Stigmatizing language used in medical records to describe patients can influence subsequent physicians-in-training in terms of their attitudes towards the patient and their medication prescribing behavior. This is an important and overlooked pathway by which bias can be propagated from one clinician to another. Attention to the language used in medical records may help to promote patient-centered care and to reduce healthcare disparities for stigmatized populations.

and population density (interdecile OR, 0.70 [95% CI, 0.32-1.51]) or poverty rate (interdecile OR, 2.03 [95% CI, 0.97-4.25]). Neighborhood-level variables were moderately to highly correlated (r = 0.66-0.83). Discussion | In this study, SARS-CoV-2 transmission among pregnant women in New York City was associated with neighborhood-and building-level markers of large household membership, household crowding, and low socioeconomic status. These data may aid policy makers in the design of interventions to reduce the spread of SARS-CoV-2. A key strength of this study was the use of a universally tested population, which allowed for ascertainment of asymptomatic cases among a defined at-risk population. Limitations of the study include that the findings may not apply to other populations given the unique demographic, physiologic, and social features of pregnant women. Additionally, the small sample size and high degree of correlation between neighborhood-level variables precluded multivariable analysis. Nonetheless, this study provides empirical support for the hypothesis that variation in the urban environment may be an important social determinant of SARS-CoV-2 transmission.

Early recognition and treatment of sepsis are linked to improved patient outcomes. Machine learning-based early warning systems may reduce the time to recognition, but few systems have undergone clinical evaluation. In this prospective, multi-site cohort study, we examined the association between patient outcomes and provider interaction with a deployed sepsis alert system called the Targeted Real-time Early Warning System (TREWS). During the study, 590,736 patients were monitored by TREWS across five hospitals. We focused our analysis on 6,877 patients with sepsis who were identified by the alert before initiation of antibiotic therapy. Adjusting for patient presentation and severity, patients in this group whose alert was confirmed by a provider within 3 h of the alert had a reduced in-hospital mortality rate (3.3%, confidence interval (CI) 1.7, 5.1%, adjusted absolute reduction, and 18.7%, CI 9.4, 27.0%, adjusted relative reduction), organ failure and length of stay compared with patients whose alert was not confirmed by a provider within 3 h. Improvements in mortality rate (4.5%, CI 0.8, 8.3%, adjusted absolute reduction) and organ failure were larger among those patients who were additionally flagged as high risk. Our findings indicate that early warning systems have the potential to identify sepsis patients early and improve patient outcomes and that sepsis patients who would benefit the most from early treatment can be identified and prioritized at the time of the alert

Our results indicate that clinicians who perceive prescribing as a categorical choice between patients remaining ill or possibly improving from therapy are more likely to prescribe antibiotics. However, this strategy assumes that antibiotics are essentially harmless. Clinicians who framed decision-making as a choice between potential harms from therapy and continued patient illness (e.g., increased appreciation of potential harms) had lower prescribing rates. These results suggest that interventions to reduce inappropriate prescribing should emphasize the non-negligible possibility of serious side effects.

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Machine learning-based clinical decision support tools for sepsis create opportunities to identify at-risk patients and initiate treatments earlier, critical to improving sepsis outcomes. Increasing use of such systems necessitates quantifying and understanding provider adoption. Using realtime provider interactions with a sepsis early detection tool (Targeted Real-time Early Warning System) deployed at five hospitals over a two-year period (469,419 screened encounters, 9,805 (2.1%) retrospectively-identified sepsis cases), we found high sensitivity (82% of sepsis cases identified), high adoption rates (89% of alerts evaluated by a physician or advanced practice provider and 38% of evaluated alerts confirmed) and an association between use of the tool and earlier treatment of sepsis patients (1.85 (95% CI:1.66-2.00) hour reduction in median time to first antibiotics order). Further, we found that provider-related factors were strongly associated with adoption. Beyond improving system performance, efforts to improve adoption should focus on provider knowledge, experience, and perceptions of the system.

Objectives With clinical use of high‐sensitivity troponin I (hsTnI), more frequent troponin elevations will occur. However, the burden and implications of these elevations are not well understood. The authors quantified the prevalence of elevated hsTnI in patients presenting with possible acute coronary syndrome (ACS) who do not have elevated troponin with a current generation assay (cardiac troponin I [cTnI]) and determined the association of these newly detected elevations with a composite of all‐cause mortality and subsequent cardiac hospitalization. Methods This was a prospective observational study of 808 subjects evaluated for possible ACS and followed for up to 1 year. Troponin values were measured with hsTnI (Abbott Laboratories) and cTnI (Abbott and Beckman Coulter). Cardiac hospitalization was defined as hospitalization for ACS, revascularization, acute heart failure (AHF), or tachy/brady arrhythmia that occurred after the index emergency department (ED) visit or hospital discharge. Results Forty subjects (5%) were diagnosed with ACS (26 myocardial infarction and 14 unstable angina). On the initial sample, the prevalence of elevated hsTnI among subjects with nonelevated cTnI was 9.2% using a gender‐neutral cutoff (95% confidence interval [CI] = 7.1% to 11.4%) and 11.1% using a gender‐specific cutoff (95% CI = 8.8% to 13.4%). Adjudicated diagnoses for subjects whose initial samples had elevated hsTnI but nonelevated cTnI (gender‐neutral cutoff) were as follows: three (4.6%) ACS, 15 (23.1%) AHF, three (4.6%) volume overload etiology unclear/noncardiac, three (4.6%) cardiac (non‐ACS), and 41 (63.1%) other. Of the 65 patients whose initial samples had hsTnI but nonelevated cTnI, eight developed cTnI elevation on subsequent serial sampling. After traditional cardiovascular risk factors and renal function were adjusted for, subjects with elevated initial hsTnI but nonelevated cTnI (initial and serial sampling) had a higher risk of all‐cause mortality and subsequent cardiac hospitalization than subjects with both nonelevated hsTnI and nonelevated cTnI (hazard ratio [HR] = 1.91, 95% CI = 1.14 to 3.19). Conclusions On the initial sample, 9% to 11% of subjects without cTnI elevation had hsTnI elevation. Although the majority of the patients with these newly detected hsTnI elevations did not have ACS, they had a higher risk for all‐cause mortality and subsequent cardiac hospitalization.