Describe the operating characteristics of a proposed set of revenue center codes to correctly identify ICU stays among hospitalized patients.Design:
Retrospective cohort study. We report the operating characteristics of all ICU-related revenue center codes for intensive and coronary care, excluding nursery, intermediate, and incremental care, to identify ICU stays. We use a classification and regression tree model to further refine identification of ICU stays using administrative data. The gold standard for classifying ICU admission was an electronic patient location tracking system.Setting:
The University of Pennsylvania Health System in Philadelphia, PA, United States.Patients:
All adult inpatient hospital admissions between July 1, 2013, and June 30, 2015.Interventions:
None.Measurements and Main Results:
Among 127,680 hospital admissions, the proposed combination of revenue center codes had 94.6% sensitivity (95% CI, 94.3–94.9%) and 96.1% specificity (95% CI, 96.0–96.3%) for correctly identifying hospital admissions with an ICU stay. The classification and regression tree algorithm had 92.3% sensitivity (95% CI, 91.6–93.1%) and 97.4% specificity (95% CI, 97.2–97.6%), with an overall improved accuracy (χ2 = 398; p < 0.001).Conclusions:
Use of the proposed combination of revenue center codes has excellent sensitivity and specificity for identifying true ICU admission. A classification and regression tree algorithm with additional administrative variables offers further improvements to accuracy.