Evaluating Automated Rules for Rapid Response System Alarm Triggers in Medical and Surgical Patients

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Abstract

BACKGROUND:

The use of rapid response systems (RRS), which were designed to bring clinicians with critical care expertise to the bedside to prevent unnecessary deaths, has increased. RRS rely on accurate detection of acute deterioration events. Early warning scores (EWS) have been used for this purpose but were developed using heterogeneous populations. Predictive performance may differ in medical vs surgical patients.

OBJECTIVE:

To evaluate the performance of published EWS in medical vs surgical patient populations.

DESIGN:

Retrospective cohort study.

SETTING:

Two tertiary care academic medical center hospitals in the Midwest totaling more than 1500 beds.

PATIENTS:

All patients discharged from January to December 2011.

INTERVENTION:

None.

MEASUREMENTS:

Time-stamped longitudinal database of patient variables and outcomes, categorized as surgical or medical. Outcomes included unscheduled transfers to the intensive care unit, activation of the RRS, and calls for cardiorespiratory resuscitation (“resuscitation call”). The EWS were calculated and updated with every new patient variable entry over time. Scores were considered accurate if they predicted an outcome in the following 24 hours.

RESULTS:

All EWS demonstrated higher performance within the medical population as compared to surgical: higher positive predictive value (P < .0001 for all scores) and sensitivity (P < .0001 for all scores). All EWS had positive predictive values below 25%.

CONCLUSIONS:

The overall poor performance of the evaluated EWS was marginally better in medical patients when compared to surgical patients.

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