Detection of potentially inappropriate prescribing in the very old: cross-sectional analysis of the data from the BELFRAIL observational cohort study

BMC Geriatr. 2015 Dec 2;15:156. doi: 10.1186/s12877-015-0149-2.

Abstract

Background: Little is known about the prevalence and clinical importance of potentially inappropriate prescribing instances (PIPs) in the very old (>80 years). The main objective was to describe the prevalence of PIPs according to START (Screening Tool to Alert doctors to Right Treatment; omissions) and,STOPP (Screening Tool of Older Person's Prescriptions; over/misuse) and the Beers list (over/misuse). Secondary objectives were to identify determinants if PIPs and to assess the clinical importance to modify the treatment in case of PIPs.

Methods: Cross-sectional analysis of baseline data of the BELFRAIL cohort, which included 567 Belgian patients aged 80 and older in primary care. Two independent researchers applied the screening tools to the study population to detect PIPs. Next, a multidisciplinary panel of experts rated the clinical importance of the PIPs on a subsample of 50 patients.

Results: In this very old population (median age 84 years, 63 % female), the screening detected START-PIPs in 59 % of patients, STOPP-PIPs in 41 % and Beers-PIPs in 32 %. Assessment of the clinical importance revealed that the most frequent PIPs were of moderate or major importance. In 28 % of the subsample, the relevance of the PIP was challenged by the global medical, functional and social background of the patient hence the validity of some criteria was questioned.

Conclusion: Potentially inappropriate prescribing is highly prevalent in the very old. A good understanding of the patients' medical, functional and social context is crucial to assess the actual appropriateness of drug treatment.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Aged, 80 and over
  • Belgium
  • Cohort Studies
  • Cross-Sectional Studies
  • Female
  • Humans
  • Inappropriate Prescribing* / prevention & control
  • Inappropriate Prescribing* / statistics & numerical data
  • Male
  • Medical Order Entry Systems / statistics & numerical data
  • Potentially Inappropriate Medication List / statistics & numerical data
  • Practice Patterns, Physicians'* / standards
  • Practice Patterns, Physicians'* / statistics & numerical data
  • Prevalence
  • Primary Health Care* / methods
  • Primary Health Care* / standards