Natalie Le Sage

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.

The Trauma Risk Adjustment Model: A New Model for Evaluating Trauma Care

Summary Background Data:The trauma injury severity score (TRISS) has been used for over 20 years for retrospective risk assessment in trauma populations. The TRISS has serious limitations, which may compromise the validity of trauma care evaluations. Objective:To derive and validate a new mortality prediction model, the trauma risk adjustment model (TRAM), and to compare the performance of the TRAM to that of the TRISS in terms of predictive validity and risk adjustment. Methods:The Quebec Trauma Registry (1998–2005), based on the mandatory participation of 59 designated provincial trauma centers, was used to derive the model. The American National Trauma Data Bank (2000–2005), based on the voluntary participation of any US hospitals treating trauma, was used for the validation phase. Adult patients with blunt trauma respecting at least one of the following criteria were included: hospital stay >2 days, intensive care unit admission, death, or hospital transfer. Hospital mortality was modeled with logistic generalized additive models using cubic smoothing splines to accommodate nonlinear relations to mortality. Predictive validity was assessed with model discrimination and calibration. Risk adjustment was assessed using comparisons of risk-adjusted mortality between hospitals. Results:The TRAM generated an area under the receiving operator curve of 0.944 and a Hosmer-Lemeshow statistic of 42 in the derivation phase. In the validation phase, the TRAM demonstrated better model discrimination and calibration than the TRISS (area under the receiving operator curve = 0.942 and 0.928, P < 0.001; Hosmer-Lemeshow statistics = 127 and 256, respectively). Replacing the TRISS with the TRAM led to a mean change of 28% in hospital risk-adjusted odds ratios of mortality. Conclusions:Our results suggest that adopting the TRAM could improve the validity of trauma care evaluations and trauma outcome research.

Using Information on Preexisting Conditions to Predict Mortality From Traumatic Injury

STUDY OBJECTIVE Preexisting conditions have been found to be an independent predictor of mortality after trauma. However, no consensus has been reached as to what indicator of preexisting condition status should be used, and the contribution of preexisting conditions to mortality prediction models is unclear. This study aims to identify the most accurate way to model preexisting condition status to predict inhospital trauma mortality and to evaluate the potential gain of adding preexisting condition status to a standard trauma mortality prediction model. METHODS The study comprised all patients from the trauma registries of 4 Level I trauma centers. Information provided by individual preexisting conditions was compared to 3 commonly used summary measures: (1) absence/presence of any preexisting condition, (2) number of preexisting conditions, and (3) Charlson Comorbidity Index. The impact of adding preexisting condition status to 2 baseline risk models, the current standard Trauma and Injury Severity Score model and an improved model based on nonparametric transformations of quantitative variables, was evaluated by the area under the receiver operating characteristics curve. RESULTS Discrimination for predicting mortality in the improved model was as follows: baseline risk model: area under the receiver operating characteristics curve=0.935; baseline risk model+individually modeled preexisting conditions: area under the receiver operating characteristics curve=0.941; baseline risk model+presence of any preexisting condition: area under the receiver operating characteristics curve=0.937; baseline risk model+number of preexisting conditions: area under the receiver operating characteristics curve=0.939; baseline risk model+Charlson Comorbidity Index: area under the receiver operating characteristics curve=0.938. CONCLUSION Preexisting condition status is an independent predictor of mortality from trauma that provides a modest improvement in mortality prediction. The total number of preexisting conditions is a good summary measure of preexisting condition status. The Charlson Comorbidity Index is no better than the total number of preexisting conditions and is therefore not recommended for use in trauma mortality modeling.

Consensus or Data-Derived Anatomic Injury Severity Scoring?

BACKGROUND Anatomic injury severity scores can be grouped into two classes; consensus-derived and data-derived. The former, including the Injury Severity Score (ISS), the New Injury Severity Score (NISS), and the Anatomic Profile Score (APS), are based on the severity score of the Abbreviated Injury Scale (AIS), assigned by clinical experts. The latter, including the International Classification of Disease Injury Severity Score (ICISS) and the Trauma Registry Abbreviated Injury Scale Score (TRAIS) are based on survival probabilities calculated in large trauma databases. We aimed to compare the predictive accuracy of consensus-derived and data-derived severity scores when considered alone and in combination with age and physiologic status. METHODS Analyses were based on 25,111 patients from the trauma registries of the four Level I trauma centers in the province of Quebec, Canada, abstracted between April 1998 and March 2005. The predictive validity of each severity score was evaluated in logistic regression models predicting hospital mortality using measures of discrimination (Area Under the Receiver Operating Characteristics curve [AUC]) and calibration (Hosmer-Lemeshow statistic [HL]). RESULTS Data-derived scores had consistently better predictive accuracy than consensus-derived scores in univariate models (p < 0.0001) but very little difference between scores was observed in models including information on age and physiologic status. The difference in AUC between the least accurate severity score (ISS) and the most accurate severity score (TRAIS) was 15% in anatomic-only models but fell to 2% in models including age and physiologic status. CONCLUSIONS Data-derived scores provide more accurate mortality prediction than consensus-derived scores do when only anatomic injury severity is considered but offer little advantage if age and physiologic status are taken into account. This may be because of the fact that data-derived scores are not an independent measure of anatomic injury severity.

Improving trauma mortality prediction modeling for blunt trauma.

BACKGROUND : Despite serious documented limitations, the Trauma Injury Severity Score (TRISS) is still used for risk adjustment in trauma system evaluation and clinical research. Several modifications have been proposed to address TRISS limitations. We aimed to assess the impact of proposed TRISS modifications on the accuracy of mortality prediction for blunt trauma. METHODS : The Quebec Trauma Registry (QTR), based on a mature, regionalized trauma system with mandatory participation of all trauma centers as well as standardized inclusion criteria and coding practices, was used to evaluate TRISS modifications. The National Trauma Data Bank was then used to validate our findings. Gains in predictive accuracy were evaluated in logistic regression models of hospital mortality with the area under the receiving operator curve and the Hosmer-Lemeshow statistic. RESULTS : When population-based weights, expanding age, modeling the Glasgow Coma Scale score as a quantitative variable, adding an indicator of comorbid status, and modeling quantitative variables with nonparametric functions to allow the expression of nonlinear relations to mortality were used, all were associated with a significant improvement in model discrimination. CONCLUSIONS : Several modifications that have been proposed to address limitations of the TRISS lead to significant improvements in the accuracy of mortality prediction. This study provides valuable information in the quest to improve trauma mortality modeling.

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

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.

Patients With Rib Fractures Do Not Develop Delayed Pneumonia: A Prospective, Multicenter Cohort Study of Minor Thoracic Injury

STUDY OBJECTIVE Patients admitted to emergency departments (EDs) for minor thoracic injuries are possibly at risk of delayed pneumonia. We aimed to evaluate the incidence of delayed pneumonia post-minor thoracic injury and the associated risk factors. METHODS A prospective, multicenter cohort study was conducted in 4 Canadian EDs, from November 2006 to November 2010. All consecutive patients aged 16 years and older with minor thoracic injury who were discharged from the ED were screened for eligibility. Uniform clinical and radiologic evaluations were performed on the initial ED visit and were repeated at weeks 1 and 2. Relative risk analyses quantified incidence with comparison by age, sex, smoking status, alcohol intoxication, pulmonary comorbidity, ability to cough atelectasis, pain level, and number of rib fractures. RESULTS Of the 1,057 participants recruited, 347 (32.8%) had at least 1 rib fracture, 87 (8.2%) had asthma, and 36 (3.4%) had chronic obstructive pulmonary disease. Only 6 patients (0.6%; 95% confidence interval 0.24% to 1.17%) developed pneumonia during the follow-up period. The relative risk for patients with preexistent pulmonary disease and radiologically proven rib fractures was 8.6 (P=.045; 95% confidence interval 1.05 to 70.9). Sex, smoking habit, initial atelectasis, ability to cough, and alcohol intoxication were not significantly associated with delayed pneumonia. CONCLUSION This prospective cohort study of nonhospitalized patients with minor thoracic injuries revealed a low incidence of delayed pneumonia. Nonetheless, our results support tailored follow-up for asthmatic or chronic obstructive pulmonary disease patients with rib fracture.

Evaluating trauma center structural performance: The experience of a Canadian provincial trauma system.

Background: Indicators of structure, process, and outcome are required to evaluate the performance of trauma centers to improve the quality and efficiency of care. While periodic external accreditation visits are part of most trauma systems, a quantitative indicator of structural performance has yet to be proposed. The objective of this study was to develop and validate a trauma center structural performance indicator using accreditation report data. Materials and Methods: Analyses were based on accreditation reports completed during on-site visits in the Quebec trauma system (1994-2005). Qualitative report data was retrospectively transposed onto an evaluation grid and the weighted average of grid items was used to quantify performance. The indicator of structural performance was evaluated in terms of test-retest reliability (kappa statistic), discrimination between centers (coefficient of variation), content validity (correlation with accreditation decision, designation level, and patient volume) and forecasting (correlation between visits performed in 1994-1999 and 1998-2005). Results: Kappa statistics were >0.8 for 66 of the 73 (90%) grid items. Mean structural performance score over 59 trauma centers was 47.4 (95% CI: 43.6-51.1). Two centers were flagged as outliers and the coefficient of variation was 31.2% (95% CI: 25.5% to 37.6%), showing good discrimination. Correlation coefficients of associations with accreditation decision, designation level, and volume were all statistically significant (r = 0.61, -0.40, and 0.24, respectively). No correlation was observed over time (r = 0.03). Conclusion: This study demonstrates the feasibility of quantifying trauma center structural performance using accreditation reports. The proposed performance indicator shows good test-retest reliability, between-center discrimination, and construct validity. The observed variability in structural performance across centers and over-time underlines the importance of evaluating structural performance in trauma systems at regular intervals to drive quality improvement efforts.

Executive dysfunction following a mild traumatic brain injury revealed in early adolescence with locomotor-cognitive dual-tasks

Abstract Objective: To compare gait parameters between children in early adolescence (EA) with and without a mild traumatic brain injury (mTBI) during dual-task walking (DTW). Methods: Children in EA with mTBI (n = 14; six girls) were compared to those without (n = 13; five girls) while walking in different combinations of obstacle avoidance and cognitive dual-tasks. Gait speed and fluidity and their related dual-task costs (DTC) were analysed along with foot clearance and proximity to the obstacle. Results: No group effects were found for gait speed, proximity or clearance, but were found for fluidity DTC, specifically during the dual Stroop task and when crossing the deeper obstacle. There were also group differences for fluidity during the planning of obstacle avoidance for the narrow obstacle combined with the verbal fluency task and the deep obstacle with no cognitive task. Finally, gait fluidity showed group differences across unobstructed dual-task situations. Conclusions: Gait fluidity may be a more sensitive variable than gait speed for revealing executive dysfunction following mTBI in EA. Assessing DTW in level walking also seems to show a potential to reveal executive dysfunctions in this age group. These results provide direction for future research on clinical assessment using DTW post-mTBI in adolescents.

Cohort study on the prevalence and risk factors for delayed pulmonary complications in adults following minor blunt thoracic trauma.

OBJECTIVES The objectives of this study are to determine the prevalence, risk factors, and time to onset of delayed hemothorax and pneumothorax in adults who experienced a minor blunt thoracic trauma. METHOD A prospective cohort of 450 consecutive patients was recruited. Eligible patients had to be over 16 years of age, consulted within 72 hours for a trauma, and available for outpatient follow-up at 2, 7, and 14 days posttrauma. The clinical outcome investigated was the presence of delayed pneumothorax or hemothorax on the follow-up chest x-ray. OUTCOMES Delayed hemothorax occurred in 11.8% (95% CI 8.8-14.8), and delayed pneumothorax occurred in 0.9% (95% CI 0.2-2.3) of participants. During the 14-day follow-up period, 87.0% of these delayed complications developed in the first week. In the multivariate analysis, the only statistically significant risk factor for delayed complications was the location of fractures on the x-ray of the hemithorax. The adjusted odds ratio was 1.52 (95% CI 0.62-3.73) for the lower ribs (tenth to twelfth rib), 3.11 (95% CI 1.60-6.08) for the midline ribs (sixth to ninth rib), and 5.05 (95% CI 1.80-14.19) for the upper ribs (third to fifth rib) versus patients with no fractures. CONCLUSION The presence of at least one rib fracture between the third and ninth rib on the x-ray of the hemithorax is a significant risk factor for delayed hemothorax and pneumothorax.