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

Abstract

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.

Influence of the medication environment on the unsafe medication behaviour of nurses: A path analysis

“…Patient safety, particularly medication safety, has become a focus of worldwide attention (Huynh, Wong, Correa‐West, Terry, & McCarthy, ; Pawluk et al., ). Medication errors are one of the most common causes of patient injury; of these errors, 46% are preventable (Saedder et al., ; Smeulers et al., ). As direct practitioners and observers of drug treatment, nurses spend approximately 40% of their work time performing drug therapy (Kavanagh, ).…”

Medicines Optimisation Assessment Tool (MOAT): a prognostic model to target hospital pharmacists' input to improve patient outcomes. Protocol for an observational study

“…Tools such as cardiac-risk calculators and the Waterlow score (to assess the risk of pressure ulcers) are both used daily across the NHS. 31 32 Prediction tools to identify hospitalised patients at risk of adverse medication-related outcomes have been developed, 33–41 but the majority identify patients at risk of adverse drug reactions, 34 35 adverse drug events 36 or medication errors, 37 rather than MRPs, or are based on ‘expert opinion’ rather than statistical determination. 38–41…”

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

“…Previous research has identified medicines that are potentially high‐risk when used in a hospital inpatient setting, but direct comparison between sources is difficult due to differences in study design, outcome measures, and the way medicines were grouped. To our knowledge, the present study is the first to identify high‐risk medicines that are associated with moderate or severe preventable MRPs.…”

“…High‐risk medicines were grouped into 11 categories (Table ), selected based on previously published research . Grouping was used rather than considering medicines individually since different organisations are likely to use different specific medicines.…”

“…Previous research has identified medicines that are potentially high‐risk when used in a hospital inpatient setting, but no statistical assessment of high‐risk medicines and clinically relevant medication‐related problems (MRPs) has yet been conducted. Statistical assessment has potential to quantify the impact of groups of high‐risk medicines on the risk of developing clinically relevant MRPs, and to explore potential correlation between high‐risk medicines and other risk factors such as age and renal function.…”