Potentially inappropriate medications (PIMs): frequency and extent of GP-related variation in PIMs: a register-based cohort study

Abstract

Objectives: Potentially inappropriate medications (PIMs) pose an increasing challenge in the ageing population. We aimed to assess the extent of PIMs and the prescriber-related variation in PIM prevalence.

Design: Nationwide register-based cohort study.

Setting: General practice.

Participants: The 4.2 million adults listed with general practitioner (GP) clinics in Denmark (n=1906) in 2016.

Main outcome measures: We estimated the patients' time with PIMs by using 29 register-operationalised STOPP criteria linking GP clinics and redeemed prescriptions. For each criterion and each GP clinic, we calculated ratios between the observed PIM time and that predicted by multivariate Poisson regressions on the patients. The observed variation was measured as the 90th/10th percentile ratios of these ratios. The extent of expectable random variation was assessed as the 90th/10th percentile ratios in randomly sampled GP populations (ie, the sampled variation). The GP-related excess variation was calculated as the ratio between the observed variation and sampled variation. The linear correlation between the observed/expected ratio for each of the criteria and the observed/expected ratio of total PIM time (for each clinic) was measured by Pearson's rho.

Results: Overall, 294 542 individuals were exposed to 1 44 117 years of PIMs. The two most prevalent PIMs were long-term use (>3 months) of non-steroidal anti-inflammatory drugs (51 074 years of PIMs) or benzodiazepines (48 723 years of PIMs). These two criteria showed considerable excess variation of 2.33 and 3.05, respectively; for total PIMs, this figure was 1.65. For more than half of the criteria, we observed a positive correlation between the specific PIM and the sum of remaining PIMs.

Conclusions: This study documents considerable variations in the prescribing practice of GPs for certain PIMs. These findings highlight a need for exploring the causal explanations for such variations, which could be markers of suboptimal GP-prescribing strategies.

Keywords: clinical pharmacology; epidemiology; general medicine (see internal medicine); primary care; public health; statistics & research methods.