Internal and emergency medicine
-
Especially in the emergency department (ED), it is critical to identify weaknesses in prescribing behavior of IV maintenance fluids to ensure a qualitative 24-h fluid management plan. The primary aim of this study was to develop an audit instrument to assess the pitfalls in documentation and prescribing habits of IV fluid therapy for non-critically ill patients admitted to the ED. In this study, an expert panel initially designed the tool. ⋯ Criterion related validity of the final version was high (93.4%). To conclude, the instrument is considered reliable and can be used in clinical practice to evaluate ED fluid management. Thorough documentation is essential to evaluate the appropriateness of the IV fluid prescription, to improve information transfer on IV fluid therapy to the ward and to facilitate retrospective chart review of ED prescribing behavior.
-
Predict in advance the need for hospitalization of adult patients for fall-related fractures based on information available at the time of triage to help decision-making at the emergency department (ED). ⋯ Using limited data available at the time of triage, we developed four machine learning models aimed at predicting hospitalization for patients presenting to the ED for fall-related fractures. All the four models were robust and performed well. Neural network method, however, performed the best for both pre- and post-models. Simple, parsimonious machine learning models can provide high accuracy for predicting hospital admission.