AMIA Annu Symp Proc - Identifying Deviations from Usual Medical Care using a Statistical Approach.

Tópicos

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Resumo

Developing methods to detect deviations from usual medical care may be useful in the development of automated clinical alerting systems to alert clinicians to treatment choices that warrant additional consideration. We developed a method for identifying deviations in medication administration in the intensive care unit that is based on learning logistic regression models from past patient data that when applied to current patient data identifies statistically unusual treatment decisions. The models predicted a total of 53 deviations for 6 medications on a set of 3000 patient cases. A set of 12 predicted deviations and 12 non-deviations was evaluated by a group of intensive care physicians. Overall, the predicted deviations were assessed to often warrant an alert and to be clinically useful, and furthermore, the frequency with which such alerts would be raised is not likely to be disruptive in a clinical setting.

Resumo Limpo

develop method detect deviat usual medic care may use develop autom clinic alert system alert clinician treatment choic warrant addit consider develop method identifi deviat medic administr intens care unit base learn logist regress model past patient data appli current patient data identifi statist unusu treatment decis model predict total deviat medic set patient case set predict deviat nondevi evalu group intens care physician overal predict deviat assess often warrant alert clinic use furthermor frequenc alert rais like disrupt clinic set

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