Search

Objective: Examine between-hospital and between-anesthesiologist variation in anesthesiology provider--volume (PV) and delivery of highvolume anesthesiology care. Background: Better outcomes for anesthesiologists with higher PV of complex gastrointestinal cancer surgery have been reported. The factors linking anesthesiology practice and organization to volume are unknown. Methods: We identified patients undergoing elective esophagectomy, hepatectomy, and pancreatectomy using linked administrative health data sets (2007--2018). Anesthesiology PV was the annual number of procedures done by the primary anesthesiologist in the 2 years before the index surgery. High-volume anesthesiology was PV>6 procedures/year. Funnel plots to described variation in anesthesiology PV and delivery of high-volume care. Hierarchical regression models examined between-anesthesiologist and between-hospital variation in delivery of high-volume care use with variance partition coefficients (VPCs) and median odds ratios (MORs). Results: Among 7893 patients cared for at 17 hospitals, funnel plots showed variation in anesthesiology PV (median ranging from 1.5, interquartile range: 1--2 to 11.5, interquartile range: 8--16) and delivery of HV care (ranging from 0% to 87%) across hospitals. After adjustment, 32% (VPC 0.32) and 16% (VPC: 0.16) of the variation were attributable to between-anesthesiologist and between-hospital differences, respectively. This translated to an anesthesiologist MOR of 4.81 (95% CI, 3.27--10.3) and hospital MOR of 3.04 (95% CI, 2.14--7.77). Conclusions: Substantial variation in anesthesiology PV and delivery of high-volume anesthesiology care existed across hospitals. The anesthesiologist and the hospital were key determinants of the variation in high-volume anesthesiology care delivery. This suggests that targeting anesthesiology structures of care could reduce variation and improve delivery of high-volume anesthesiology care. [ABSTRACT FROM AUTHOR]

Objective: To examine the association of between hospital rates of high-volume anesthesiology care and of postoperative major morbidity. Background: Individual anesthesiology volume has been associated with individual patient outcomes for complex gastrointestinal cancer surgery. However, whether hospital-level anesthesiology care, where changes can be made, influences the outcomes of patients cared at this hospital is unknown. Methods: We conducted a population-based retrospective cohort study of adults undergoing esophagectomy, pancreatectomy, or hepatectomy for cancer from 2007 to 2018. The exposure was hospital-level adjusted rate of high-volume anesthesiology care. The outcome was hospital-level adjusted rate of 90-day major morbidity (Clavien-Dindo grade 3–5). Scatterplots visualized the relationship between each hospital's adjusted rates of high-volume anesthesiology and major morbidity. Analyses at the hospital-year level examined the association with multivariable Poisson regression. Results: For 7893 patients at 17 hospitals, the rates of high-volume anesthesiology varied from 0% to 87.6%, and of major morbidity from 38.2% to 45.4%. The scatter plot revealed a weak inverse relationship between hospital rates of high-volume anesthesiology and of major morbidity (Pearson: −0.23). The adjusted hospital rate of high-volume anesthesiology was independently associated with the adjusted hospital rate of major morbidity (rate ratio: 0.96; 95% CI, 0.95–0.98; P <0.001 for each 10% increase in the high-volume rate). Conclusions: Hospitals that provided high-volume anesthesiology care to a higher proportion of patients were associated with lower rates of 90-day major morbidity. For each additional 10% patients receiving care by a high-volume anesthesiologist at a given hospital, there was an associated reduction of 4% in that hospital's rate of major morbidity. [ABSTRACT FROM AUTHOR]

Supplemental Digital Content is available in the text Objective: Evaluate interhospital variation in resource use for in-hospital injury deaths. Background: Significant variation in resource use for end-of-life care has been observed in the US for chronic diseases. However, there is an important knowledge gap on end-of-life resource use for trauma patients. Methods: We conducted a multicenter, retrospective cohort study of injury deaths following hospitalization in any of the 57 trauma centers in a Canadian trauma system (2013–2016). Resource use intensity was measured using activity-based costing (2016 $CAN) according to time of death (72 h, 3–14 d, ≥14 d). We used multilevel log-linear regression to model resource use and estimated interhospital variation using intraclass correlation coefficients (ICC). Results: Our study population comprised 2044 injury deaths. Variation in resource use between hospitals was observed for all 3 time frames (ICC = 6.5%, 6.6%, and 5.9% for < 72 h, 3–14 d, and ≥14 d, respectively). Interhospital variation was stronger for allied health services (ICC = 18 to 26%), medical imaging (ICC = 4 to 10%), and the ICU (ICC = 5 to 6%) than other activity centers. We observed stronger interhospital variation for patients < 65 years of age (ICC = 11 to 34%) than those ≥65 (ICC = 5 to 6%) and for traumatic brain injury (ICC = 5 to 13%) than other injuries (ICC = 1 to 8%). Conclusions: We observed variation in resource use intensity for injury deaths across trauma centers. Strongest variation was observed for younger patients and those with traumatic brain injury. Results may reflect variation in level of care decisions and the incidence of withdrawal of life-sustaining therapies. [ABSTRACT FROM AUTHOR]

Objective: Create practice guidelines for the appropriate use of red blood cell transfusions in hepatectomy. Background: Hepatectomy is associated with a high prevalence of transfusions. A transfusion can be life-saving, but can be associated with important adverse effects. Given the prevalence, the potential for benefit and harm, and the difficulty in conducting clinical trials, transfusion in hepatectomy is well-suited for a study of appropriateness. Methods: Using the RAND/UCLA appropriateness method, an international, multidisciplinary expert panel in hepatobiliary surgery, anesthesia, transfusion medicine, and critical care rated a series of 468 perioperative scenarios for transfusion appropriateness. Scenarios were rated individually, and again during an inperson group moderated session. Median scores and level of agreement were calculated to classify each scenario as appropriate, inappropriate, or uncertain. Results: Approximately, 47.4% of scenarios were rated as appropriate for transfusion, 28.2% were inappropriate, and 24.4% were uncertain. The key recommendations for intraoperative transfusion were (i) it is never inappropriate to transfuse for significant bleeding or ST segment changes; (ii) it is never inappropriate to transfuse for an intraoperative hemoglobin ≤75 g/L; and (iii) in the absence of significant bleeding or ST changes, transfusion for hemoglobin of ≥95 g/L is inappropriate, and transfusion for hemoglobin of ≥85 g/L requires strong justification. The key recommendations for postoperative transfusions were: (i) in a stable, asymptomatic patient, an appropriate transfusion trigger is 70 g/L (without coronary artery disease) or 80 g/L (with coronary artery disease) and (ii) it is appropriate to transfuse any patient for a hemoglobin of ≤75 g/L either immediately post-operative, or with a significant decrease from the previous day (>15 g/L). Conclusions: Based on best available evidence and expert opinion, criteria for appropriate perioperative red blood cell transfusions in hepatectomy were determined. [ABSTRACT FROM AUTHOR]

Objective: To assess the variation in hospital and intensive care unit (ICU) length of stay (LOS) for injury admissions across Canadian provinces and to evaluate the relative contribution of patient case mix and treatment-related factors (intensity of care, complications, and discharge delays) to explaining observed variations. Background: Identifying unjustified interprovider variations in resource use and the determinants of such variations is an important step towards optimizing health care. Methods: We conducted a multicenter, retrospective cohort study on admissions for major trauma (injury severity score >12) to level I and II trauma centers across Canada (2006-2012). We used data from the Canadian National Trauma Registry linked to hospital discharge data to compare risk-adjusted hospital and ICU LOS across provinces. Results: Risk-adjusted hospital LOS was shortest in Ontario (10.0 days) and longest in Newfoundland and Labrador (16.1 days; P < 0.001). Risk-adjusted ICU LOS was shortest in Québec (4.4 days) and longest in Alberta (6.1 days; P < 0.001). Patient case-mix explained 32% and 8% of interhospital variations in hospital and ICU LOS, respectively, whereas treatment-related factors explained 63% and 22%. Conclusions: We observed significant variation in risk-adjusted hospital and ICU LOS across trauma systems in Canada. Provider ranks on hospital LOS were not related to those observed for ICU LOS. Treatment-related factors explained more interhospital variation in LOS than patient case-mix. Results suggest that interventions targeting reductions in low-value procedures, prevention of adverse events, and better discharge planning may be most effective for optimizing LOS for injury admissions. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

To derive and internally validate a quality indicator (QI) for acute care length of stay (LOS) after admission for injury.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.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.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).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. [ABSTRACT FROM AUTHOR]

Objectives: To assess the clinical outcomes, predictors, and prevalence of anterior pituitary disorders following traumatic brain injury. Data Sources: We searched Medline, Embase, Cochrane Registry, BIOSIS, and Trip Database up to February 2012 and consulted bibliographies of narrative reviews and selected articles. Study Selection: We included cohort, case-control, cross-sectional studies and randomized trials enrolling at least five adults with blunt traumatic brain injury in whom at least one anterior pituitary axis was assessed. We excluded case series and studies in which other neurological conditions were indistinguishable from traumatic brain injury. Data Extraction: Two independent reviewers selected citations, extracted data, and assessed the risk of bias using a standardized form. Data Synthesis: We performed meta-analyses using random effect models and assessed heterogeneity using the I2 index. Results: We included 66 studies (5,386 patients) evaluating prevalence, 14 evaluating clinical outcomes, and 27 evaluating predictors. Thirty studies were at low risk of bias. Anterior pituitary disorders were associated with a trend toward increased ICU mortality (risk ratio, 1.79; 95% CI, 0.99-3.21; four studies) and no difference in Glasgow Outcome Scale score (mean difference, -0.45; 95% CI, -1.10 to 0.20; three studies). Age (mean difference, 3.19; 95% CI, 0.31-6.08; 19 studies), traumatic brain injury severity (risk ratio, 2.15; 95% CI, 1.20-3.86 for patients with severe vs nonsevere traumatic brain injury; seven studies), and skull fractures (risk ratio, 1.73; 95% CI, 1.03-2.91; six studies) predicted anterior pituitary disorders. Over the long term, 31.6% (95% CI, 23.6-40.1%; 27 studies) of patients had at least one anterior pituitary disorder. We observed significant heterogeneity that was not solely explained by the risk of bias or traumatic brain injury severity. Conclusions: Approximately one third of traumatic brain injury patients have persistent anterior pituitary disorder. Older age, traumatic brain injury severity, and skull fractures predict anterior pituitary disorders, which in turn may be associated with higher ICU mortality. Further high-quality studies are warranted to better define the burden of anterior pituitary disorders and to identify high-risk patients. [ABSTRACT FROM AUTHOR]

The article presents a study which shows that severe traumatic brain injury in patients remained limited but the mortality rate following the withdrawal of life sustaining therapies proved to be high and variable. A survey was carried out which was used to determine the prognosis of the patients who suffered with severe traumatic brain injury. It states that due to significant variation in the perceptions of neurologic prognosis, more consistent approach for predicting the outcome was needed.

Background: Tibial malrotation is a complication that is seen in approximately 30% of patients following locked intramedullary nailing. In this cohort study, we evaluated the hypothesis that tibial malrotation would lead to impaired functional outcomes. Methods: Patients with a unilateral tibial shaft fracture who were managed with intramedullary nailing between 2003 and 2007 were identified with use of ICD-10 (International Classification of Diseases, 10th Revision) codes. After institutional review board approval and written informed consent had been obtained, specific assessment of eligible patients was achieved with use of computed tomography, functional measures (Lower Extremity Functional Scale, Olerud-Molander Score, six-minute walk test), and physical examination. Measures were compared between patients with and without tibial malrotation (defined as tibial rotation of ⩾10°) on imaging studies. Results: Of the 288 patients who were identified, 100 were eligible for the study and seventy consented to participate. The mean duration of follow-up (and standard deviation) for these seventy patients was 58 ± 11 months. Twenty-nine patients (41%) had tibial malrotation. Lower Extremity Functional Scale scores were similar between the groups with and without malrotation (mean, 70.8 ± 8.6 points compared with 72.6 ± 8.7 points; p = 0.41). The results for the other functional tests were also similar. Conclusions: Despite high rates of tibial malrotation following locked intramedullary nailing of isolated tibial diaphyseal fractures, this finding does not have a significant intermediate-term functional impact. Level of Evidence: Prognostic Level II. See Instructions for Authors for a complete description of levels of evidence. [ABSTRACT FROM AUTHOR]

The article presents a study on the influence of the definition of mortality on the results of trauma center performance evaluations according to the ages of patients. The researchers based the multicenter cohort study on the inclusive trauma system in Quebec. They also linked the trauma registry to provincial vital statistics data in order to obtain information on postdischarge mortality.

To develop a method of evaluating trauma center mortality that addresses the limitations of currently available methodology—Standardized Mortality Ratios (SMRs) based on the Trauma and Injury Severity Score.TRISS SMRs have important limitations including inadequate risk adjustment, comparison to an inappropriate standard, lack of consideration for inter- and intrahospital variation, and incomparability across hospitals.The methodology was developed using data from a provincial trauma registry with mandatory participation of all trauma centers, uniform inclusion criteria, and standardized data collection methods. Institutional performance was described with estimates of risk-adjusted mortality derived from a hierarchical logistic regression model. Risk adjustment was performed with a risk score generated by the Trauma Risk Adjustment Model (TRAM), as well as a term for incoming transfers and an interaction between transfer and the risk score. Outliers were identified by comparing each hospital to all remaining hospitals.The study population comprised 88,235 patients including 4731 deaths (5.4%) from 59 trauma centers. Crude mortality varied between 1.3% and 14.3%. TRAM-adjusted mortality estimates varied between 3.7% (95% CI: 3.2%-4.3%) and 6.9% (5.8%-8.2%). Three trauma centers had significantly higher adjusted mortality and one center had statistically significant lower mortality when compared with all other centers.The proposed method of trauma center profiling offers comprehensive adjustment for patient-level risk factors and consideration of transfer status, is based on comparisons to an internal standard, accounts for inter- and intrahospital variation, and replaces SMRs with estimates of regression-adjusted mortality that are comparable across hospitals. TRAM-adjusted mortality estimates can be used to describe institutional outcome performance and to identify institutional outliers. Such information is the key to identiyfing ways to improve the quality of modern trauma care. [ABSTRACT FROM AUTHOR]