Jean Lapointe

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

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

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.

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.

Implementation and Evaluation of a Wiki Involving Multiple Stakeholders Including Patients in the Promotion of Best Practices in Trauma Care: The WikiTrauma Interrupted Time Series Protocol.

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

Background Trauma is the most common cause of mortality among people between the ages of 1 and 45 years, costing Canadians 19.8 billion dollars a year (2004 data), yet half of all patients with major traumatic injuries do not receive evidence-based care, and significant regional variation in the quality of care across Canada exists. Accordingly, our goal is to lead a research project in which stakeholders themselves will adapt evidence-based trauma care knowledge tools to their own varied institutional contexts and cultures. We will do this by developing and assessing the combined impact of WikiTrauma, a free collaborative database of clinical decision support tools, and Wiki101, a training course teaching participants how to use WikiTrauma. WikiTrauma has the potential to ensure that all stakeholders (eg, patients, clinicians, and decision makers) can all contribute to, and benefit from, evidence-based clinical knowledge about trauma care that is tailored to their own needs and clinical setting. Objective Our main objective will be to study the combined effect of WikiTrauma and Wiki101 on the quality of care in four trauma centers in Quebec. Methods First, we will pilot-test the wiki with potential users to create a version ready to test in practice. A rapid, iterative prototyping process with 15 health professionals from nonparticipating centers will allow us to identify and resolve usability issues prior to finalizing the definitive version for the interrupted time series. Second, we will conduct an interrupted time series to measure the impact of our combined intervention on the quality of care in four trauma centers that will be selected—one level I, one level II, and two level III centers. Participants will be health care professionals working in the selected trauma centers. Also, five patient representatives will be recruited to participate in the creation of knowledge tools destined for their use (eg, handouts). All participants will be invited to complete the Wiki101 training and then use, and contribute to, WikiTrauma for 12 months. The primary outcome will be the change over time of a validated, composite, performance indicator score based on 15 process performance indicators found in the Quebec Trauma Registry. Results This project was funded in November 2014 by the Canadian Medical Protective Association. We expect to start this trial in early 2015 and preliminary results should be available in June 2016. Two trauma centers have already agreed to participate and two more will be recruited in the next months. Conclusions We expect that this study will add important and unique evidence about the effectiveness, safety, and cost savings of using collaborative platforms to adapt knowledge implementation tools across jurisdictions.

Trauma center performance evaluation based on costs: a systematic review of cohort studies.

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.

Influence of access to an integrated trauma system on in-hospital mortality and length of stay

BACKGROUND In 2000, more than 50 million Americans were treated in hospitals following injury, with costs estimated at

Healthcare professionals' intentions to use wiki-based reminders to promote best practices in trauma care: a survey protocol

80 billion, yet no performance indicator based on costs has been developed and validated specifically for acute trauma care. This study aimed to describe how data on costs have been used to evaluate the performance of acute trauma care hospitals. METHODS A systematic review using MEDLINE, EMBASE, Web of Science, The Cochrane Library, CINAHL, TRIP, and ProQuest was performed in December 2012. Cohort studies evaluating hospital performance for the treatment of injury inpatients in terms of costs were considered eligible. Two authors conducted the screening and the data abstraction independently using a piloted electronic data abstraction form. Methodological quality was evaluated using seven criteria from the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement and the Downs and Black tool. RESULTS The search retrieved 6,635 studies, of which 10 were eligible for inclusion. Nine studies were conducted in the United States and one in Europe. Six studies used patient charges as a proxy for patient costs, of which four used cost-to-charge ratios. One study estimated costs using average unit costs, and three studies were based on the real costs obtained from a hospital accounting system. Average costs per patient in 2013 US dollar varied between 2,568 and 74,435. Four studies (40%) were considered to be of good methodological quality. CONCLUSION Studies evaluating the performance of trauma hospitals in terms of costs are rare. Most are based on charges rather than costs, and they have low methodological quality. Further research is needed to develop and validate a performance indicator based on inpatient costs that will enable us to monitor trauma centers in terms of resource use. LEVEL OF EVIDENCE Systematic review, evidence, level III.