Gilles Bourgeois

Rates, patterns, and determinants of unplanned readmission after traumatic injury: a multicenter cohort study.

Objective:This study aimed to (i) describe unplanned readmission rates after injury according to time, reason, and place; (ii) compare observed rates with general population rates, and (iii) identify determinants of 30-day readmission. Background:Hospital readmissions represent an important burden in terms of mortality, morbidity, and resource use but information on unplanned rehospitalization after injury admissions is scarce. Methods:This multicenter retrospective cohort study was based on adults discharged alive from a Canadian provincial trauma system (1998–2010; n = 115,329). Trauma registry data were linked to hospital discharge data to obtain information on readmission up to 12 months postdischarge. Provincial admission rates were matched to study data by age and gender to obtain expected rates. Determinants of readmission were identified using multiple logistic regression. Results:Cumulative readmission rates at 30 days, 3 months, 6 months, and 12 months were 5.9%, 10.9%, 15.5%, and 21.1%, respectively. Observed rates persisted above expected rates up to 11 months postdischarge. Thirty percent of 30-day readmissions were due to potential complications of injury compared with 3% for general provincial admissions. Only 23% of readmissions were to the same hospital. The strongest independent predictors of readmission were the number of prior admissions, discharge destination, the number of comorbidities, and age. Conclusions:Unplanned readmissions after discharge from acute care for traumatic injury are frequent, persist beyond 30 days, and are often related to potential complications of injury. Several patient-, injury-, and hospital-related factors are associated with the risk of readmission. Injury readmission rates should be monitored as part of trauma quality assurance efforts.

Donabedian's structure-process-outcome quality of care model: Validation in an integrated trauma system.

BACKGROUND According to Donabedian’s health care quality model, improvements in the structure of care should lead to improvements in clinical processes that should in turn improve patient outcome. This model has been widely adopted by the trauma community but has not yet been validated in a trauma system. The objective of this study was to assess the performance of an integrated trauma system in terms of structure, process, and outcome and evaluate the correlation between quality domains. METHODS Quality of care was evaluated for patients treated in a Canadian provincial trauma system (2005–2010; 57 centers, n = 63,971) using quality indicators (QIs) developed and validated previously. Structural performance was measured by transposing on-site accreditation visit reports onto an evaluation grid according to American College of Surgeons criteria. The composite process QI was calculated as the average sum of proportions of conformity to 15 process QIs derived from literature review and expert opinion. Outcome performance was measured using risk-adjusted rates of mortality, complications, and readmission as well as hospital length of stay (LOS). Correlation was assessed with Pearson’s correlation coefficients. RESULTS Statistically significant correlations were observed between structure and process QIs (r = 0.33), and process and outcome QIs (r = −0.33 for readmission, r = −0.27 for LOS). Significant positive correlations were also observed between outcome QIs (r = 0.37 for mortality-readmission; r = 0.39 for mortality-LOS and readmission-LOS; r = 0.45 for mortality-complications; r = 0.34 for readmission-complications; 0.63 for complications-LOS). CONCLUSION Significant correlations between quality domains observed in this study suggest that Donabedian’s structure-process-outcome model is a valid model for evaluating trauma care. Trauma centers that perform well in terms of structure also tend to perform well in terms of clinical processes, which in turn has a favorable influence on patient outcomes. LEVEL OF EVIDENCE Prognostic study, level III.

Derivation and validation of a quality indicator for 30-day unplanned hospital readmission to evaluate trauma care.

BACKGROUND Unplanned readmissions represent 20% of all admissions and cost

Mortality in Canadian Trauma Systems: A Multicenter Cohort Study

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.

A comparison of methods to obtain a composite performance indicator for evaluating clinical processes in trauma care.

Objective: To measure the variation in trauma center mortality across Canadian trauma systems, assess the contribution of traumatic brain injury and thoracoabdominal injury to observed variations, and evaluate whether the presence of recommended trauma system components is associated with mortality. Summary Background Data: Injuries represent one of the leading causes of mortality, disability, and health care costs worldwide. Trauma systems have improved injury outcomes, but the impact of trauma system configuration on mortality is unknown. Methods: We conducted a retrospective cohort study of adults admitted for major injury to trauma centers across Canada (2006–2012). Multilevel logistic regression was used to estimate risk-adjusted hospital mortality and assess the impact of 13 recommended trauma system components. Results: Of 78,807 patients, 8382 (10.6%) died in hospital including 6516 (78%) after severe traumatic brain injury and 749 (9%) after severe thoracoabdominal injury. Risk-adjusted mortality varied from 7.0% to 14.2% across provinces (P < 0.0001); 11.1% to 26.0% for severe traumatic brain injury (P < 0.0001), and 4.7% to 5.9% for thoracoabdominal injury (P = 0.2). Mortality decreased with increasing number of recommended trauma system elements; adjusted odds ratio = 0.93 (0.87–0.99). Conclusions: We observed significant variation in trauma center mortality across Canadian provinces, specifically for severe traumatic brain injury. Provinces with more recommended trauma system components had better patient survival. Results suggest that trauma system configuration may be an important determinant of injury mortality. A better understanding of which system processes drive optimal outcomes is required to reduce the burden of injury worldwide.

Hospital length of stay after admission for traumatic injury in Canada: a multicenter cohort study.

BACKGROUND: Process performance indicators that evaluate trauma centers in clinical case management provide information essential to the improvement of trauma care. However, multiple indicators are needed to adequately evaluate process performance, which renders comparisons cumbersome. Several methods are available for generating composite indicators that measure global performance. The goal of this study was to compare three composite methods that are widely used in other health care domains to identify the most appropriate for trauma care process performance evaluation. METHODS: In this retrospective, multicenter cohort study, 15 process performance indicators were implemented using data from a Canadian provincial trauma registry (19,853 patients; 59 centers) on patients with an Injury Severity Score (ISS) greater than 15. Composite scores were derived using three methods as follows: the indicator average, the opportunity model, and a latent variable model. Composite scores were evaluated in terms of discrimination, construct validity (association with an indicator of trauma center structural performance), criterion predictive validity (association with clinical outcomes), and forecasting (correlation over time). RESULTS: All composite scores discriminated well between trauma centers. Only the average indicator score was correlated with improved structure (r = 0.29; 95% confidence interval [CI], 0.07–0.53), lower risk‐adjusted mortality (r = ‐0.22; 95% CI, ‐0.46 to 0.04), and lower risk‐adjusted complication rate (r = ‐0.48; 95% CI, ‐0.65 to ‐0.25). Composite scores calculated with 1999 to 2002 data all correlated with those calculated with 2003 to 2006 data (r = 0.49, 0.87, and 0.84 for the indicator average, the opportunity model, and the latent variable model, respectively). CONCLUSION: Results suggest that of the three composite scores evaluated, only the indicator average demonstrates content and predictive criterion validity, discriminates between centers, and has good forecasting properties. In addition, this score is simple and intuitive and not subject to variation in weights over trauma systems and time. The observed association between higher indicator average scores and lower risk‐adjusted mortality and complication rates suggests that improving process performance may improve patient outcome. LEVEL OF EVIDENCE: Epidemiologic and prognostic study, level III.

Validation of complications selected by consensus to evaluate the acute phase of adult trauma care: a multicenter cohort study

Objective:To describe acute care length of stay (LOS) over all consecutive hospitalizations for the injury and according to level of care [intensive care unit (ICU), intermediate care, general ward], compare observed and expected LOS, and identify predictors of LOS. Background:Prolonged LOS has important consequences in terms of costs and outcome, yet detailed information on LOS after trauma is lacking. Methods:This multicenter retrospective cohort study was based on adults discharged alive from a Canadian trauma system (1999–2010; n = 126,513). Registry data were used to calculate index LOS (LOS in trauma center with highest designation level) and were linked to hospital discharge data to calculate total LOS (all consecutive hospitalizations for the injury). Expected LOS was obtained by matching general provincial discharge statistics to study data by year, age, and sex. Potential predictors of LOS were evaluated using linear regression. Results:Mean index and total LOS were 8.6 and 9.4 days, respectively. ICU, intermediate care unit, and general ward care constituted 8.9%, 2.5%, and 88.6% of total hospital days. Observed mean index and ICU LOS in our trauma patients were 2.9 and 1.3 days longer than expected LOS (P < 0.0001). The strongest determinants of index LOS were discharge destination, age, transfer status, and injury severity. Conclusions:Results suggest that acute care LOS after injury is underestimated when only information on the index hospitalization is used and that ICU or intermediate care constitute an important part of LOS. This information should be used to inform the development of an informative and actionable quality indicator.

Access to a Canadian provincial integrated trauma system: A population-based cohort study

Objective: Evaluate the predictive validity of complications derived using expert consensus methodology to monitor the quality of trauma care. Secondary objectives were to assess the predictive validity of complications not selected by consensus and identify determinants of complications. Background: A list of complications to monitor the quality of trauma care has recently been derived using Delphi consensus methodology. However, the predictive validity of consensus complications has not yet been demonstrated. Methods: We conducted a multicenter cohort study of adults admitted to the 57 adult trauma centers of a Canadian integrated trauma system (2007–2012; n = 84,216). Multiple generalized linear models were used to assess the influence of complications on mortality and acute care length of stay (LOS) and to identify determinants of consensus complications. Results: The presence of at least 1 consensus complication was associated with a 2.7-fold [95% confidence interval (CI): 2.45–2.90] and 2.2-fold (95% CI: 2.11–2.19) increase in the odds of mortality and mean LOS, respectively. Nonselected complications were associated with no increase in mortality (odds ratio = 0.90, 95% CI: 0.80–1.01) and a 60% increase in LOS (geometric mean ratio = 1.60, 95% CI: 1.57–1.62). Patient-related factors and factors related to treatment explained 66% and 34% of the variation in complication rates, respectively. Conclusions: In addition to the face and content validity ensured by consensus methodology, this study suggests that consensus complications have good predictive validity. Monitoring these complications as part of quality improvement activities would provide an opportunity to improve outcome and resource use for injury admissions.

Derivation and validation of a quality indicator of acute care length of stay to evaluate trauma care.

BACKGROUND Access to specialised trauma care is an important measure of trauma system efficiency. However, few data are available on access to integrated trauma systems. We aimed to describe access to trauma centres (TCs) in an integrated Canadian trauma system and identify its determinants. METHODS We conducted a population-based cohort study including all injured adults admitted to acute care hospitals in the province of Québec between 2006 and 2011. Proportions of injured patients transported directly or transferred to TCs were assessed. Determinants of access were identified through a modified Poisson regression model and a relative importance analysis was used to determine the contribution of each independent variable to predicting access. RESULTS Of the 135,653 injury admissions selected, 75% were treated within the trauma system. Among 25,522 patients with major injuries [International Classification of diseases Injury Severity Score (ICISS<0.85)], 90% had access to TCs. Access was higher for patients aged under 65, men and among patients living in more remote areas (p-value <0.001). The region of residence followed by injury mechanism, number of trauma diagnoses, injury severity and age were the most important determinants of access to trauma care. CONCLUSIONS In an integrated, mature trauma system, we observed high access to TCs. However, problems in access were observed for the elderly, women and in urban areas where there are many non-designated hospitals. Access to trauma care should be monitored as part of quality of care improvement activities and pre-hospital guidelines for trauma patients should be applied uniformly throughout the province.

Trends in Injury Outcomes Across Canadian Trauma Systems

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.