Context Studies involving physicians suggest that unconscious bias may be related to clinical decision making and may predict poor patient-physician interaction. The presence of unconscious race and social class bias and its association with clinical assessments or decision making among medical students is unknown. Objective To estimate unconscious race and social class bias among first-year medical students and investigate its relationship with assessments made during clinical vignettes. Design, Setting, and Participants A secure Web-based survey was administered to 211 medical students entering classes at Johns Hopkins School of Medicine, Baltimore, Maryland, in August 2009 and August 2010. The survey included the Implicit Association Test (IAT) to assess unconscious preferences, direct questions regarding students’ explicit race and social class preferences, and 8 clinical assessment vignettes focused on pain assessment, informed consent, patient reliability, and patient trust. Adjusting for student demographics, multiple logistic regression was used to determine whether responses to the vignettes were associated with unconscious race or social class preferences. Main Outcome Measures Association of scores on an established IAT for race and a novel IAT for social class with vignette responses. Results Among the 202 students who completed the survey, IAT responses were consistent with an implicit preference toward white persons among 140 students (69%, 95% CI, 61%–75%). Responses were consistent with a preference toward those in the upper class among 174 students (86%, 95% CI, 80%–90%). Assessments generally did not vary by patient race or occupation, and multivariable analyses for all vignettes found no significant relationship between implicit biases and clinical assessments. Regression coefficient for the association between pain assessment and race IAT scores was −0.49 (95% CI, −1.00 to 0.03) and for social class, the coefficient was −0.04 (95% CI, −0.50 to 0.41). Adjusted odds ratios for other vignettes ranged from 0.69 to 3.03 per unit change in IAT score, but none were statistically significant. Analysis stratified by vignette patient race or class status yielded similarly negative results. Tests for interactions between patient race or class status and student IAT D scores in predicting clinical assessments were not statistically significant. Conclusions The majority of first-year medical students at a single school had IAT scores consistent with implicit preference for white persons and possibly for those in the upper class. However, overall vignette-based clinical assessments were not associated with patient race or occupation, and no association existed between implicit preferences and the assessments.

No abstract

No abstract

Systematic review/guideline, level III.

Background Risk-adjusted analyses are critical in evaluating trauma outcomes. The National Trauma Data Bank (NTDB) is a statistically robust registry that allows such analyses; however, analytical techniques are not yet standardized. In this study, we examine peer-reviewed manuscripts published using NTDB data, with particular attention to characteristics strongly associated with trauma outcomes. Our objective is to determine if there are substantial variations in the methodology and quality of risk-adjusted analyses and thus, whether the development of best practices for risk-adjusted analyses is warranted. Study Design A database of all studies utilizing NTDB data published through December 2010 was created by searching Pubmed and Embase. Studies with multivariate risk-adjusted analyses were examined for their central question, main outcome measures, analytical techniques, the co-variates in adjusted analyses, and handling of missing data. Results Of 286 NTDB publications, 122 performed a multivariable adjusted analysis. These studies focused on Clinical Outcomes (51), Public Health Policy or Injury Prevention (30), Quality (16), Disparities (15), Trauma Center Designation (6) or Scoring Systems (4). Mortality was the main outcome in 98 of these studies. There were considerable differences in the co-variates used for case adjustment. The three most frequently controlled for co-variates were age (95%), Injury Severity Score (85%) and gender (78%). Up to 43% of studies did not control for the five basic covariates necessary to conduct a risk-adjusted analysis of trauma mortality. Less than 10% of studies used clustering to adjust for facility differences or imputation to handle missing data. Conclusions There is significant variability in how risk-adjusted analyses using data from the NTDB are performed. Best practices are needed to further improve the quality of research from the NTDB.

The ABC score is a valid instrument to predict MT early in the patient's care and across various demographically diverse trauma centers. Future research should focus on this score's ability to prospectively identify patients who will receive MT.

Venous thromboembolism is associated with substantial morbidity and mortality and is largely preventable. Despite this fact, appropriate prophylaxis is vastly underutilized. To improve compliance with best practice prophylaxis for VTE in hospitalized trauma patients, we implemented a mandatory computerized provider order entry-based clinical decision support tool. The system required completion of checklists of VTE risk factors and contraindications to pharmacologic prophylaxis. With this tool, we were able to determine a patient's risk stratification level and recommend appropriate prophylaxis. To evaluate the effect of our mandatory computerized provider order entry-based clinical decision support tool on compliance with prophylaxis guidelines for venous thromboembolism (VTE) and VTE outcomes among admitted adult trauma patients.

Objective In 2012, Medicare began cutting reimbursement for hospitals with high readmission rates. We sought to define the incidence and risk factors associated with readmission after surgery. Methods A total of 230,864 patients discharged after general, upper gastrointestinal (GI), small and large intestine, hepatopancreatobiliary (HPB), vascular, and thoracic surgery were identified using the 2011 American College of Surgeons National Surgical Quality Improvement Program. Readmission rates and patient characteristics were analyzed. A predictive model for readmission was developed among patients with length of stay (LOS) 10 days or fewer and then validated using separate samples. Results Median patient age was 56 years; 43% were male, and median American Society of Anesthesiologists (ASA) class was 2 (general surgery: 2; upper GI: 3; small and large intestine: 2; HPB: 3; vascular: 3; thoracic: 3; P < 0.001). The median LOS was 1 day (general surgery: 0; upper GI: 2; small and large intestine: 5; HPB: 6; vascular: 2; thoracic: 4; P < 0.001). Overall 30-day readmission was 7.8% (general surgery: 5.0%; upper GI: 6.9%; small and large intestine: 12.6%; HPB: 15.8%; vascular: 11.9%; thoracic: 11.1%; P < 0.001). Factors strongly associated with readmission included ASA class, albumin less than 3.5, diabetes, inpatient complications, nonelective surgery, discharge to a facility, and the LOS (all P < 0.001). On multivariate analysis, ASA class and the LOS remained most strongly associated with readmission. A simple integer-based score using ASA class and the LOS predicted risk of readmission (area under the receiver operator curve 0.702). Conclusions Readmission among patients with the LOS 10 days or fewer occurs at an incidence of at least 5% to 16% across surgical subspecialties. A scoring system on the basis of ASA class and the LOS may help stratify readmission risk to target interventions.