IMPORTANCE It is unclear whether antimicrobial timing for sepsis has changed outside of performance incentive initiatives. OBJECTIVE To examine temporal trends and variation in time-to-antibiotics for sepsis in the US Department of Veterans Affairs (VA) health care system. DESIGN, SETTING, AND PARTICIPANTS This observational cohort study included 130 VA hospitals from 2013 to 2018. Participants included all patients admitted to the hospital via the emergency department with sepsis from 2013 to 2018, using a definition adapted from the Centers for Disease Control and Prevention Adult Sepsis Event definition, which requires evidence of suspected infection, acute organ dysfunction, and systemic antimicrobial therapy within 12 hours of presentation. Data were analyzed from October 6, 2020, to July 1, 2021.EXPOSURES Time from presentation to antibiotic administration. MAIN OUTCOMES AND MEASURESThe main outcome was differences in time-to-antibiotics across study periods, hospitals, and patient subgroups defined by presenting temperature and blood pressure. Temporal trends in time-to-antibiotics were measured overall and by subgroups. Hospitallevel variation in time-to-antibiotics was quantified after adjusting for differences in patient characteristics using multilevel linear regression models.RESULTS A total of 111 385 hospitalizations for sepsis were identified, including 107 547 men (96.6%) men and 3838 women (3.4%) with a median (interquartile range [IQR]) age of 68 (62-77) years. A total of 7574 patients (6.8%) died in the hospital, and 13 855 patients (12.4%) died within 30 days. Median (IQR) time-to-antibiotics was 3.9 (2.4-6.5) hours but differed by presenting characteristics. Unadjusted median (IQR) time-to-antibiotics decreased over time, from 4.5 (2.7-7.1) hours during 2013 to 2014 to 3.5 (2.2-5.9) hours during 2017 to 2018 (P < .001). In multilevel models adjusted for patient characteristics, median time-to-antibiotics declined by 9.0 (95% CI, 8.8-9.2) minutes per calendar year. Temporal trends in time-to-antibiotics were similar across patient subgroups, but hospitals with faster baseline time-to-antibiotics had less change over time, with hospitals in the slowest tertile decreasing time-to-antibiotics by 16.6 minutes (23.1%) per year, while hospitals in the fastest tertile decreased time-to-antibiotics by 7.2 minutes (13.1%) per year. In the most recent years (2017)(2018), median time-to-antibiotics ranged from 3.1 to 6.7 hours across hospitals (after adjustment for patient characteristics), 6.8% of variation in time-to-antibiotics was explained at the hospital level, and odds of receiving antibiotics within 3 hours increased by 65% (95% CI, 56%-77%) for the median patient if moving to a hospital with faster time-to-antibiotics.

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Background Few published studies report lessons learned for recruiting older adults from racial/ethnic minority, low SES communities for behavioral interventions. In this article, we describe recruitment processes and results for Take Heart, a randomized controlled trial testing the effectiveness of an adapted heart disease self-management program for primarily African American, urban, low SES adults 50 years or older living in Detroit. Methods Older adults were recruited via community-based (CB), electronic medical record (EMR), and in-person hospital clinic (HC) methods. Recruitment processes, demographic characteristics of enrolled participants, yield and cost, lessons learned, and best practices for each method are described. Results Within 22 months, 1,478 potential participants were identified, 1,223 were contacted and 453 enrolled, resulting in an overall recruitment yield of 37%. The CB method had the highest yield at 49%, followed by HC at 36% and EMR at 16%. Of six CB approaches, information sessions and flyers had the highest yields at 60% and 59%, respectively. The average cost of recruiting and enrolling one participant was $142. Conclusions CB, EMR, and HC methods each made important contributions to reaching our recruitment goal. The CB method resulted in the highest recruitment yield, while EMR had the lowest. Face-to-face interaction with community members and hiring a community health worker were particularly useful in engaging this population. Further research is needed to confirm these findings in urban, minority, low SES populations of older adults.

Most ARISE participants did not meet the Sepsis-3 definition for septic shock at baseline. However, the majority fulfilled the new sepsis definition and mortality was higher than for participants not fulfilling the criteria. A quarter of participants meeting the new sepsis definition did not fulfill the qSOFA screening criteria, potentially limiting its utility as a screening tool for sepsis trials with patients with suspected infection in the ED. The implications of the new definitions for patients not eligible for recruitment into the ARISE trial are unknown.

Heart disease is the leading cause of death in the United States. African Americans and people of low socioeconomic status suffer disproportionately from heart disease-related morbidity and mortality. In Detroit, Michigan, a primarily African American and low-income urban area, heart disease mortality is at twice the national rate. Despite evidence for the effectiveness of self-management support interventions in reducing chronic disease burden for older adults, few are adapted for communities most in need. This article describes the process of adapting Take PRIDE, an evidence-based heart disease self-management intervention, for older adults in Detroit via the Replicating Effective Programs (REP) framework. Working within a community-academic partnership, we found REP useful in facilitating the identification of diverse stakeholders, core versus adaptable elements of the intervention and barriers to implementation. We also made several modifications to the REP framework in order to better fit our project needs. Overall, we found REP to be an effective, flexible tool that allowed us to successfully adapt a disease-management intervention for this setting. Processes, lessons learned, and recommendations offered in this article may help researchers and practitioners working to expand access to self-management support for populations most affected by chronic disease.