Person:

Pallin, Daniel

Introduction: Nothing has been published to describe the practices of medical societies in choosing abstracts for presentations at their annual meetings. We surveyed medical societies to determine their practices, and also present a theoretical analysis of the topic. Methods: We contacted a convenience sample of large U.S. medical conferences, and determined their approach to choosing abstracts. We obtained information from web sites, telephone, and email. Our theoretical analysis compares values-based and empirical approaches for scoring system development. Results: We contacted 32 societies and obtained data on 28 (response rate 88%). We excluded one upon learning that research was not presented at its annual meeting, leaving 27 for analysis. Only 2 (7%) made their abstract scoring process available to submitters. Reviews were blinded in most societies (21;78%), and all but one asked reviewers to recuse themselves for conflict of interest (96%). All required ≥3 reviewers. Of the 24 providing information on how scores were generated, 21 (88%) reported using a single gestalt score, and three used a combined score created from pooled domain-specific sub-scores. We present a framework for societies to use in choosing abstracts, and demonstrate its application in the development of a new scoring system. Conclusions: Most medical societies use subjective, gestalt methods to select research for presentation at their annual meetings and do not disclose to submitters the details of how abstracts are chosen. We present a new scoring system that is transparent to submitters and reviewers alike with an accompanying statement of values and ground rules. We discuss the challenges faced in selecting abstracts for a large scientific meeting and share the values and practical considerations that undergird the new system.

Background: Policymakers advocate universal electronic medical records (EMRs) and propose incentives for “meaningful use” of EMRs. Though emergency departments (EDs) are particularly sensitive to the benefits and unintended consequences of EMR adoption, surveillance has been limited. We analyze data from a nationally representative sample of US EDs to ascertain the adoption of various EMR functionalities. Methodology/Principal: Findings We analyzed data from the National Hospital Ambulatory Medical Care Survey, after pooling data from 2005 and 2006, reporting proportions with 95% confidence intervals (95% CI). In addition to reporting adoption of various EMR functionalities, we used logistic regression to ascertain patient and hospital characteristics predicting “meaningful use,” defined as a “basic” system (managing demographic information, computerized provider order entry, and lab and imaging results). We found that 46% (95% CI 39–53%) of US EDs reported having adopted EMRs. Computerized provider order entry was present in 21% (95% CI 16–27%), and only 15% (95% CI 10–20%) had warnings for drug interactions or contraindications. The “basic” definition of “meaningful use” was met by 17% (95% CI 13–21%) of EDs. Rural EDs were substantially less likely to have a “basic” EMR system than urban EDs (odds ratio 0.19, 95% CI 0.06–0.57, p = 0.003), and Midwestern (odds ratio 0.37, 95% CI 0.16–0.84, p = 0.018) and Southern (odds ratio 0.47, 95% CI 0.26–0.84, p = 0.011) EDs were substantially less likely than Northeastern EDs to have a “basic” system. Conclusions/Significance: EMRs are becoming more prevalent in US EDs, though only a minority use EMRs in a “meaningful” way, no matter how “meaningful” is defined. Rural EDs are less likely to have an EMR than metropolitan EDs, and Midwestern and Southern EDs are less likely to have an EMR than Northeastern EDs. We discuss the nuances of how to define “meaningful use,” and the importance of considering not only adoption, but also full implementation and consequences.

Context: Studies documenting racial/ethnic disparities in health care frequently implicate physicians’ unconscious biases. No study to date has measured physicians’ unconscious racial bias to test whether this predicts physicians’ clinical decisions. Objective: To test whether physicians show implicit race bias and whether the magnitude of such bias predicts thrombolysis recommendations for black and white patients with acute coronary syndromes. Design, Setting, and Participants: An internet-based tool comprising a clinical vignette of a patient presenting to the emergency department with an acute coronary syndrome, followed by a questionnaire and three Implicit Association Tests (IATs). Study invitations were e-mailed to all internal medicine and emergency medicine residents at four academic medical centers in Atlanta and Boston; 287 completed the study, met inclusion criteria, and were randomized to either a black or white vignette patient. Main Outcome Measures: IAT scores (normal continuous variable) measuring physicians’ implicit race preference and perceptions of cooperativeness. Physicians’ attribution of symptoms to coronary artery disease for vignette patients with randomly assigned race, and their decisions about thrombolysis. Assessment of physicians’ explicit racial biases by questionnaire. Results: Physicians reported no explicit preference for white versus black patients or differences in perceived cooperativeness. In contrast, IATs revealed implicit preference favoring white Americans (mean IAT score = 0.36, P < .001, one-sample t test) and implicit stereotypes of black Americans as less cooperative with medical procedures (mean IAT score 0.22, P < .001), and less cooperative generally (mean IAT score 0.30, P  < .001). As physicians’ prowhite implicit bias increased, so did their likelihood of treating white patients and not treating black patients with thrombolysis (P = .009). Conclusions: This study represents the first evidence of unconscious (implicit) race bias among physicians, its dissociation from conscious (explicit) bias, and its predictive validity. Results suggest that physicians’ unconscious biases may contribute to racial/ethnic disparities in use of medical procedures such as thrombolysis for myocardial infarction.

Introduction: Our goal was to develop and validate an index to predict in-hospital mortality in older adults after non-traumatic emergency department (ED) intubations. Methods: We used Vizient administrative data from hospitalizations of 22,374 adults ≥75 years who underwent non-traumatic ED intubation from 2008–2015 at nearly 300 U.S. hospitals to develop and validate an index to predict in-hospital mortality. We randomly selected one half of participants for the development cohort and one half for the validation cohort. Considering 25 potential predictors, we developed a multivariable logistic regression model using least absolute shrinkage and selection operator method to determine factors associated with in-hospital mortality. We calculated risk scores using points derived from the final model’s beta coefficients. To evaluate calibration and discrimination of the final model, we used Hosmer-Lemeshow chi-square test and receiver-operating characteristic analysis and compared mortality by risk groups in the development and validation cohorts. Results: Death during the index hospitalization occurred in 40% of cases. The final model included six variables: history of myocardial infarction, history of cerebrovascular disease, history of metastatic cancer, age, admission diagnosis of sepsis, and admission diagnosis of stroke/ intracranial hemorrhage. Those with low-risk scores (<6) had 31% risk of in-hospital mortality while those with high-risk scores (>10) had 58% risk of in-hospital mortality. The Hosmer-Lemeshow chi-square of the model was 6.47 (p=0.09), and the c-statistic was 0.62 in the validation cohort. Conclusion: The model may be useful in identifying older adults at high risk of death after ED intubation.

Study objective There are limited data on the clinical presentations and management of dabigatran-associated major bleeding outside the clinical trial setting. The aim of this study is to describe clinical characteristics, interventions, and outcomes in patients with dabigatran-associated major bleeding who present to the emergency department (ED). Methods: We performed a retrospective observational chart review study of dabigatran-treated patients with nonvalvular atrial fibrillation who presented with acute major bleeding to the ED. We searched electronic medical record databases cross-referencing medication lists and hemorrhage International Classification of Diseases, Ninth Revision (ICD-9) and ICD-10 codes. We studied the resulting charts to yield confirmed nonvalvular atrial fibrillation in patients with an index event of major bleeding and at least 1 dose of dabigatran in the 5 preceding days. Results: The electronic search yielded 284 cases, and we assessed 93 as ineligible, leaving 191 in the final cohort. Of these, 118 patients (62%) had gastrointestinal hemorrhage; 36 (19%) had intracranial hemorrhage, 8 (4%) of which were nontraumatic cases and 28 (15%) traumatic. Thirty-six (19%) of the index events were in “other” locations and 1 (0.5%) “unknown.” There were 12 deaths (6%): 8 from patients presenting with gastrointestinal bleeding events, 2 from intracranial hemorrhage (both nontraumatic), and 2 from other. Although RBC and plasma transfusions were common, only 11 patients (6%) received purified coagulation factors. Conclusion: Despite rare use of reversal strategies, mortality was low and outcomes were favorable, similar to reported outcomes from clinical trials, in this sample of patients with major bleeding while receiving dabigatran.

Background: Cancer chemotherapy-associated febrile neutropenia (FN) is a common condition that is deadly when bacteremia is present. Detection of bacteremia depends on culture, which takes days, and no accurate predictive tools applicable to the initial evaluation are available. We utilized metabolomics and transcriptomics to develop multivariable predictors of bacteremia among FN patients. Methods: We classified emergency department patients with FN and no apparent infection at presentation as bacteremic (cases) or not (controls), according to blood culture results. We assessed relative metabolite abundance in plasma, and relative expression of 2,560 immunology and cancer-related genes in whole blood. We used logistic regression to identify multivariable predictors of bacteremia, and report test characteristics of the derived predictors. Results: For metabolomics, 14 bacteremic cases and 25 non-bacteremic controls were available for analysis; for transcriptomics we had 7 and 22 respectively. A 5-predictor metabolomic model had an area under the receiver operating characteristic curve of 0.991 (95%CI: 0.972,1.000), 100% sensitivity, and 96% specificity for identifying bacteremia. Pregnenolone steroids were more abundant in cases and carnitine metabolites were more abundant in controls. A 3-predictor gene expression model had corresponding results of 0.961 (95%CI: 0.896,1.000), 100%, and 86%. Genes involved in innate immunity were differentially expressed. Conclusions: Classifiers derived from metabolomic and gene expression data hold promise as objective and accurate predictors of bacteremia among FN patients without apparent infection at presentation, and can provide insights into the underlying biology. Our findings should be considered illustrative, but may lay the groundwork for future biomarker development.