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

Abel N Kho*, David Rotz, Kinan Alrahi, Wendy Cárdenas, Kristin Ramsey, David Liebovitz, Gary A Noskin, Chuck Watts

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

24 Scopus citations

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.

Original languageEnglish (US)
Pages (from-to)404-408
Number of pages5
JournalAMIA ... Annual Symposium proceedings / AMIA Symposium. AMIA Symposium
StatePublished - Dec 1 2007

ASJC Scopus subject areas

  • Medicine(all)

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