Annals of Surgery

Skip Navigation LinksHome > December 2014 - Volume 260 - Issue 6 > Derivation and Validation of a Quality Indicator of Acute Ca...
Annals of Surgery:
doi: 10.1097/SLA.0000000000000648
Original Articles

Derivation and Validation of a Quality Indicator of Acute Care Length of Stay to Evaluate Trauma Care

Moore, Lynne PhD*,†; Stelfox, Henry Thomas MD, MSc, FRCPC; Turgeon, Alexis F. MD, MSc, FRCPC*,†,§; Nathens, Avery B. MD, PhD, MPH; Lavoie, André PhD†,¶; Émond, Marcel MD, MSc; Bourgeois, Gilles MD; Neveu, Xavier MSc

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Objective: To derive and internally validate a quality indicator (QI) for acute care length of stay (LOS) after admission for injury.

Background: Unnecessary hospital days represent an estimated 20% of total LOS implying an important waste of resources as well as increased patient exposure to hospital-acquired infections and functional decline.

Methods: This study is based on a multicenter, retrospective cohort from a Canadian provincial trauma system (2005–2010; 57 trauma centers; n = 57,524). Data were abstracted from the provincial trauma registry and the hospital discharge database. Candidate risk factors were identified by expert consensus and selected for model derivation using bootstrap resampling. The validity of the QI was evaluated in terms of interhospital discrimination, construct validity, and forecasting.

Results: The risk adjustment model explains 37% of the variation in LOS. The QI discriminates well across trauma centers (coefficient of variation = 0.02, 95% confidence interval: 0.011–0.028) and is correlated with the QI on processes of care (r = −0.32), complications (r = 0.66), unplanned readmissions (r = 0.38), and mortality (r = 0.35). Performance in 2005 to 2007 was predictive of performance in 2008 to 2010 (r = 0.80).

Conclusions: We have developed a QI on the basis of risk-adjusted LOS to evaluate trauma care that can be implemented with routinely collected data. The QI is based on a robust risk adjustment model with good internal and temporal validity, and demonstrates good properties in terms of discrimination, construct validity, and forecasting. This QI can be used to target interventions to reduce LOS, which will lead to more efficient resource use and may improve patient outcomes after injury.

Copyright © 2014 Wolters Kluwer Health, Inc. All rights reserved.


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