Prescribing potentially inappropriate medication (PIM) in Germany's elderly as indicated by the PRISCUS list. An analysis based on regional claims data

Pharmacoepidemiol Drug Saf. 2013 Jul;22(7):719-27. doi: 10.1002/pds.3429. Epub 2013 Apr 12.

Abstract

Purpose: The aim of this study was to estimate the prevalence of potentially inappropriate medication (PIM) in the elderly as indicated by Germany's recently published list (PRISCUS) and to assess factors independently associated with PIM prescribing, both overall and separately for therapeutic groups.

Methods: Claims data analysis (Health Insurance Sample AOK Hesse/KV Hesse, 18.75% random sample of insurants from AOK Hesse, Germany) is used in the study. The study population is composed of 73,665 insurants >64 years of age continuously insured in the last quarter of 2009 and either continuously insured or deceased in 2010. Prevalence estimates are standardized to the population of Germany (31 December 2010). The variables age, sex, polypharmacy, hospital stay and nursing care are assessed for their independent association with general PIM prescription and among 11 therapeutic subgroups using multivariate logistic regression analysis.

Results: In 2010, 22.0% of the elderly received at least one PIM prescription (men: 18.3%, women: 24.8%). The highest PIM prevalence was observed for antidepressants (6.5%), antihypertensives (3.8%) and antiarrhythmic drugs (3.5%). Amitriptyline, tetrazepam, doxepin, acetyldigoxin, doxazosin and etoricoxib were the most frequently prescribed PIMs. Multivariate analyses indicate that women (OR 1.39; 95% CI: 1.34-1.44) and persons with extreme polypharmacy (≥10 vs. <5 drugs: OR 5.16; 95% CI: 4.87-5.47) were at higher risk for receiving a PRISCUS-PIM. Risk analysis for therapeutic groups shows divergent associations.

Conclusion: PRISCUS-PIMs are widely used. Educational programs should focus on drugs with high treatment prevalence and call professionals' attention to those elderly patients who are at special risk for inappropriate medication.

Keywords: claims data; elderly; pharmacoepidemiology; potentially inappropriate medication; prevalence; risk factors.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Age Factors
  • Aged
  • Aged, 80 and over
  • Chi-Square Distribution
  • Data Mining
  • Databases, Factual / statistics & numerical data
  • Drug Prescriptions / statistics & numerical data
  • Female
  • Germany
  • Humans
  • Inappropriate Prescribing / statistics & numerical data*
  • Logistic Models
  • Male
  • Multivariate Analysis
  • Odds Ratio
  • Pharmacoepidemiology
  • Pharmacovigilance
  • Polypharmacy
  • Risk Factors
  • Sex Factors