Literature DB >> 18693867

Utility of commonly captured data from an EHR to identify hospitalized patients at risk for clinical deterioration.

Abel Kho1, David Rotz, Kinan Alrahi, Wendy Cárdenas, Kristin Ramsey, David Liebovitz, Gary Noskin, Chuck Watts.   

Abstract

Rapid Response Teams (RRTs) respond to critically ill patients in the hospital. Activation of RRTs is highly subjective and misses a proportion of at-risk patients. We created an automated scoring system for non-ICU inpatients based on readily available electronic vital signs data, age, and body mass index. Over two weeks, we recorded scores on 1,878 patient with a range of scores from 0 to 10. Fifty patients reached the primary outcome of code call, cardiopulmonary arrest, or transfer to an ICU. Using a cutoff score of 4 or greater would result in identification of an additional 20 patients over the 7 patients identified by the current method of RRT activation. The area under the Receiver Operating Curve for the prediction model was 0.72 which compared favorably to other scoring systems. An electronic scoring system using readily captured EMR data may improve identification of patients at risk for clinical deterioration.

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Year:  2007        PMID: 18693867      PMCID: PMC2655808     

Source DB:  PubMed          Journal:  AMIA Annu Symp Proc        ISSN: 1559-4076


  17 in total

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  10 in total

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5.  Learning to predict post-hospitalization VTE risk from EHR data.

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6.  Patient acuity rating: quantifying clinical judgment regarding inpatient stability.

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Review 9.  Risk stratification of hospitalized patients on the wards.

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10.  Predicting out of intensive care unit cardiopulmonary arrest or death using electronic medical record data.

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  10 in total

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