AMIA ... Annual Symposium proceedings / AMIA Symposium. AMIA Symposium
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AMIA Annu Symp Proc · Jan 2007
Predicting ambulance diversion in an adult Emergency Department using a Gaussian process.
When the Emergency Department (ED) reaches a critical level of overcrowding, it diverts ambulances to other hospitals. We evaluated the accuracy of a Gaussian process for prediction of ambulance diversion using March 1, 2005 November 30, 2005 data. The area under the receiver operating curve (AUC) for 120 minutes in advance was 0.93 (SE: 0.19). The instrument demonstrated a high AUC and may be used to alert ED managers earlier of a diversion episode.
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Predicting hospital admission for Emergency Department (ED) patients at the time of triage may improve throughput. To predict admission we created and validated a Bayesian Network from 47,993 encounters (training: n=23,996, validation: n=9,599, test: n=14,398). The area under the receiver operator characteristic curve was 0.833 (0.8260.840) for the network and 0.790 (0.7810.799) for the control variable (acuity only). Predicting hospital admission early during an encounter may help anticipate ED workload and potential overcrowding.
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AMIA Annu Symp Proc · Jan 2007
Migrating toward a next-generation clinical decision support application: the BJC HealthCare experience.
The next-generation model outlined in the AMIA Roadmap for National Action on Clinical Decision Support (CDS) is aimed to optimize the effectiveness of CDS interventions, and to achieve widespread adoption. BJC HealthCare re-engineered its existing CDS system in alignment with the AMIA roadmap and plans to use it for guidance on further enhancements. ⋯ Rules were separated from execution code and made customizable for multi-facility deployment. Those changes resulted in system improvement in the short term while aligning with long-term strategic objectives.
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AMIA Annu Symp Proc · Jan 2007
Extraction and mapping of drug names from free text to a standardized nomenclature.
Free text fields are often used to store clinical drug data in electronic health records. The use of free text facilitates rapid data entry by the clinician. Errors in spelling, abbreviations, and jargon, however, limit the utility of these data. ⋯ Overall sensitivity and specificity for the validation set were 92.2% and 95.7% respectively. The mains sources of error were misspellings and unknown but valid drug names. These preliminary results demonstrate that free text clinical drug data can be efficiently extracted and mapped to a controlled drug nomenclature.
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Shifts in the supply of and demand for emergency department (ED) services have led to ED overcrowding and make the efficient allocation of ED resources increasingly important. Reliable means of modeling and forecasting the demand for resources are critical to any ED resource planning strategy. Vector Autoregression (VAR) is a flexible multivariate time-series forecasting methodology that is well suited to modeling demand for resources in the ED.