• JAMA surgery · Jul 2016

    Multicenter Study

    Derivation and Validation of a Quality Indicator to Benchmark In-Hospital Complications Among Injury Admissions.

    • Lynne Moore, François Lauzier, Henry T Stelfox, John Kortbeek, Richard Simons, Simon Berthelot, Julien Clément, Gilles Bourgeois, and Alexis F Turgeon.
    • Department of Social and Preventive Medicine, Université Laval, Quebec, Quebec, Canada2Population Health and Optimal Health Practices Research Unit, Trauma-Emergency-Critical Care Medicine, Centre de Recherche du Centre Hospitalier Universitaire de Québec.
    • JAMA Surg. 2016 Jul 1; 151 (7): 622-30.

    ImportanceThe rate of complications among injury admissions has been estimated to be more than 3 times that observed for general admissions, and complications have been targeted as an important quality-of-care metric. Despite the negative effect of complications on resource use and patient mortality and morbidity, there is no standardized method to benchmark trauma centers in terms of in-hospital complications, to our knowledge.ObjectivesTo develop a quality indicator (QI) for in-hospital complications that can be used to evaluate the quality of acute injury care and to assess its validity.Design, Setting, And ParticipantsMulticenter retrospective cohort study. The setting was a well-established inclusive trauma system in Canada. Participants included all 66 048 moderate or major injury admissions to an adult trauma center between April 1, 2006, and March 31, 2012. The dates of the analysis were January to April 2015.Main Outcomes And MeasuresThe primary outcome was the occurrence of at least 1 in-hospital complication. We selected risk-adjustment variables by expert consultation and bootstrap resampling. We evaluated internal validity using measures of discrimination, construct validity, and forecasting.ResultsThe study cohort comprised 66 048 patients. Their mean (SD) age was 59 (22) years, and 48.0% were female. Fifteen percent of patients had at least 1 in-hospital complication. The risk-adjustment model has excellent discrimination (area under the curve, 0.81) and calibration. The QI was correlated with the risk-adjusted incidence of mortality (r = 0.71), unplanned readmission (r = 0.43), and mean length of stay (r = 0.68). Hospital performance on the QI from 2007 to 2009 was predictive of performance from 2010 to 2012 (r = 0.82).Conclusions And RelevanceWe developed a QI to benchmark trauma centers on in-hospital complications among injury admissions. The QI is based on data that are routinely collected in most trauma systems and demonstrates good internal validity. The integration of this QI in trauma quality improvement programs will facilitate the identification of quality problems, the implementation of solutions, and the evaluation of their effectiveness. Therefore, the QI has the potential to lead to reductions in mortality, morbidity, and resource use after injury.

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