Longitudinal prevalence of potentially inappropriate medicines and potential prescribing omissions in a cohort of community-dwelling older people.

Research paper by Frank F Moriarty, Kathleen K Bennett, Tom T Fahey, Rose Anne RA Kenny, Caitriona C Cahir

Indexed on: 11 Feb '15Published on: 11 Feb '15Published in: European Journal of Clinical Pharmacology


This study aims to compare the prevalence of potentially inappropriate medicines (PIMs) and potential prescribing omissions (PPOs) using several screening tools in an Irish community-dwelling older cohort, to assess if the prevalence changes over time and to determine factors associated with any change.This is a prospective cohort study of participants aged ≥65 years in The Irish Longitudinal Study on Ageing (TILDA) with linked pharmacy claims data (n = 2051). PIM and PPO prevalence was measured in the year preceding participants' TILDA baseline interviews and in the year preceding their follow-up interviews using the Screening Tool for Older Persons' Prescriptions (STOPP), Beers criteria (2012), Assessing Care of Vulnerable Elders (ACOVE) indicators and the Screening Tool to Alert doctors to Right Treatment (START). Generalised estimating equations were used to determine factors associated with change in prevalence over time.Depending on the screening tool used, between 19.8% (ACOVE indicators) and 52.7% (STOPP) of participants received a PIM at baseline, and PPO prevalence ranged from 38.2% (START) to 44.8% (ACOVE indicators), while 36.7% of participants had both a PIM and PPO. Common criteria were aspirin for primary prevention (19.6%) and omission of calcium/vitamin D in osteoporosis (14.7%). Prevalence of PIMs and PPOs increased at follow-up (PIMs range 22-56.1%, PPOs range 40.5-49.3%), and this was associated with patient age, female sex, and numbers of medicines and chronic conditions.Sub-optimal prescribing is common in older patients. Ongoing prescribing review to optimise care is important, particularly as patients get older, receive more medicines or develop more illnesses.

More like this: