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Current Aging Science

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ISSN (Print): 1874-6098
ISSN (Online): 1874-6128

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Research Article

STOPP-START Criteria Used to Identify the Elderly Population Prone to Potentially Inadequate Prescribing in a Colombian Cohort

Author(s): Loren Zambrano, Rosa-Helena Bustos*, Edgar Beltran, Daniel Gomez, Sara Arias and Wilson Briceño

Volume 17, Issue 2, 2024

Published on: 16 January, 2024

Page: [135 - 143] Pages: 9

DOI: 10.2174/0118746098274486231227101704

Price: $65

Abstract

Background: Elderly people have multiple comorbidities that often require treatment with multiple medications. Having strategies to lessen the risks associated with pharmacological interactions and potentially inadequate prescribing (PIP) is of major importance. The STOPP– START criteria are useful in identifying PIP along with other tools, such as LASA (look alike/sound alike) drugs and high-risk medications (HRM).

Objective: We aimed to clinically and sociodemographically characterize the population with PIP according to the STOPP–START criteria in hospitalized elderly patients over 6 months in a third-level hospital in Colombia, South America. We also aimed to calculate the prevalence of PIP, LASA drugs and HRM and to identify other problems related with medication. Finally, we proposed an algorithm for the identification of PIP in this population.

Methods and Materials: This was a descriptive, cross-sectional study in hospitalized patients older than 60 years during the first semester of 2021 to identify PIP according to STOPP– START criteria. An analysis of clinical and sociodemographic variables was conducted, as well as the construction of an algorithm to identify PIP in the elderly in a semiautomated way. Data were collected and analyzed using the software SPSS 2021, using descriptive statistics and measures of central tendency.

Results: The prevalence of PIP in the study population was 25%. Furthermore, 60% of patients had one problem related to medication, and 27% used at least one LASA drug or HRM.

Conclusion: This study allows one to characterize, for the first time, the Colombian population prone to PIP, as well as the construction of an algorithm that identifies PIP in a semiautomated way.

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