In an ED, caADEs are frequent, and a significant proportion of these events and their related costs appear to be predictable and preventable. The ED as a first-line provider for ADE cases appears to be an appropriate environment to implement strategic and operative improvements for enhanced patient safety.

Elderly patients more frequently suffer from ADR and from the clinical consequences of medication errors. Elderly patients taking PIMs are more likely to suffer from ADRs and MEs, even though most drug-related events are still attributable to non-PIM.

The Pareto principle provides a method for identifying the locally most relevant ADE, ME, and involved drugs. This permits subsequent development of interventions to increase patient safety in the ED admission process that best suit local needs.

AIMSThe incidence of clinical events related to medication errors and/or adverse drug reactions reported in the literature varies by a degree that cannot solely be explained by the clinical setting, the varying scrutiny of investigators or varying definitions of drug-related events. Our hypothesis was that the individual complexity of many clinical cases may pose relevant limitations for current definitions and algorithms used to identify, classify and count adverse drug-related events. METHODSBased on clinical cases derived from an observational study we identified and classified common clinical problems that cannot be adequately characterized by the currently used definitions and algorithms. RESULTSIt appears that some key models currently used to describe the relation of medication errors (MEs), adverse drug reactions (ADRs) and adverse drug events (ADEs) can easily be misinterpreted or contain logical inconsistencies that limit their accurate use to all but the simplest clinical cases. A key limitation of current models is the inability to deal with complex interactions such as one drug causing two clinically distinct side effects or multiple drugs contributing to a single clinical event. Using a large set of clinical cases we developed a revised model of the interdependence between MEs, ADEs and ADRs and extended current event definitions when multiple medications cause multiple types of problems. We propose algorithms that may help to improve the identification, classification and counting of drug-related events. CONCLUSIONSThe new model may help to overcome some of the limitations that complex clinical cases pose to current paper-or software-based drug therapy safety.

BackgroundAlthough usage and acceptance are important factors for a successful implementation of clinical decision support systems for medication, most studies only concentrate on their design and outcome. Our objective was to comparatively investigate a set of traditional medication safety measures such as medication safety training for physicians, paper-based posters and checklists concerning potential medication problems versus the additional benefit of a computer-assisted medication check. We concentrated on usage, acceptance and suitability of such interventions in a busy emergency department (ED) of a 749 bed acute tertiary care hospital.MethodsA retrospective, qualitative evaluation study was conducted using a field observation and a questionnaire-based survey. Six physicians were observed while treating 20 patient cases; the questionnaire, based on the Technology Acceptance Model 2 (TAM2), has been answered by nine ED physicians.ResultsDuring field observations, we did not observe direct use of any of the implemented interventions for medication safety (paper-based and electronic). Questionnaire results indicated that the electronic medication safety check was the most frequently used intervention, followed by checklist and posters. However, despite their positive attitude, physicians most often stated that they use the interventions in only up to ten percent for subjectively “critical” orders. Main reasons behind the low usage were deficits in ease-of-use and fit to the workflow. The intention to use the interventions was rather high after overcoming these barriers.ConclusionsMethodologically, the study contributes to Technology Acceptance Model (TAM) research in an ED setting and confirms TAM2 as a helpful diagnostic tool in identifying barriers for a successful implementation of medication safety interventions. In our case, identified barriers explaining the low utilization of the implemented medication safety interventions - despite their positive reception - include deficits in accessibility, briefing for the physicians about the interventions, ease-of-use and compatibility to the working environment.