Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2017 Aug;45(8):e758-e762.
doi: 10.1097/CCM.0000000000002374.

Validation of an Administrative Definition of ICU Admission Using Revenue Center Codes

Gary E Weissman  1 , Rebecca A Hubbard, Rachel Kohn, George L Anesi, Scott Manaker, Meeta Prasad Kerlin, Scott D Halpern
Affiliations

Validation of an Administrative Definition of ICU Admission Using Revenue Center Codes

Gary E Weissman et al. Crit Care Med. 2017 Aug.

Abstract

Objectives: 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 (χ = 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.

PubMed Disclaimer

Conflict of interest statement

Dr. Kohn has disclosed that she does not have any potential conflicts of interest.

Figures

Figure 1
Figure 1. Classification of hospital admissions as having or not having an intensive care unit (ICU) admission using commonly available administrative data
Abbreviations: ICU = intensive care unit, RCC = revenue center code, DRG = diagnosis related group. High-risk DRG codes include: 64, 65, 189, 193, 208, 247, 280, 287, 291, 292, 309, 310, 313, 378, 638, 682, 871, and 918.
See this image and copyright information in PMC

References

    1. Iwashyna TJ, Odden A, Rohde J, et al. Identifying patients with severe sepsis using administrative claims: Patient-level validation of the Angus implementation of the International Consensus Conference definition of severe sepsis. Med Care. 2014;52:e39–43. - PMC - PubMed
    1. Kerlin MP, Weissman GE, Wonneberger KA, et al. Validation of administrative definitions of invasive mechanical ventilation across 30 ICUs. Am J Resp Crit Care Med. 2016 In press. - PMC - PubMed
    1. Barrett M, Smith M, Elixhauser A, et al. Utilization of intensive care services, 2011. Agency for Healthcare Research and Quality Statistical Brief. 2014;185:1–14. - PubMed
    1. Kersten A, Milbrandt E, Rahim M, et al. How big is critical care in the US? Crit Care Med. 2003;31:A8.
    1. Wunsch H, Angus DC, Harrison DA, et al. Variation in critical care services across North America and Western Europe. Crit Care Med. 2008;36:2787–2793. - PubMed

MeSH terms