
authors.initials: C
authors.lastname: Brettschneider
authors.forename: H-H
authors.initials: HH
authors.lastname: König
authors.forename: B
authors.initials: B
authors.lastname: Wiese
authors.forename: H
authors.initials: H
authors.lastname: Bickel
authors.forename: E
authors.initials: E
authors.lastname: Mösch
authors.forename: M
authors.initials: M
authors.lastname: Luppa
authors.forename: S
authors.initials: S
authors.lastname: Riedel-Heller
authors.forename: J
authors.initials: J
authors.lastname: Werle
authors.forename: S
authors.initials: S
authors.lastname: Weyerer
authors.forename: A
authors.initials: A
authors.lastname: Fuchs
authors.forename: M
authors.initials: M
authors.lastname: Pentzek
authors.forename: B
authors.initials: B
authors.lastname: Hänisch
authors.forename: W
authors.initials: W
authors.lastname: Maier
authors.forename: M
authors.initials: M
authors.lastname: Scherer
authors.forename: F
authors.initials: F
authors.lastname: Jessen
mesh_terms: D017677:Age Distribution; D000368:Aged; D000369:Aged, 80 and over; D003863:Depression / Q000188:drug therapy* / Q000453:epidemiology*; D005260:Female; D005858:Germany / Q000453:epidemiology; D006299:Health Services for the Aged / Q000706:statistics & numerical data* / Q000639:trends; D006801:Humans; D057970:Inappropriate Prescribing / Q000706:statistics & numerical data* / Q000639:trends; D008137:Longitudinal Studies; D008297:Male; D019338:Polypharmacy; D011320:Primary Health Care / Q000706:statistics & numerical data* / Q000639:trends; D012189:Retrospective Studies; D012307:Risk Factors; D017678:Sex Distribution