Background: Unplanned readmissions represent 20% of all admissions and cost $12 billion annually in the United States. Despite the burden of injuries for the health care system, no quality indicator (QI) based on readmissions is available to evaluate trauma care. The objective of this study was to derive and internally validate a QI for a 30-day unplanned hospital readmission to evaluate trauma care.
Methods: We performed a multicenter retrospective cohort study in a Canadian integrated provincial trauma system. We included adults admitted to any of the 57 provincial trauma centers between 2005 and 2010 (n = 57,524). Data were abstracted from the provincial trauma registry and linked to the hospital discharge database. The primary outcome was unplanned readmission to an acute care hospital within 30 days of discharge. Candidate risk factors were identified by expert consensus and selected for derivation of the risk adjustment model using bootstrap resampling. The validity of the QI was evaluated in terms of interhospital discrimination, construct validity, and forecasting.
Results: The risk adjustment model includes patient age, sex, the Injury Severity Score (ISS), region of the most severe injury, and 11 comorbid conditions. The QI discriminates well across trauma centers (coefficient of variation, 0.02) and is correlated with QIs that measure hospital performance in terms of clinical processes (r = -0.38), risk-adjusted mortality (r = 0.32), and complication rates (r = 0.38). In addition, performance in 2005 to 2007 was predictive of performance in 2008 to 2010 (r = 0.59).
Conclusion: We have developed a QI based on risk-adjusted 30-day rates of unplanned readmission, which can be used to evaluate trauma care with routinely collected data. The QI is based on a comprehensive risk adjustment model with good internal and temporal validity and demonstrates good properties in terms of discrimination, construct validity, and forecasting. This research represents an essential step toward reducing unplanned readmission rates to improve resource use and patient outcomes following injury.
Level of evidence: Prognostic study, level III.