Evaluation of two European risk models for predicting medication harm in an Australian patient cohort.
Adverse drug events
Adverse drug reactions
Clinical pharmacology
Clinical pharmacy
Medication harm
Predictive risk model
Predictive risk score
Risk prediction
Journal
European journal of clinical pharmacology
ISSN: 1432-1041
Titre abrégé: Eur J Clin Pharmacol
Pays: Germany
ID NLM: 1256165
Informations de publication
Date de publication:
Apr 2022
Apr 2022
Historique:
received:
23
08
2021
accepted:
16
12
2021
pubmed:
19
1
2022
medline:
19
3
2022
entrez:
18
1
2022
Statut:
ppublish
Résumé
To externally evaluate the performance of two European risk prediction models, for identifying patients at high-risk of medication harm, in an Australian hospital setting. This was a secondary analysis of a pre-existing cohort study described in a recently published study by Falconer et al. (Br J Clin Pharmacol 87(3):1512-1524, 2021) describing the development of a predictive risk model for inpatient medication harm. We retrospectively extracted relevant variables using the electronic health records of general medical and geriatric patients admitted to a quaternary hospital, in Brisbane, over 6 months from July to December 2017. This dataset was used to externally evaluate the two European models, The Brighton Adverse Drug Reaction Risk (BADRI) model by Tangiisuran et al. and a risk model developed by Trivalle et al. The variables were entered into both models and the patients' risk of medication harm was calculated, and compared with actual patient outcomes. Predictive performance was evaluated by measuring area under the receiver operative characteristic (AuROC) curves. The Australian patient cohort included 1982 patients (median age 74 years), of which 136 (7%) patients experienced ≥ 1 medication harm event(s). External evaluation of the two European models identified that both the BADRI and the Trivalle models had reduced predictive performance in an Australian patient cohort, compared with their original studies (AuROC of 0.63 [95% CI: 0.58-0.68] and 0.60 [95% CI: 0.55-0.65], respectively). Neither model demonstrated sufficient discrimination to warrant further evaluation in our local setting. This is likely a result of variations between the development and the validation cohorts, and the change in healthcare systems over time, and highlights the need for an up-to-date and context-specific risk prediction model.
Identifiants
pubmed: 35041044
doi: 10.1007/s00228-021-03271-1
pii: 10.1007/s00228-021-03271-1
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
679-686Subventions
Organisme : The University of Queensland
ID : PhD Scholarship (RTP)
Informations de copyright
© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.
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