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Predictive Model Effective at Identifying High-Risk Patients

Commonwealth Fund–supported researchers led by Carlos A. Alvarez of Texas Tech University developed and piloted a predictive model for identifying hospital patients who are not in the intensive care unit but are nonetheless at high risk of cardiac arrest or another potentially fatal event. The study, published in BMC Medical Informatics and Decision Making, found that the model was better at predicting serious adverse events than systems relying solely on human judgment.

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