Design of a score to identify hospitalized patients at risk of drug‐related problems

Urbina, Olatz; Ferrández, Olivia; Grau, Santiago; Luque, S.; Mojal, Sergi; Marín-Casino, Mónica; Mateu-de-Antonio, Javier; Carmona, Ana T.; Conde-Estévez, David; Espona, Mercè; González, Elena; Riu, Marta; Salas, E.

doi:10.1002/pds.3634

Cited by 42 publications

(141 citation statements)

References 47 publications

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“…The number of drugs was the only associated factor remaining significant in the multivariate model. This result is in accordance with previous studies and the National Board of Health and Welfare in Sweden [4, 5, 34]. The complexity of polypharmacy causes problems for patients and provides a considerable challenge for healthcare professionals.…”

Section: Discussionsupporting

confidence: 92%

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Characterisation of Drug-Related Problems and Associated Factors at a Clinical Pharmacist Service-Naïve Hospital in Northern Sweden

Peterson

Gustafsson

2017

Drugs - Real World Outcomes

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BackgroundPolypharmacy and increased sensitivity to side effects cause adverse drug events, drug–drug interactions and medication errors in the elderly.ObjectiveThe objective of this study was to investigate the prevalence and type of drug-related problems and associated factors among patients admitted to a clinical pharmacist service-naïve medical ward in an inland hospital in northern Sweden.MethodsDuring September–November 2015 and February–April 2016, clinical pharmacists working as part of a ward team on the medical ward conducted 103 medication reviews. Drug-related problems were identified and classified. Associated factors, drug classes and specific drugs involved were also investigated.ResultsThe clinical pharmacists identified 133 drug-related problems in 66% [68/103] of the study population. The most common drug-related problems in this study were inappropriate drug use and interactions. Cardiovascular drugs and psychotropic drugs were most commonly involved. Drug-related problems were more frequently observed at higher age, increasing number of drugs prescribed and in patients with reduced renal function. In the multivariate analysis, only the number of prescribed drugs was still significant.ConclusionDrug-related problems were commonly observed among patients admitted to the medical ward. Medication reviews conducted by clinical pharmacists as part of a ward team resulted in several interventions to improve the patients’ drug treatment.

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Section: Discussionsupporting

confidence: 92%

“…The finding of higher age as a factor associated with DRPs is in line with previous studies [33, 34]. Further, reduced renal function has been shown in previous studies to be a risk factor for DRPs [35, 36].…”

Section: Discussionsupporting

confidence: 91%

Characterisation of Drug-Related Problems and Associated Factors at a Clinical Pharmacist Service-Naïve Hospital in Northern Sweden

Peterson

Gustafsson

2017

Drugs - Real World Outcomes

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“…Urbina et al . categorized age and number of medications using cut‐off points with the highest sensitivity and specificity . Zopf et al .…”

Section: Resultsmentioning

confidence: 99%

Systematic review of predictive risk models for adverse drug events in hospitalized patients

Falconer

Barras

Cottrell

2018

Brit J Clinical Pharma

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Keywords adverse drug events, adverse drug reactions, clinical pharmacology, clinical pharmacy, drug related problems, medication errors, predictive risk model, risk score AIMAn emerging approach to reducing hospital adverse drug events is the use of predictive risk scores. The aim of this systematic review was to critically appraise models developed for predicting adverse drug event risk in inpatients. METHODSEmbase, PubMed, CINAHL and Scopus databases were used to identify studies of predictive risk models for hospitalized adult inpatients. Studies had to have used multivariable logistic regression for model development, resulting in a score or rule with two or more variables, to predict the likelihood of inpatient adverse drug events. The Checklist for the critical Appraisal and data extraction for systematic Reviews of prediction Modelling Studies (CHARMS) was used to critically appraise eligible studies. RESULTSEleven studies met the inclusion criteria and were included in the review. Ten described the development of a new model, whilst one study revalidated and updated an existing score. Studies used different definitions for outcome but were synonymous with or closely related to adverse drug events. Four studies undertook external validation, five internally validated and two studies did not validate their model. No studies evaluated impact of risk scores on patient outcomes. CONCLUSIONAdverse drug event risk prediction is a complex endeavour but could help to improve patient safety and hospital resource management. Studies in this review had some limitations in their methods for model development, reporting and validation. Two studies, the BADRI and Trivalle's risk scores, used better model development and validation methods and reported reasonable performance, and so could be considered for further research.British Journal of Clinical Pharmacology Br J Clin Pharmacol (2018) 84 846-864 846

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“…To our knowledge, no algorithms exist that evaluate the risk of MEs by the use of risk scores. Other studies developed risk scores by the use of multiple regressions . Hohl et al .…”

Section: Discussionmentioning

confidence: 99%

Detection of Patients at High Risk of Medication Errors: Development and Validation of an Algorithm

Sædder

Lisby

Nielsen

et al. 2015

Basic Clin Pharma Tox

119

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Medication errors (MEs) are preventable and can result in patient harm and increased expenses in the healthcare system in terms of hospitalization, prolonged hospitalizations and even death. We aimed to develop a screening tool to detect acutely admitted patients at low or high risk of MEs comprised by items found by literature search and the use of theoretical weighting. Predictive variables used for the development of the risk score were found by the literature search. Three retrospective patient populations and one prospective pilot population were used for modelling. The final risk score was evaluated for precision by the use of sensitivity, specificity and area under the ROC (receiver operating characteristic) curves. The variables used in the final risk score were reduced renal function, the total number of drugs and the risk of individual drugs to cause harm and drug-drug interactions. We found a risk score in the prospective population with an area under the ROC curve of 0.76. The final risk score was found to be quite robust as it showed an area under the ROC curve of 0.87 in a recent patient population, 0.74 in a population of internal medicine and 0.66 in an orthopaedic population. We developed a simple and robust score, MERIS, with the ability to detect patients and divide them according to low and high risk of MEs in a general population admitted at acute admissions unit. The accuracy of the risk score was at least as good as other models reported using multiple regression analysis.

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Design of a score to identify hospitalized patients at risk of drug‐related problems

Abstract: Knowledge of the variables associated with DRP could aid their early detection in at-risk patients. The use of an application that can be continually updated in daily clinical practice helps to optimize resources.

Cited by 42 publications

References 47 publications

Characterisation of Drug-Related Problems and Associated Factors at a Clinical Pharmacist Service-Naïve Hospital in Northern Sweden

Characterisation of Drug-Related Problems and Associated Factors at a Clinical Pharmacist Service-Naïve Hospital in Northern Sweden

Systematic review of predictive risk models for adverse drug events in hospitalized patients

Detection of Patients at High Risk of Medication Errors: Development and Validation of an Algorithm

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