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High-risk medicines associated with clinically relevant medication-related problems in UK hospitals: A prospective observational study.


ABSTRACT: The aim of this prospective observational study was to establish associations between the use of high-risk medicine groups and the study outcome: occurrence of at least 1 moderate or severe preventable medication-related problem. Data on medication-related problems, high-risk medicines, and other potential risk factors were collected from adults on medical wards in 2 UK hospitals. Logistic regression modelling was used to determine relationships between high-risk medicines and the study outcome. Among 1503 eligible admissions, 6 high-risk medicine groups were associated with the study outcome on univariable analysis; multivariable analysis found only systemic antimicrobials and epilepsy medicines to be independently associated with the outcome (adjusted odds ratio 1.44, 95% confidence interval 1.08-1.92 and adjusted odds ratio 1.61, 95% confidence interval 1.16-2.25 respectively). Identification of high-risk medicine groups has potential to permit targeting of patients at highest risk of avoidable medication-related harm, but multivariable analysis suggests risk is likely to be multifactorial.

SUBMITTER: Geeson C 

PROVIDER: S-EPMC6983521 | biostudies-literature | 2020 Jan

REPOSITORIES: biostudies-literature

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High-risk medicines associated with clinically relevant medication-related problems in UK hospitals: A prospective observational study.

Geeson Cathy C   Wei Li L   Franklin Bryony Dean BD  

British journal of clinical pharmacology 20191217 1


The aim of this prospective observational study was to establish associations between the use of high-risk medicine groups and the study outcome: occurrence of at least 1 moderate or severe preventable medication-related problem. Data on medication-related problems, high-risk medicines, and other potential risk factors were collected from adults on medical wards in 2 UK hospitals. Logistic regression modelling was used to determine relationships between high-risk medicines and the study outcome.  ...[more]

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