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Abstract Inpatient boarding (holding patients in the emergency department [ED] while awaiting an inpatient bed) is associated with increased risk of delirium, medication safety events, and hospital mortality in older adults. We investigated boarding trends across age strata to determine if older patients had elevated rates compared to younger patients. Administrative data for ED encounters resulting in admission from 3 healthcare systems (2 Midwest, 1 Northeast) from 1/1/19 to 12/31/24 were reviewed. Age was categorized by strata: < 21, 21-64, 65-74, 75-84, and ≥ 85. Based on the CMS Age Friendly Hospital Measures, the proportion of patients boarding for 3+ hours was calculated within each year and age strata. Boarding rates varied substantially by system and age group. At Systems 1 (S1) and 3 (S3), ≥ 85 patients had the highest rates (S1: 54.9%, S3: 70.9% in 2024) and, at System 2 (S2), all adult patients (21+) had similar rates (20.5-22.4% in 2024). Boarding rates increased in all systems over the study period. At S1 and S3, < 21 patients had the highest average yearly increase in boarding (S1: 7.4%, S3: 3.9%). At S2, boarding increased most in ≥ 85 (23.9%). In this multisystem evaluation, approximately one in two older adults experience ED boarding, with the oldest patients (≥ 85) facing the greatest exposure to boarding in recent years. These findings taken alongside known delays and safety risks associated with boarding and patient care complexity amongst the oldest adults may result in disproportionate harm to some of the most vulnerable patients.

Importance The choice of induction agent during rapid sequence intubation (RSI) of critically ill adults may affect clinical outcomes. Although ketamine and etomidate are frequently used for RSI, their comparative effectiveness remains controversial. Objective To compare the safety of etomidate vs ketamine for emergency RSI in critically ill adults. Design, Setting, and Participants This cohort study used a target trial emulation with observational data collected between March 1, 2022, and April 30, 2024, from 18 emergency departments across Brazil, with data from the Brazilian Airway Registry Cooperation. Adults who underwent RSI and received either etomidate or ketamine as a sole hypnotic agent were included; those with preintubation cardiac arrest or immediate postintubation transfer were excluded. Exposure Administration of etomidate or ketamine as the induction agent for RSI. Main Outcomes and Measures The primary outcome was 28-day in-hospital mortality. Secondary outcomes included 7-day in-hospital mortality, first-attempt intubation success, and major adverse events (new hemodynamic instability, severe hypoxemia, and cardiac arrest) within 30 minutes after intubation. Inverse probability of treatment weighting was used to adjust for confounding. Risk ratios (RRs) and risk differences (RDs) with 95% CIs were used to compare outcomes between groups. Results Among 1810 patients (median age, 64 years [IQR, 50-74 years]; 1048 men [57.9%]), 514 received ketamine and 1296 received etomidate. The median shock index was higher in the ketamine group than the etomidate group (0.81 [IQR, 0.65-1.01] vs 0.76 [IQR, 0.59-0.99]), and preintubation vasopressor use was more common in the ketamine group than the etomidate group (191 of 514 [37.2%] vs 391 of 1296 [30.2%]). Weighted 28-day mortality was higher with etomidate than ketamine (60.5% [95% CI, 57.2%-63.8%] vs 54.4% [95% CI, 45.0%-63.9%]; RR, 1.14 [95% CI, 1.03-1.27]; RD, 7.6% [95% CI, 2.0%-13.3%]). Seven-day mortality was also higher with etomidate than ketamine (35.2% [95% CI, 32.0%-38.3%] vs 30.1% [95% CI, 23.5%-36.7%]; RR, 1.19 [95% CI, 1.04-1.35]). New hemodynamic instability within 30 minutes after intubation was more frequent with ketamine (24.2% [95% CI, 20.4%-28.0%] vs 18.9% [95% CI, 16.7%-21.0%]; RR, 0.78 [0.64-0.95]). There were no statistically significant differences in the other secondary outcomes. Conclusions and Relevance In this cohort study of critically ill adults undergoing RSI, etomidate use was associated with higher in-hospital mortality at 7 and 28 days compared with ketamine. These findings highlight the need for definitive randomized clinical trials to compare both agents.

Importance The 2007 US Food and Drug Administration (FDA) Amendments Act (FDAAA) expanded its safety-related regulatory authorities, including enhanced postmarketing safety surveillance and new clinical study requirements. However, whether FDAAA has been associated with differences in the frequency and timing of postmarket safety-related actions remains poorly understood. Objectives To assess whether FDAAA was associated with differences in time to first FDA postmarket drug safety−related action, and to assess whether therapeutic and regulatory characteristics were associated with differences in time to these actions post-FDAAA implementation. Design and Setting This was a cross-sectional study of all novel therapeutics approved by FDA between January 1, 2001, and December 31, 2019, and followed up through December 31, 2024. Approvals were categorized as pre- or post-FDAAA (before or after March 25, 2008). Post-FDAAA therapeutic and regulatory characteristics included drug class, therapeutic area, orphan status, special regulatory pathway, and presence of a boxed warning or FDAAA-mandated postmarket study requirement at approval. Main Outcomes and Measures Time to first FDA postmarket drug safety−related action, a composite of withdrawals due to safety concerns, incremental boxed warnings, and safety-related communications. Results Of the 560 novel therapeutics approved, FDA took postmarket safety-related actions for 130 (23.2%) during a median (IQR) follow-up of 12.1 (7.8-18.2) years. These comprised actions within 5 years of approval for 34 of 164 therapeutics (20.7%) approved pre-FDAAA, and 57 of 396 (14.4%) approved post-FDAAA (rate ratio, 0.69; 95% CI, 0.47-1.02; P = .06). Compared to pre-FDAAA approvals, after accounting for therapeutic and regulatory characteristics, there was no statistically significant difference in time to first postmarket safety-related action for post-FDAAA approvals (time ratio, 0.40; 95% CI, 0.15-1.07; P = .07). However, among therapeutics with postmarket safety-related actions within 5 years of approval, median time to first action was shorter post-FDAAA (median [IQR], 3.1 (2.0-4.2) years for pre-FDAAA vs 1.8 [1.3-2.5] years post-FDAAA; P = .004). Among 260 novel therapeutics approved post-FDAAA, after the October 2013 enactment of breakthrough therapy designation, the following therapeutic and regulatory characteristics were associated with time to first postmarket safety-related action: small molecule type (time ratio, 0.24; 95% CI, 0.07-0.81; P = .02), orphan designation (time ratio, 8.29; 95% CI, 2.43-28.27; P < .001), fast track (time ratio, 0.22; 95% CI, 0.08-0.64; P = .005), breakthrough therapy designation (time ratio, 0.10; 95% CI, 0.03-0.32; P < .001), prolonged regulatory review time (>400 days; time ratio, 0.16; 95% CI, 0.03-0.73; P = .02), and FDAAA-mandated postmarket study requirements at approval (time ratio, 0.35; 95% CI, 0.15-0.80; P = .01). Conclusions and Relevance This cross-sectional analysis found that the enhanced safety-related regulatory authorities of FDAAA were not associated with differences in time to first postmarket safety-related action. However, among therapeutics with postmarket safety-related actions within 5 years of approval, median time to first action was shorter post-FDAAA implementation.

Importance Validation of prognostic tools is an essential component of their integration into clinical practice. Objective To validate 4 delirium risk stratification tools in an independent emergency department (ED) cohort. Design, Setting, and Participants This prognostic study included a retrospective cohort of patients 65 years or older who presented to an academic ED between January 1, 2021, and December 31, 2024. Data were analyzed from February 10 to August 21, 2025. Exposure Delirium screening included the Delirium Triage Screen followed by the brief Confusional Assessment Method as part of the standard of care. Four delirium risk scores were obtained, including the Kennedy rule, the Zucchelli rule, the Mayo Delirium Prediction (MDP) tools, and the Recognizing Delirium in Emergency Medicine (REDEEM) score. Main Outcomes and Measures Main outcomes included risk score performances and diagnostic test accuracy measured using the area under the receiver operating characteristics curve (AUROC), sensitivity, specificity, negative (NPV) and positive (PPV) predictive values, and positive and negative likelihood ratios (LRs) with 95% CIs. Secondary outcomes were discriminative and calibration measures. Results A total of 44 578 patients were included, of whom 1701 (3.8%) were diagnosed with delirium. The median age was 80.0 (IQR, 75.0-85.0) years, and 22 786 patients (51.1%) were female. The Kennedy rule had an AUROC of 0.777 (95% CI, 0.766-0.789). At a cutoff of 5, sensitivity was 0.55 (95% CI, 0.52-0.57); specificity, 0.85 (95% CI, 0.84-0.85); positive LR, 3.54 (95% CI, 3.37-3.72); negative LR, 0.54 (95% CI, 0.51-0.57); PPV, 0.12 (95% CI, 0.12-0.13); and NPV, 0.98 (95% CI, 0.98-0.98). The Zucchelli tool had an AUROC of 0.701 (95% CI, 0.686-0.713). At a cutoff of 5, sensitivity was 0.68 (95% CI, 0.66-0.70); specificity, 0.66 (95% CI, 0.65-0.66); positive LR, 1.99 (95% CI, 1.92-2.06); negative LR, 0.49 (95% CI, 0.45-0.52); PPV, 0.07 (95% CI, 0.07-0.08); and NPV, 0.98 (95% CI, 0.98-0.98). The MDP tool had an AUROC of 0.898 (95% CI, 0.891-0.905). At a 30% cutoff, sensitivity was 0.51 (95% CI, 0.48-0.53); specificity, 0.95 (95% CI, 0.95-0.95); positive LR, 9.69 (95% CI, 9.11-10.31); negative LR, 0.52 (95% CI, 0.50-0.55); PPV, 0.28 (95% CI, 0.26-0.29); and NPV, 0.98 (95% CI, 0.98-0.98). The REDEEM score demonstrated the highest AUROC at 0.921 (95% CI, 0.914-0.929). Using a cutoff of 11 or greater, sensitivity was 0.83 (95% CI, 0.81-0.85); specificity, 0.92 (95% CI, 0.91-0.92), negative LR, 0.18 (95% CI, 0.17-0.20); positive LR, 9.91 (95% CI, 9.54-10.29); PPV, 0.28 (95% CI, 0.27-0.29); and NPV, 0.99 (95% CI, 0.99-0.99). Conclusions and Relevance In this prognostic study comparing 4 delirium tools to improve delirium detection and identify high-risk patients, the REDEEM score and the MDP tool had better performance for delirium detection in the ED. These findings lay the groundwork for integrating validated risk stratification into ED workflows to improve early delirium detection and inform prevention strategies for high-risk older adults.

ABSTRACT Background The Geriatric Emergency Department (ED) guidelines recommend screening older adults for delirium using evidence‐based screening tools, but these tools are often underutilized. We aimed to identify barriers and facilitators to implementing an electronic health record (EHR)‐based delirium screening tool as intended. Methods This mixed methods and focused ethnographic study combined a review of structured delirium screening data with observations of real‐time delirium screenings and semi‐structured in‐person interviews at an academic ED that previously implemented the Delirium Triage Screen (DTS) and Brief Confusion Assessment Method (bCAM) tool. Content analysis of field notes from observations and interview transcripts was guided by the Exploration, Preparation, Implementation, and Sustainment implementation framework. Results From a total of 40,818 ED visits, 6196 (15.2%) had incomplete screens (i.e., without fidelity). We observed 62 encounters, of which 25 (40.3%) screenings were implemented without fidelity due to (1) not asking the required screening questions, (2) assuming patient responses, or (3) not completing the screen due to uncertainty regarding a patient's baseline mentation. We conducted 32 interviews. Identified barriers included staff prioritization of other tasks (e.g., stroke code, cleaning patients), limited knowledge of the screen's importance and utility, and language discordance. Facilitators included care partners providing baseline mental status information and nurses prefacing the screening to increase patient engagement. Conclusion The fidelity of ED delirium screening is influenced by an interplay of environmental, patient, provider, and caregiver factors. Fidelity may be improved by focusing education on the importance of screening, training screeners on how to determine whether a patient's mentation is acutely changed, providing clear action steps when a patient screens positive, and addressing how to administer the delirium screen to patients who do not speak English fluently.

Abstract Introduction The rapidly ageing population and multimorbidity are associated with increased emergency department (ED) visits by older adults. In the ED, older adults have higher risk of hospitalization, functional and cognitive decline, and mortality. Boarding, holding admitted patients in the ED awaiting a hospital bed, exacerbates these negative outcomes, which disproportionately affect older adults. Methods We conducted a cross-sectional analysis to investigate US boarding trends by age using clinical administrative data from 5 health systems and publicly available NHAMCS data from 2018 to 2024. Results Boarding ≥3 h in the ED has increased across diverse hospital types, with oldest adults (85+) facing the greatest risk (System 4: IRR [95% CI] = 1.18 [1.15-1.20], System 5: IRR [95% CI] = 1.20 [1.17-1.23], System 3 [Community Hospital]: IRR [95% CI] = 1.25 [1.19-1.33]). These results were recapitulated at the national level in NHAMCS (IRR [95% CI] = 1.30 [1.05-1.61]). Discussion The trend of increased boarding has serious implications for patients, caregivers, and health systems. The 2025 CMS Age-Friendly Hospital Measure offers opportunities to improve processes and procedures to mitigate the negative effects of hospital boarding on older patients. We highlight opportunities to address this challenge, including ongoing quality improvement initiatives, bed prioritization algorithms, and alternate admission pathways.

Abstract Background Opioid stewardship policies could adversely affect pain management for patients with cancer. Yet patients with cancer are also at risk for opioid‐related harms. This study sought to determine trends in opioid prescribing by clinical stratum and pain for patients with cancer from 2016 to 2020. Methods A retrospective study was conducted of opioid‐naive adults with newly diagnosed cancer from 2016 to 2020 ( N = 10,232) in a large Connecticut health system. Logistic regression was used to calculate changes in the predicted probability of opioid prescribing from 2016 to 2020. Two subpopulations were examined: patients treated surgically ( n = 4405) and patients with metastatic cancer ( n = 2158). Flowsheet pain scores for patients with metastatic cancer were used to stratify by no pain (all scores, 0) versus any pain. The main outcomes were new (≥1 prescription in the 0–6 months after diagnosis) and additional (0–6 and 7–9 months) opioid prescriptions. Results A decline was observed in the predicted probability of new (71.1% to 64.6%; p < .001) and additional prescribing (27.2% to 24.2%; p = .07 [not significant]) declined. Among surgical patients, the predicted probability of new opioid prescribing fell (96.0% to 88.6%; p < .001), whereas additional prescribing was stable (13%). For patients with metastatic cancer with pain, new opioid prescribing was stable (56%). For those reporting no pain, the predicted probability of new opioid prescribing declined from 61.6% to 36.1% ( p < .001). Conclusions In the context of widespread policy changes, this study showed a modest decline in new and additional opioid prescribing for patients with cancer. In metastatic cancer, prescribing remained stable for patients reporting pain and declined steeply for those reporting no pain.

ABSTRACTObjectivesWe describe the types of emergency department (ED) visits managed by non‐physician providers (NPPs), including physician assistants and nurse practitioners, and emergency medicine (EM) physicians, assessing shifts in care patterns over time.MethodsWe used data from the National Hospital Ambulatory Medical Care Survey collected from 2009 to 2021. We classified visits by provider type: physician only, physician with resident, physician with NPP, and NPP only. We described characteristics of visits by provider type, including patient demographics, triage urgency, imaging, length of stay, and disposition, and analyzed using Poisson regression. We described the change in type of provider seen over this study period and further analyzed by triage urgency and hospital location.ResultsOf 1.684 billion estimated ED visits from 2009 to 2021, 1.171 billion were managed by physicians without residents or NPPs (physicians only), 136.3 million by physicians with residents, 209.1 million by physicians with NPPs, and 167.4 million by NPPs only. Patients seen by physicians only were older, were triaged as having more urgent needs, had a longer ED length of stay, and were more likely to be admitted compared to those seen by NPPs only. Physician‐only visits decreased from 77% to 62%, while NPP‐only visits increased from 6% to 11%. The physician with the NPP group similarly grew from 9% to 17%. For visits assigned a triage urgency level of 2 (“emergent”), physician‐only visits decreased by 20%, physician with NPP visits increased by 13%, and NPP‐only visits increased by 3%. In metropolitan areas, physician‐only visits dropped 14%, with a 5% increase in NPP‐only visits. In non‐metropolitan areas, physician‐only visits decreased 17%, with a 9% increase in NPP‐only visits.ConclusionsThe EM workforce has shifted, with NPPs seeing a higher percentage of patients, including both lower‐ and higher‐acuity patients. This shift is particularly prominent in rural areas but is evident across all regions.

Abstract In comparative effectiveness research (CER), ensuring internal, construct, and external validity is crucial. Internal validity determines whether observed outcomes are causally linked to an intervention; construct validity assesses whether a study measures what it intends to; and external validity relates to generalizability in routine practice. Double-blind randomized trials optimize internal validity by minimizing bias and confounding, while construct validity is strengthened through pre-specified protocols and standardized data collection. However, controlled conditions limit external validity. Pragmatic RCTs improve generalizability but may compromise internal validity due to open-label designs. Observational CER studies—including observational studies following the target trial emulation framework—offer broader external validity and feasibility in less time and at lower cost. However, due to lack of random assignment, these studies are susceptible to measured and unmeasured confounding. Several techniques help mitigate these concerns, including a detailed pre-specified protocol, tools such as propensity score matching to balance measured confounders, falsification endpoint testing for assessing the presence of unmeasured confounders, and quasi-experimental designs (including instrumental variable analysis), which may be able to address both. Pre-specified sensitivity analyses and triangulation with complementary data sources further enhance robustness. Construct validity in observational CER depends on accurate patient profiling and validated computational phenotypes for identifying patients, exposures, and outcomes. Thoughtful study design and analytic rigor are essential for balancing these validity considerations. This brief review highlights these issues with examples from thrombosis research.