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Int J Clin Pharm ; 39(2): 386-393, 2017 Apr.
Article in English | MEDLINE | ID: mdl-28188508

ABSTRACT

Background The Screening Tool of Older Persons' Prescriptions/Screening Tool to Alert doctors to Right Treatment (STOPP/START) criteria is used to identify instances of potentially inappropriate prescribing in a patient's medication regimen. Objective To determine the prevalence and predictors of potentially inappropriate medications (PIMs) and potential prescribing omissions (PPOs) among elderly patients at hospital discharge. Setting A university hospital medical clinic in Brazil. Method Discharge prescriptions were examined using the STOPP/START criteria. Subjects were inpatients aged ≥60 years receiving at least one medication prior to hospitalization and with a history of cardiovascular disease. The prevalence of PIMs and PPOs was determined and a multivariable binary regression analysis was performed to identify independent predictors associated with PIMs or PPOs. Main outcome measure Prevalence of PIMs and PPOs. Results Of the 230 subjects, 13.9% were prescribed at least one PIM. The most frequently prescribed PIMs were glibenclamide or chlorpropamide prescribed for type 2 diabetes mellitus (31.0%), and aspirin at doses >150 mg/day (14.3%). Ninety patients had at least one PPO (39.1%). The most prevalent PPOs were statins (29.8%) and antiplatelet therapy (13.7%) for diabetes mellitus when coexisting major cardiovascular risk factors were present. No predictors for PIMs were found. In contrast, diabetes was a risk factor while dyslipidaemia was a protective factor for PPOs. Conclusion PIMs and PPOs commonly occur with elderly people at hospital discharge. Diabetes and dyslipidaemia were significantly associated with PPOs. Our findings show the need for interventions to reduce potentially inappropriate prescribing, such as a pharmacist medication review process at hospital discharge.


Subject(s)
Inappropriate Prescribing/statistics & numerical data , Potentially Inappropriate Medication List/statistics & numerical data , Aged , Aged, 80 and over , Brazil/epidemiology , Cross-Sectional Studies , Female , Humans , Male , Middle Aged , Patient Discharge , Prevalence , Risk Factors
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