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Developing real-world evidence from electronic health records (EHR) is vital to advance kidney transplantation (KT). We assessed the feasibility of studying KT using the Epic Cosmos aggregated EHR dataset, which includes 274 million unique individuals cared for in 238 U.S. health systems, by comparing it with the Scientific Registry of Transplant Recipients (SRTR). We identified 69,418 KT recipients transplanted between January 2014 and December 2022 in Cosmos (39.4% of all US KT transplants during this period). Demographics and clinical characteristics of recipients captured in Cosmos were consistent with the overall SRTR cohort. Survival estimates were generally comparable, although there were some differences in long-term survival. At 7 years post-transplant, patient survival was 80.4% in Cosmos and 77.8% in SRTR. Multivariable Cox regression showed consistent associations between clinical factors and mortality in both cohorts, with minor discrepancies in the associations between death and both age and race. In summary, Cosmos provides a reliable platform for KT research, allowing EHR-level clinical granularity not available with either the transplant registry or healthcare claims. Consequently, Cosmos will enable novel analyses to improve our understanding of KT management on a national scale., Competing Interests: Declaration of Competing Interest ☒ The authors declare the following financial interests/personal relationships which may be considered as potential competing interests:Michal Mankowski reports financial support was provided by National Institute of Diabetes and Digestive and Kidney Diseases. Dorry Segev reports financial support was provided by National Institute of Allergy and Infectious Diseases. Sunjae Bae reports financial support was provided by National Institute of Diabetes and Digestive and Kidney Diseases. Allan Massie reports was provided by National Institute of Diabetes and Digestive and Kidney Diseases. Alexandra Strauss reports was provided by National Institute of Diabetes and Digestive and Kidney Diseases. Dorry Segev reports a relationship with Sanofi, Novartis, CLS Behring, Jazz Pharmaceuticals, Veloxis, Mallinckrodt, Thermo Fisher Scientific that includes: consulting or advisory and speaking and lecture fees. Eric Oermann reports a relationship with Sofinnova, Google Inc., income from Eikon Therapeutics, and equity in Artisight, Delvi. that includes: consulting or advisory, employment, and equity or stocks. Alexandra Strauss is a member of the Epic Hepatology Specialty Steering Board. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier Inc.)

Background: Despite the central role of experiential learning in residency training, the actual clinical experiences residents participate in are not well characterized. A better understanding of the type, volume, and variation in residents' clinical experiences is essential to support precision medical education strategies., Objective: We sought to characterize the entirety of the clinical experiences had by individual internal medicine residents throughout their time in training., Method: We evaluated the clinical experiences of medicine residents (n = 51) who completed training at NYU Grossman School of Medicine's Brooklyn campus between 2020 and 2023. Residents' inpatient and outpatient experiences were identified using notes written, orders placed, and care team sign-ins; principal ICD-10 codes for each encounter were converted into medical content categories using a previously described crosswalk tool., Results: Of 152,426 clinical encounters with available ICD-10 codes, 132,284 were mapped to medical content categories (94.5% capture). Residents' clinical experiences were particularly enriched in infectious and cardiovascular disease; most had very little exposure to allergy, dermatology, oncology, or rheumatology. Some trainees saw twice as many cases in a given content area as did others. There was little concordance between actual frequency of clinical experience and expected content frequency on the ABIM certification exam., Conclusions: Individual residents' clinical experiences in training vary widely, both in number and in type. Characterizing these experiences paves the way for exploration of the relationships between clinical exposure and educational outcomes, and for the implementation of precision education strategies that could fill residents' experiential gaps and complement strengths with targeted educational interventions., (© 2024 Society of Hospital Medicine.)

Background: We examined effects of single-nucleotide variants (SNVs) of IL1RN, the gene encoding the anti-inflammatory interleukin 1 receptor antagonist (IL-1Ra), on the cytokine release syndrome (CRS) and mortality in patients with acute severe respiratory syndrome coronavirus 2 (SARS-CoV-2) infection., Methods: IL1RN CTA haplotypes formed from 3 SNVs (rs419598, rs315952, rs9005) and the individual SNVs were assessed for association with laboratory markers of inflammation and mortality. We studied 2589 patients hospitalized with SARS-CoV-2 between March 2020 and March 2021., Results: Mortality was 15.3% and lower in women than men (13.1% vs 17.3%, P = .0003). Carriers of the CTA-1/2 IL1RN haplotypes exhibited decreased inflammatory markers and increased plasma IL-1Ra. Evaluation of the individual SNVs of the IL1RN, carriers of the rs419598 C/C SNV exhibited significantly reduced inflammatory biomarker levels and numerically lower mortality compared to the C/T-T/T genotype (10.0% vs 17.8%, P = .052) in men, with the most pronounced association observed in male patients ≤74 years old, whose mortality was reduced by 80% (3.1% vs 14.0%, P = .030)., Conclusions: The IL1RN haplotype CTA and C/C variant of rs419598 are associated with attenuation of the CRS and decreased mortality in men with acute SARS-CoV-2 infection. The data suggest that the IL1RN pathway modulates the severity of coronavirus disease 2019 (COVID-19) via endogenous anti-inflammatory mechanisms., Competing Interests: Potential conflicts of interest. All authors: No reported conflicts. All authors have submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest. Conflicts that the editors consider relevant to the content of the manuscript have been disclosed., (© The Author(s) 2024. Published by Oxford University Press on behalf of Infectious Diseases Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

The recombinant SARS-CoV-2 Omicron XBB.1.5 variant was first detected in New York City (NYC) and rapidly became the predominant variant in the area by early 2023. The increased occurrence of circulating variants within the SARS-CoV-2 XBB-sublineage prompted the modification of COVID-19 mRNA vaccines by Moderna and Pfizer-BioNTech. This update, implemented in mid-September 2023, involved the incorporation of a monovalent XBB.1.5 component. Considering that NYC probably played a central role in the emergence of the XBB.1.5 variant, we conducted phylogeographic analysis to investigate the emergence and spread of this variant in the metropolitan area. Our analysis confirms that XBB.1.5 emerged within or near the NYC area and indicates that XBB.1.5 had a diffusion velocity similar to that of the variant Alpha in the same study area. Additionally, the analysis of 2,392 genomes collected in the context of the genomic surveillance program at NYU Langone Health system showed that there was no increased proportion of XBB.1.5, relative to all cocirculating variants, in the boosted compared to unvaccinated individuals. This study provides a comprehensive description of the emergence and dissemination of XBB.1.5., Competing Interests: Mark J. Mulligan reports potential competing interests: clinical trials and laboratory research contract funding for vaccines and monoclonal antibodies for SARS-CoV-2 with Lilly, Pfizer, and Sanofi; personal fees for Scientific Advisory Board service from Merck, Meissa Vaccines, Inc., and Pfizer. All other authors declare no conflicts of interest., (© The Author(s) 2024. Published by Oxford University Press.)

Background: Socio-economic status, living environments, and race have been implicated in the development of different congenital abnormalities. As orofacial clefting is the most common anomaly affecting the face, an understanding of its prevalence in the United States and its relationship with different determinants of health is paramount. Therefore, the purpose of this study is to determine the modern prevalence of oral-facial clefting in the United States and its association with different social determinants of health. Methods: Utilizing Epic Cosmos, data from approximately 180 US institutions were queried. Patients born between November 2012 and November 2022 were included. Eight orofacial clefting (OC) cohorts were identified. The Social Vulnerability Index (SVI) was used to assess social determinants of health. Results: Of the 15,697,366 patients identified, 31,216 were diagnosed with OC, resulting in a prevalence of 19.9 (95% CI: 19.7-20.1) per 10,000 live births. OC prevalence was highest among Asian (27.5 CI: 26.2-28.8) and Native American (32.8 CI: 30.4-35.2) patients and lowest among Black patients (12.96 CI: 12.5-13.4). Male and Hispanic patients exhibited higher OC prevalence than female and non-Hispanic patients. No significant differences were found among metropolitan (20.23/10,000), micropolitan (20.18/10,000), and rural populations (20.02/10,000). SVI data demonstrated that OC prevalence was positively associated with the percentage of the population below the poverty line and negatively associated with the proportion of minority language speakers. Conclusions: This study examined the largest US cohort of OC patients to date to define contemporary US prevalence, reporting a marginally higher rate than previous estimates. Multiple social determinants of health were found to be associated with OC prevalence, underscoring the importance of holistic prenatal care. These data may inform clinicians about screening and counseling of expectant families based on socio-economic factors and direct future research as it identifies potential risk factors and provides prevalence data, both of which are useful in addressing common questions related to screening and counseling.

The COVID-19 pandemic has boosted digital health utilization, raising concerns about increased physicians' after-hours clinical work ("work-outside-work"). The surge in patients' digital messages and additional time spent on work-outside-work by telemedicine providers underscores the need to evaluate the connection between digital health utilization and physicians' after-hours commitments. We examined the impact on physicians' workload from two types of digital demands - patients' messages requesting medical advice (PMARs) sent to physicians' inbox (inbasket), and telemedicine. Our study included 1716 ambulatory-care physicians in New York City regularly practicing between November 2022 and March 2023. Regression analyses assessed primary and interaction effects of (PMARs) and telemedicine on work-outside-work. The study revealed a significant effect of PMARs on physicians' work-outside-work and that this relationship is moderated by physicians' specialties. Non-primary care physicians or specialists experienced a more pronounced effect than their primary care peers. Analysis of their telemedicine load revealed that primary care physicians received fewer PMARs and spent less time in work-outside-work with more telemedicine. Specialists faced increased PMARs and did more work-outside-work as telemedicine visits increased which could be due to the difference in patient panels. Reducing PMAR volumes and efficient inbasket management strategies needed to reduce physicians' work-outside-work. Policymakers need to be cognizant of potential disruptions in physicians carefully balanced workload caused by the digital health services., (© 2024. The Author(s).)

Background: High rates of vaccination and natural infection drive immunity and redirect selective viral adaptation. Updated boosters are installed to cope with drifted viruses, yet data on adaptive evolution under increasing immune pressure in a real-world situation are lacking., Methods: Cross-sectional study to characterise SARS-CoV-2 mutational dynamics and selective adaptation over >1 year in relation to vaccine status, viral phylogenetics, and associated clinical and demographic variables., Findings: The study of >5400 SARS-CoV-2 infections between July 2021 and August 2022 in metropolitan New York portrayed the evolutionary transition from Delta to Omicron BA.1-BA.5 variants. Booster vaccinations were implemented during the Delta wave, yet booster breakthrough infections and SARS-CoV-2 re-infections were almost exclusive to Omicron. In adjusted logistic regression analyses, BA.1, BA.2, and BA.5 had a significant growth advantage over co-occurring lineages in the boosted population, unlike BA.2.12.1 or BA.4. Selection pressure by booster shots translated into diffuse adaptive evolution in Delta spike, contrasting with strong, receptor-binding motif-focused adaptive evolution in BA.2-BA.5 spike (Fisher Exact tests; non-synonymous/synonymous mutation rates per site). Convergent evolution has become common in Omicron, engaging spike positions crucial for immune escape, receptor binding, or cleavage., Interpretation: Booster shots are required to cope with gaps in immunity. Their discriminative immune pressure contributes to their effectiveness but also requires monitoring of selective viral adaptation processes. Omicron BA.2 and BA.5 had a selective advantage under booster vaccination pressure, contributing to the evolution of BA.2 and BA.5 sublineages and recombinant forms that predominate in 2023., Funding: The study was supported by NYU institutional funds and partly by the Cancer Center Support Grant P30CA016087 at the Laura and Isaac Perlmutter Cancer Center., Competing Interests: Declaration of interests Mark J. Mulligan reports potential competing interests: clinical trials and laboratory research contract funding for vaccines and monoclonal antibodies for SARS-CoV-2 with Lilly, Pfizer, and Sanofi; personal fees for Scientific Advisory Board service from Merck, Meissa Vaccines, Inc., and Pfizer. All other authors declare no conflicts of interest., (Copyright © 2023 The Authors. Published by Elsevier B.V. All rights reserved.)

Introduction: Available evidence is mixed concerning associations between smoking status and COVID-19 clinical outcomes. Effects of nicotine replacement therapy (NRT) and vaccination status on COVID-19 outcomes in smokers are unknown., Methods: Electronic health record data from 104 590 COVID-19 patients hospitalized February 1, 2020 to September 30, 2021 in 21 U.S. health systems were analyzed to assess associations of smoking status, in-hospital NRT prescription, and vaccination status with in-hospital death and ICU admission., Results: Current (n = 7764) and never smokers (n = 57 454) did not differ on outcomes after adjustment for age, sex, race, ethnicity, insurance, body mass index, and comorbidities. Former (vs never) smokers (n = 33 101) had higher adjusted odds of death (aOR, 1.11; 95% CI, 1.06-1.17) and ICU admission (aOR, 1.07; 95% CI, 1.04-1.11). Among current smokers, NRT prescription was associated with reduced mortality (aOR, 0.64; 95% CI, 0.50-0.82). Vaccination effects were significantly moderated by smoking status; vaccination was more strongly associated with reduced mortality among current (aOR, 0.29; 95% CI, 0.16-0.66) and former smokers (aOR, 0.47; 95% CI, 0.39-0.57) than for never smokers (aOR, 0.67; 95% CI, 0.57, 0.79). Vaccination was associated with reduced ICU admission more strongly among former (aOR, 0.74; 95% CI, 0.66-0.83) than never smokers (aOR, 0.87; 95% CI, 0.79-0.97)., Conclusions: Former but not current smokers hospitalized with COVID-19 are at higher risk for severe outcomes. SARS-CoV-2 vaccination is associated with better hospital outcomes in COVID-19 patients, especially current and former smokers. NRT during COVID-19 hospitalization may reduce mortality for current smokers., Implications: Prior findings regarding associations between smoking and severe COVID-19 disease outcomes have been inconsistent. This large cohort study suggests potential beneficial effects of nicotine replacement therapy on COVID-19 outcomes in current smokers and outsized benefits of SARS-CoV-2 vaccination in current and former smokers. Such findings may influence clinical practice and prevention efforts and motivate additional research that explores mechanisms for these effects., (© The Author(s) 2022. Published by Oxford University Press on behalf of the Society for Research on Nicotine and Tobacco.)

Competency-based medical education (CBME) is an outcomes-based approach to education and assessment that focuses on what competencies trainees need to learn in order to provide effective patient care. Despite this goal of providing quality patient care, trainees rarely receive measures of their clinical performance. This is problematic because defining a trainee's learning progression requires measuring their clinical performance. Traditional clinical performance measures (CPMs) are often met with skepticism from trainees given their poor individual-level attribution. Resident-sensitive quality measures (RSQMs) are attributable to individuals, but lack the expeditiousness needed to deliver timely feedback and can be difficult to automate at scale across programs. In this eye opener, the authors present a conceptual framework for a new type of measure - TRainee Attributable & Automatable Care Evaluations in Real-time (TRACERs) - attuned to both automation and trainee attribution as the next evolutionary step in linking education to patient care. TRACERs have five defining characteristics: meaningful (for patient care and trainees), attributable (sufficiently to the trainee of interest), automatable (minimal human input once fully implemented), scalable (across electronic health records [EHRs] and training environments), and real-time (amenable to formative educational feedback loops). Ideally, TRACERs optimize all five characteristics to the greatest degree possible. TRACERs are uniquely focused on measures of clinical performance that are captured in the EHR, whether routinely collected or generated using sophisticated analytics, and are intended to complement (not replace) other sources of assessment data. TRACERs have the potential to contribute to a national system of high-density, trainee-attributable, patient-centered outcome measures., Competing Interests: The authors have no competing interests to declare., (Copyright: © 2023 The Author(s).)

Background: The introduction of electronic workflows has allowed for the flow of raw uncontextualized clinical data into medical documentation. As a result, many electronic notes have become replete of "noise" and deplete clinically significant "signals." There is an urgent need to develop and implement innovative approaches in electronic clinical documentation that improve note quality and reduce unnecessary bloating., Objective: This study aims to describe the development and impact of a novel set of templates designed to change the flow of information in medical documentation., Methods: This is a multihospital nonrandomized prospective improvement study conducted on the inpatient general internal medicine service across 3 hospital campuses at the New York University Langone Health System. A group of physician leaders representing each campus met biweekly for 6 months. The output of these meetings included (1) a conceptualization of the note bloat problem as a dysfunction in information flow, (2) a set of guiding principles for organizational documentation improvement, (3) the design and build of novel electronic templates that reduced the flow of extraneous information into provider notes by providing link outs to best practice data visualizations, and (4) a documentation improvement curriculum for inpatient medicine providers. Prior to go-live, pragmatic usability testing was performed with the new progress note template, and the overall user experience was measured using the System Usability Scale (SUS). Primary outcome measures after go-live include template utilization rate and note length in characters., Results: In usability testing among 22 medicine providers, the new progress note template averaged a usability score of 90.6 out of 100 on the SUS. A total of 77% (17/22) of providers strongly agreed that the new template was easy to use, and 64% (14/22) strongly agreed that they would like to use the template frequently. In the 3 months after template implementation, general internal medicine providers wrote 67% (51,431/76,647) of all inpatient notes with the new templates. During this period, the organization saw a 46% (2768/6191), 47% (3505/7819), and 32% (3427/11,226) reduction in note length for general medicine progress notes, consults, and history and physical notes, respectively, when compared to a baseline measurement period prior to interventions., Conclusions: A bundled intervention that included the deployment of novel templates for inpatient general medicine providers significantly reduced average note length on the clinical service. Templates designed to reduce the flow of extraneous information into provider notes performed well during usability testing, and these templates were rapidly adopted across all hospital campuses. Further research is needed to assess the impact of novel templates on note quality, provider efficiency, and patient outcomes., (©Jonah Feldman, Adam Goodman, Katherine Hochman, Eesha Chakravartty, Jonathan Austrian, Eduardo Iturrate, Brian Bosworth, Archana Saxena, Marwa Moussa, Dina Chenouda, Frank Volpicelli, Nicole Adler, Joseph Weisstuch, Paul Testa. Originally published in JMIR Formative Research (https://formative.jmir.org), 12.04.2023.)

Background: Male sex, elevated troponin levels, and elevated D-dimer levels are associated with more complicated COVID-19 illness and greater mortality; however, while there are known sex differences in the prognostic value of troponin and D-dimer in other disease states, it is unknown whether they exist in the setting of COVID-19., Objective: We assessed whether sex modified the relationship between troponin, D-dimer, and severe COVID-19 illness (defined as mechanical ventilation, ICU admission or transfer, discharge to hospice, or death)., Methods: We conducted a retrospective cohort study of patients hospitalized with COVID-19 at a large, academic health system. We used multivariable regression to assess associations between sex, troponin, D-dimer, and severe COVID-19 illness, adjusting for demographic, clinical, and laboratory covariates. To test whether sex modified the relationship between severe COVID-19 illness and troponin or D-dimer, models with interaction terms were utilized., Results: Among 4,574 patients hospitalized with COVID-19, male sex was associated with higher levels of troponin and greater odds of severe COVID-19 illness, but lower levels of initial D-dimer when compared with female sex. While sex did not modify the relationship between troponin level and severe COVID-19 illness, peak D-dimer level was more strongly associated with severe COVID-19 illness in male patients compared to female patients (males: OR=2.91, 95%CI=2.63-2.34, p<0.001; females: OR=2.31, 95%CI=2.04-2.63, p<0.001; p-interaction=0.005)., Conclusion: Sex did not modify the association between troponin level and severe COVID-19 illness, but did modify the association between peak D-dimer and severe COVID-19 illness, suggesting greater prognostic value for D-dimer in males with COVID-19., (Copyright © 2022 Elsevier Inc. All rights reserved.)

Background: There is mixed evidence about the relations of current versus past cancer with severe COVID-19 outcomes and how they vary by patient and cancer characteristics., Methods: Electronic health record data of 104,590 adult hospitalized patients with COVID-19 were obtained from 21 United States health systems from February 2020 through September 2021. In-hospital mortality and ICU admission were predicted from current and past cancer diagnoses. Moderation by patient characteristics, vaccination status, cancer type, and year of the pandemic was examined., Results: 6.8% of the patients had current (n = 7,141) and 6.5% had past (n = 6,749) cancer diagnoses. Current cancer predicted both severe outcomes but past cancer did not; adjusted odds ratios (aOR) for mortality were 1.58 [95% confidence interval (CI), 1.46-1.70] and 1.04 (95% CI, 0.96-1.13), respectively. Mortality rates decreased over the pandemic but the incremental risk of current cancer persisted, with the increment being larger among younger vs. older patients. Prior COVID-19 vaccination reduced mortality generally and among those with current cancer (aOR, 0.69; 95% CI, 0.53-0.90)., Conclusions: Current cancer, especially among younger patients, posed a substantially increased risk for death and ICU admission among patients with COVID-19; prior COVID-19 vaccination mitigated the risk associated with current cancer. Past history of cancer was not associated with higher risks for severe COVID-19 outcomes for most cancer types., Impact: This study clarifies the characteristics that modify the risk associated with cancer on severe COVID-19 outcomes across the first 20 months of the COVID-19 pandemic. See related commentary by Egan et al., p. 3., (©2022 The Authors; Published by the American Association for Cancer Research.)

Background: Corticosteroids and tocilizumab have been shown to improve survival in patients who require supplemental oxygen from coronavirus disease 2019 (COVID-19) pneumonia. The optimal dose of immunosuppression for the treatment of COVID-19 acute respiratory distress syndrome (ARDS) is still unknown., Objective: The objective of this study was to evaluate the effectiveness and safety of high- versus low-dose corticosteroids with or without tocilizumab for the treatment of COVID-19 ARDS., Methods: This was a retrospective study of patients admitted to the intensive care unit (ICU) requiring mechanical ventilation who received high- versus low-dose corticosteroids with or without tocilizumab. The primary outcome was survival to discharge. Safety outcomes included infections and incidence of hyperglycemia., Results: In this cohort, 110 (54%) and 95 (46%) patients received high-dose (≥10 mg dexamethasone equivalent) and low-dose (<10 mg dexamethasone equivalent) corticosteroids for more than 3 consecutive days, respectively. Thirty-five patients (32%) in the high-dose group and 33 patients (35%) in the low-dose group survived to hospital discharge ( P = 0.85). There was no difference in 28-day mortality in patients who received high-dose corticosteroids without tocilizumab compared with those who received low-dose corticosteroids with tocilizumab (n = 38/82, 46% vs n = 19/40, 48% P = 0.99); however, there was a higher mortality if patients received low-dose corticosteroids without tocilizumab (n = 39/55, 71%, P = 0.01). The highest rate of a bacterial pneumonia was in patients who received high-dose corticosteroids with tocilizumab., Conclusions: In critically ill patients with COVID-19 ARDS requiring mechanical ventilation, we found no difference in high- versus low-dose corticosteroids with regard to survival to hospital discharge. However, patients receiving only low-dose corticosteroids without tocilizumab did worse than the other groups. Larger prospective studies are needed to determine the optimal immunosuppression dosing strategy in this patient population.

Purpose: Despite progress in the treatment of coronavirus disease 2019 (COVID-19), including the development of monoclonal antibodies (mAbs), more clinical data to support the use of mAbs in outpatients with COVID-19 is needed. This study is designed to determine the impact of bamlanivimab, bamlanivimab/etesevimab, or casirivimab/imdevimab on clinical outcomes within 30 days of COVID-19 diagnosis., Methods: A retrospective cohort study was conducted at a single academic medical center with 3 campuses in Manhattan, Brooklyn, and Long Island, NY. Patients 12 years of age or older who tested positive for COVID-19 or were treated with a COVID-19-specific therapy, including COVID-19 mAb therapies, at the study site between November 24, 2020, and May 15, 2021, were included. The primary outcomes included rates of emergency department (ED) visit, inpatient admission, intensive care unit (ICU) admission, or death within 30 days from the date of COVID-19 diagnosis., Results: A total of 1,344 mAb-treated patients were propensity matched to 1,344 patients with COVID-19 patients who were not treated with mAb therapy. Within 30 days of diagnosis, among the patients who received mAb therapy, 101 (7.5%) presented to the ED and 79 (5.9%) were admitted. Among the patients who did not receive mAb therapy, 165 (12.3%) presented to the ED and 156 (11.6%) were admitted (relative risk [RR], 0.61 [95% CI, 0.50-0.75] and 0.51 [95% CI, 0.40-0.64], respectively). Four mAb patients (0.3%) and 2.64 control patients (0.2%) were admitted to the ICU (RR, 01.51; 95% CI, 0.45-5.09). Six mAb-treated patients (0.4%) and 3.37 controls (0.3%) died and/or were admitted to hospice (RR, 1.61; 95% CI, 0.54-4.83). mAb therapy in ambulatory patients with COVID-19 decreases the risk of ED presentation and hospital admission within 30 days of diagnosis., (© American Society of Health-System Pharmacists 2022. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Main Objective: There is limited information on how patient outcomes have changed during the COVID-19 pandemic. This study characterizes changes in mortality, intubation, and ICU admission rates during the first 20 months of the pandemic., Study Design and Methods: University of Wisconsin researchers collected and harmonized electronic health record data from 1.1 million COVID-19 patients across 21 United States health systems from February 2020 through September 2021. The analysis comprised data from 104,590 adult hospitalized COVID-19 patients. Inclusion criteria for the analysis were: (1) age 18 years or older; (2) COVID-19 ICD-10 diagnosis during hospitalization and/or a positive COVID-19 PCR test in a 14-day window (+/- 7 days of hospital admission); and (3) health system contact prior to COVID-19 hospitalization. Outcomes assessed were: (1) mortality (primary), (2) endotracheal intubation, and (3) ICU admission., Results and Significance: The 104,590 hospitalized participants had a mean age of 61.7 years and were 50.4% female, 24% Black, and 56.8% White. Overall risk-standardized mortality (adjusted for age, sex, race, ethnicity, body mass index, insurance status and medical comorbidities) declined from 16% of hospitalized COVID-19 patients (95% CI: 16% to 17%) early in the pandemic (February-April 2020) to 9% (CI: 9% to 10%) later (July-September 2021). Among subpopulations, males (vs. females), those on Medicare (vs. those on commercial insurance), the severely obese (vs. normal weight), and those aged 60 and older (vs. younger individuals) had especially high mortality rates both early and late in the pandemic. ICU admission and intubation rates also declined across these 20 months., Conclusions: Mortality, intubation, and ICU admission rates improved markedly over the first 20 months of the pandemic among adult hospitalized COVID-19 patients although gains varied by subpopulation. These data provide important information on the course of COVID-19 and identify hospitalized patient groups at heightened risk for negative outcomes., Trial Registration: ClinicalTrials.gov Identifier: NCT04506528 (https://clinicaltrials.gov/ct2/show/NCT04506528)., Competing Interests: The authors have declared that no competing interests exist.

Background: In 2021, Delta became the predominant SARS-CoV-2 variant worldwide. While vaccines have effectively prevented COVID-19 hospitalization and death, vaccine breakthrough infections increasingly occurred. The precise role of clinical and genomic determinants in Delta infections is not known, and whether they contributed to increased rates of breakthrough infections compared to unvaccinated controls., Methods: We studied SARS-CoV-2 variant distribution, dynamics, and adaptive selection over time in relation to vaccine status, phylogenetic relatedness of viruses, full genome mutation profiles, and associated clinical and demographic parameters., Findings: We show a steep and near-complete replacement of circulating variants with Delta between May and August 2021 in metropolitan New York. We observed an increase of the Delta sublineage AY.25 (14% in vaccinated, 7% in unvaccinated), its spike mutation S112L, and AY.44 (8% in vaccinated, 2% in unvaccinated) with its nsp12 mutation F192V in breakthroughs. Delta infections were associated with younger age and lower hospitalization rates than Alpha. Delta breakthrough infections increased significantly with time since vaccination, and, after adjusting for confounders, they rose at similar rates as in unvaccinated individuals., Interpretation: We observed a modest adaptation of Delta genomes in breakthrough infections in New York, suggesting an improved genomic framework to support Delta's epidemic growth in times of waning vaccine protection despite limited impact on vaccine escape., Funding: The study was supported by NYU institutional funds. The NYULH Genome Technology Center is partially supported by the Cancer Center Support Grant P30CA016087 at the Laura and Isaac Perlmutter Cancer Center., Competing Interests: Declaration of interests The authors have no conflict of interest to declare., (Copyright © 2022 The Author(s). Published by Elsevier B.V. All rights reserved.)

Background: Telemedicine as a mode of health care work has grown dramatically during the COVID-19 pandemic; the impact of this transition on clinicians' after-hours electronic health record (EHR)-based clinical and administrative work is unclear., Objective: This study assesses the impact of the transition to telemedicine during the COVID-19 pandemic on physicians' EHR-based after-hours workload (ie, "work outside work") at a large academic medical center in New York City., Methods: We conducted an EHR-based retrospective cohort study of ambulatory care physicians providing telemedicine services before the pandemic, during the acute pandemic, and after the acute pandemic, relating EHR-based after-hours work to telemedicine intensity (ie, percentage of care provided via telemedicine) and clinical load (ie, patient load per provider)., Results: A total of 2129 physicians were included in this study. During the acute pandemic, the volume of care provided via telemedicine significantly increased for all physicians, whereas patient volume decreased. When normalized by clinical load (ie, average appointments per day by average clinical days per week), telemedicine intensity was positively associated with work outside work across time periods. This association was strongest after the acute pandemic., Conclusions: Taking physicians' clinical load into account, physicians who devoted a higher proportion of their clinical time to telemedicine throughout various stages of the pandemic engaged in higher levels of EHR-based after-hours work compared to those who used telemedicine less intensively. This suggests that telemedicine, as currently delivered, may be less efficient than in-person-based care and may increase the after-hours work burden of physicians., (©Katharine Lawrence, Oded Nov, Devin Mann, Soumik Mandal, Eduardo Iturrate, Batia Wiesenfeld. Originally published in JMIR Medical Informatics (https://medinform.jmir.org), 28.07.2022.)

Type I interferon (IFN) is critical in our defense against viral infections. Increased type I IFN pathway activation is a genetic risk factor for systemic lupus erythematosus (SLE), and a number of common risk alleles contribute to the high IFN trait. We hypothesized that these common gain-of-function IFN pathway alleles may be associated with protection from mortality in acute COVID-19. We studied patients admitted with acute COVID-19 (756 European-American and 398 African-American ancestry). Ancestral backgrounds were analyzed separately, and mortality after acute COVID-19 was the primary outcome. In European-American ancestry, we found that a haplotype of interferon regulatory factor 5 (IRF5) and alleles of protein kinase cGMP-dependent 1 (PRKG1) were associated with mortality from COVID-19. Interestingly, these were much stronger risk factors in younger patients (OR = 29.2 for PRKG1 in ages 45-54). Variants in the IRF7 and IRF8 genes were associated with mortality from COVID-19 in African-American subjects, and these genetic effects were more pronounced in older subjects. Combining genetic information with blood biomarker data such as C-reactive protein, troponin, and D-dimer resulted in significantly improved predictive capacity, and in both ancestral backgrounds the risk genotypes were most relevant in those with positive biomarkers (OR for death between 14 and 111 in high risk genetic/biomarker groups). This study confirms the critical role of the IFN pathway in defense against COVID-19 and viral infections, and supports the idea that some common SLE risk alleles exert protective effects in antiviral immunity., (Copyright © 2022. Published by Elsevier Inc.)

Background and Objective: With the coronavirus disease 2019 (COVID-19) pandemic, rates of in-hospital antimicrobial use increased due to perceived bacterial and fungal coinfections along with COVID-19. We describe the incidence of these coinfections and antimicrobial use in patients hospitalized with COVID-19 to help guide effective antimicrobial use in this population., Setting: This study was conducted in 3 tertiary-care referral university teaching hospitals in New York City., Methods: This multicenter retrospective observational cohort study involved all patients admitted with COVID-19 from January 1, 2020, to February 1, 2021. Variables of interest were extracted from a de-identified data set of all COVID-19 infections across the health system. Population statistics are presented as median with interquartile range (IQR) or proportions with 95% confidence intervals (CIs) as indicated., Results: Among 7,209 of patients admitted with COVID-19, 663 (9.2%) had a positive culture from the respiratory tract or blood sometime during their initial hospital admission. Positive respiratory cultures occurred found in 449 (6.2%) patients, and 20% were collected within 48 hours of admission. Blood culture positivity occurred in 334 patients (4.6%), with 33.5% identified within 48 hours of admission. A higher proportion of patients received antimicrobials in the first wave than in the later pandemic period (82.4% vs 52.0%). Antimicrobials were prescribed to 70.1% of inpatients, with a median of 6 antimicrobial days per patient. Infection-free survival decreased over the course of hospitalization., Conclusions: We detected a very low incidence of coinfection with COVID-19 at admission. A longer duration of hospitalization was associated with an increased risk of coinfection. Antimicrobial use far exceeded the true incidence and detection of coinfections in these patients., (© The Author(s) 2022.)

Background: The epidemiology of nosocomial bloodstream infections (NBSIs) in patients with coronavirus disease 2019 (COVID-19) is poorly understood, due in part to substantial disease heterogeneity resulting from multiple potential pathogens., Methods: We identified risk factors for NBSIs and examined the association between NBSIs and mortality in a retrospective cohort of patients hospitalized with COVID-19 in 2 New York City hospitals during the height of the pandemic. We adjusted for the potential effects of factors likely to confound that association, including age, race, illness severity upon admission, and underlying health status., Results: Between January 1 and October 1, 2020, 1403 patients had a positive blood culture, and 79 and 101 met the stringent criteria for NBSI among non-COVID-19 and COVID-19 patients, respectively. NBSIs occurred almost exclusively among patients who were severely ill with COVID-19 at hospital admission. NBSIs were associated with elevated mortality, even after adjusting for baseline differences in COVID-19 illness (55% cases vs 45% controls; P  = .13). Mortality was concentrated in patients with early-onset pneumonia caused by S. aureus and gram-negative bacteria. Less virulent Candida (49%) and Enterococcus (12%) species were the predominant cause of NBSI in the latter stages of hospitalization, after antibiotic treatment and COVID-19 treatments that attenuate immune response. Most Enterococcus and Candida infections did not have an identifiable source and were not associated with common risk factors for infection by these organisms., Conclusions: Pathogen species and mortality exhibited temporal differences. Early recognition of risk factors among COVID-19 patients could potentially decrease NBSI-associated mortality through early COVID-19 and antimicrobial treatment., (© The Author(s) 2022. Published by Oxford University Press on behalf of Infectious Diseases Society of America.)

Background: Guidelines recommend moderate to high-intensity statins and antithrombotic agents in patients with atherosclerotic cardiovascular disease (ASCVD). However, guideline-directed medical therapy (GDMT) remains suboptimal., Methods: In this quality initiative, best practice alerts (BPA) in the electronic health record (EHR) were utilized to alert providers to prescribe to GDMT upon hospital discharge in ASCVD patients. Rates of GDMT were compared for 5 months pre- and post-BPA implementation. Multivariable regression was used to identify predictors of GDMT., Results: In 5985 pre- and 5568 post-BPA patients, the average age was 69.1 ± 12.8 years and 58.5% were male. There was a 4.0% increase in statin use from 67.3% to 71.3% and a 3.1% increase in antithrombotic use from 75.3% to 78.4% in the post-BPA cohort., Conclusions: This simple EHR-based initiative was associated with a modest increase in ASCVD patients being discharged on GDMT. Leveraging clinical decision support tools provides an opportunity to influence provider behavior and improve care for ASCVD patients, and warrants further investigation.

Objective: The widespread deployment of electronic health records (EHRs) has introduced new sources of error and inefficiencies to the process of ordering medications in the hospital setting. Existing work identifies orders that require pharmacy intervention by comparing them to a patient's medical records. In this work, we develop a machine learning model for identifying medication orders requiring intervention using only provider behavior and other contextual features that may reflect these new sources of inefficiencies., Materials and Methods: Data on providers' actions in the EHR system and pharmacy orders were collected over a 2-week period in a major metropolitan hospital system. A classification model was then built to identify orders requiring pharmacist intervention. We tune the model to the context in which it would be deployed and evaluate global and local feature importance., Results: The resultant model had an area under the receiver-operator characteristic curve of 0.91 and an area under the precision-recall curve of 0.44., Conclusions: Providers' actions can serve as useful predictors in identifying medication orders that require pharmacy intervention. Careful model tuning for the clinical context in which the model is deployed can help to create an effective tool for improving health outcomes without using sensitive patient data., (© The Author(s) 2021. Published by Oxford University Press on behalf of the American Medical Informatics Association.)

Importance: Black and Hispanic populations have higher rates of coronavirus disease 2019 (COVID-19) hospitalization and mortality than White populations but lower in-hospital case-fatality rates. The extent to which neighborhood characteristics and comorbidity explain these disparities is unclear. Outcomes in Asian American populations have not been explored., Objective: To compare COVID-19 outcomes based on race and ethnicity and assess the association of any disparities with comorbidity and neighborhood characteristics., Design, Setting, and Participants: This retrospective cohort study was conducted within the New York University Langone Health system, which includes over 260 outpatient practices and 4 acute care hospitals. All patients within the system's integrated health record who were tested for severe acute respiratory syndrome coronavirus 2 between March 1, 2020, and April 8, 2020, were identified and followed up through May 13, 2020. Data were analyzed in June 2020. Among 11 547 patients tested, outcomes were compared by race and ethnicity and examined against differences by age, sex, body mass index, comorbidity, insurance type, and neighborhood socioeconomic status., Exposures: Race and ethnicity categorized using self-reported electronic health record data (ie, non-Hispanic White, non-Hispanic Black, Hispanic, Asian, and multiracial/other patients)., Main Outcomes and Measures: The likelihood of receiving a positive test, hospitalization, and critical illness (defined as a composite of care in the intensive care unit, use of mechanical ventilation, discharge to hospice, or death)., Results: Among 9722 patients (mean [SD] age, 50.7 [17.5] years; 58.8% women), 4843 (49.8%) were positive for COVID-19; 2623 (54.2%) of those were admitted for hospitalization (1047 [39.9%] White, 375 [14.3%] Black, 715 [27.3%] Hispanic, 180 [6.9%] Asian, 207 [7.9%] multiracial/other). In fully adjusted models, Black patients (odds ratio [OR], 1.3; 95% CI, 1.2-1.6) and Hispanic patients (OR, 1.5; 95% CI, 1.3-1.7) were more likely than White patients to test positive. Among those who tested positive, odds of hospitalization were similar among White, Hispanic, and Black patients, but higher among Asian (OR, 1.6, 95% CI, 1.1-2.3) and multiracial patients (OR, 1.4; 95% CI, 1.0-1.9) compared with White patients. Among those hospitalized, Black patients were less likely than White patients to have severe illness (OR, 0.6; 95% CI, 0.4-0.8) and to die or be discharged to hospice (hazard ratio, 0.7; 95% CI, 0.6-0.9)., Conclusions and Relevance: In this cohort study of patients in a large health system in New York City, Black and Hispanic patients were more likely, and Asian patients less likely, than White patients to test positive; once hospitalized, Black patients were less likely than White patients to have critical illness or die after adjustment for comorbidity and neighborhood characteristics. This supports the assertion that existing structural determinants pervasive in Black and Hispanic communities may explain the disproportionately higher out-of-hospital deaths due to COVID-19 infections in these populations.

Background: There is concern about the potential of an increased risk related to medications that act on the renin-angiotensin-aldosterone system in patients exposed to coronavirus disease 2019 (Covid-19), because the viral receptor is angiotensin-converting enzyme 2 (ACE2)., Methods: We assessed the relation between previous treatment with ACE inhibitors, angiotensin-receptor blockers, beta-blockers, calcium-channel blockers, or thiazide diuretics and the likelihood of a positive or negative result on Covid-19 testing as well as the likelihood of severe illness (defined as intensive care, mechanical ventilation, or death) among patients who tested positive. Using Bayesian methods, we compared outcomes in patients who had been treated with these medications and in untreated patients, overall and in those with hypertension, after propensity-score matching for receipt of each medication class. A difference of at least 10 percentage points was prespecified as a substantial difference., Results: Among 12,594 patients who were tested for Covid-19, a total of 5894 (46.8%) were positive; 1002 of these patients (17.0%) had severe illness. A history of hypertension was present in 4357 patients (34.6%), among whom 2573 (59.1%) had a positive test; 634 of these patients (24.6%) had severe illness. There was no association between any single medication class and an increased likelihood of a positive test. None of the medications examined was associated with a substantial increase in the risk of severe illness among patients who tested positive., Conclusions: We found no substantial increase in the likelihood of a positive test for Covid-19 or in the risk of severe Covid-19 among patients who tested positive in association with five common classes of antihypertensive medications., (Copyright © 2020 Massachusetts Medical Society.)

Background: Although clinical decision support (CDS) alerts are effective reminders of best practices, their effectiveness is blunted by clinicians who fail to respond to an overabundance of inappropriate alerts. An electronic health record (EHR)-integrated machine learning (ML) algorithm is a potentially powerful tool to increase the signal-to-noise ratio of CDS alerts and positively impact the clinician's interaction with these alerts in general., Objective: This study aimed to describe the development and implementation of an ML-based signal-to-noise optimization system (SmartCDS) to increase the signal of alerts by decreasing the volume of low-value herpes zoster (shingles) vaccination alerts., Methods: We built and deployed SmartCDS, which builds personalized user activity profiles to suppress shingles vaccination alerts unlikely to yield a clinician's interaction. We extracted all records of shingles alerts from January 2017 to March 2019 from our EHR system, including 327,737 encounters, 780 providers, and 144,438 patients., Results: During the 6 weeks of pilot deployment, the SmartCDS system suppressed an average of 43.67% (15,425/35,315) potential shingles alerts (appointments) and maintained stable counts of weekly shingles vaccination orders (326.3 with system active vs 331.3 in the control group; P=.38) and weekly user-alert interactions (1118.3 with system active vs 1166.3 in the control group; P=.20)., Conclusions: All key statistics remained stable while the system was turned on. Although the results are promising, the characteristics of the system can be subject to future data shifts, which require automated logging and monitoring. We demonstrated that an automated, ML-based method and data architecture to suppress alerts are feasible without detriment to overall order rates. This work is the first alert suppression ML-based model deployed in practice and serves as foundational work in encounter-level customization of alert display to maximize effectiveness., (©Ji Chen, Sara Chokshi, Roshini Hegde, Javier Gonzalez, Eduardo Iturrate, Yin Aphinyanaphongs, Devin Mann. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 29.04.2020.)

Purpose: To develop natural language processing (NLP) to identify incidental lung nodules (ILNs) in radiology reports for assessment of management recommendations., Methods and Materials: We searched the electronic health records for patients who underwent chest CT during 2014 and 2017, before and after implementation of a department-wide dictation macro of the Fleischner Society recommendations. We randomly selected 950 unstructured chest CT reports and reviewed manually for ILNs. An NLP tool was trained and validated against the manually reviewed set, for the task of automated detection of ILNs with exclusion of previously known or definitively benign nodules. For ILNs found in the training and validation sets, we assessed whether reported management recommendations agreed with Fleischner Society guidelines. The guideline concordance of management recommendations was compared between 2014 and 2017., Results: The NLP tool identified ILNs with sensitivity and specificity of 91.1% and 82.2%, respectively, in the validation set. Positive and negative predictive values were 59.7% and 97.0%. In reports of ILNs in the training and validation sets before versus after introduction of a Fleischner reporting macro, there was no difference in the proportion of reports with ILNs (108 of 500 [21.6%] versus 101 of 450 [22.4%]; P = .8), or in the proportion of reports with ILNs containing follow-up recommendations (75 of 108 [69.4%] versus 80 of 101 [79.2%]; P = .2]. Rates of recommendation guideline concordance were not significantly different before and after implementation of the standardized macro (52 of 75 [69.3%] versus 60 of 80 [75.0%]; P = .43)., Conclusion: NLP reliably automates identification of ILNs in unstructured reports, pertinent to quality improvement efforts for ILN management., (Copyright © 2019 American College of Radiology. Published by Elsevier Inc. All rights reserved.)

Introduction: Emergency department (ED) patient care often hinges on the result of a diagnostic test. Frequently there is a lag time between a test result becoming available for review and physician decision-making or disposition based on that result. We implemented a system that electronically alerts ED providers when test results are available for review via a smartphone- and smartwatch-push notification. We hypothesized this would reduce the time from result to clinical decision-making., Methods: We retrospectively assessed the impact of the implementation of a push notification system at three EDs on time-to-disposition or time-to-follow-up order in six clinical scenarios of interest: chest radiograph (CXR) to disposition, basic metabolic panel (BMP) to disposition, urinalysis (UA) to disposition, respiratory pathogen panel (RPP) to disposition, hemoglobin (Hb) to blood transfusion order, and abnormal D-dimer to computed tomography pulmonary angiography (CTPA) order. All ED patients during a one-year period of push-notification availability were included in the study. The primary outcome was median time in each scenario from result availability to either disposition order or defined follow-up order. The secondary outcome was the overall usage rate of the opt-in push notification system by providers., Results: During the study period there were 6115 push notifications from 4183 ED encounters (2.7% of all encounters). Of the six clinical scenarios examined in this study, five were associated with a decrease in median time from test result availability to patient disposition or follow-up order when push notifications were employed: CXR to disposition, 80 minutes (interquartile range [IQR] 32-162 minutes) vs 56 minutes (IQR 18-141 minutes), difference 24 minutes (p<0.01); BMP to disposition, 128 minutes (IQR 62-225 minutes) vs 116 minutes (IQR 33-226 minutes), difference 12 minutes (p<0.01); UA to disposition, 105 minutes (IQR 43-200 minutes) vs 55 minutes (IQR 16-144 minutes), difference 50 minutes (p<0.01); RPP to disposition, 80 minutes (IQR 28-181 minutes) vs 37 minutes (IQR 10-116 minutes), difference 43 minutes (p<0.01); and D-dimer to CTPA, 14 minutes (IQR 6-30 minutes) vs 6 minutes (IQR 2.5-17.5 minutes), difference 8 minutes (p<0.01). The sixth scenario, Hb to blood transfusion (difference 19 minutes, p=0.73), did not meet statistical significance., Conclusion: Implementation of a push notification system for test result availability in the ED was associated with a decrease in lag time between test result and physician decision-making in the examined clinical scenarios. Push notifications were used in only a minority of ED patient encounters., Competing Interests: Conflicts of Interest: By the WestJEM article submission agreement, all authors are required to disclose all affiliations, funding sources and financial or management relationships that could be perceived as potential sources of bias. No author has professional or financial relationships with any companies that are relevant to this study. There are no conflicts of interest or sources of funding to declare.

Background: Testing for venous thromboembolism (VTE) is associated with cost and risk to patients (e.g. radiation). To assess the appropriateness of imaging utilization at the provider level, it is important to know that provider's diagnostic yield (percentage of tests positive for the diagnostic entity of interest). However, determining diagnostic yield typically requires either time-consuming, manual review of radiology reports or the use of complex and/or proprietary natural language processing software., Objectives: The objectives of this study were twofold: 1) to develop and implement a simple, user-configurable, and open-source natural language processing tool to classify radiology reports with high accuracy and 2) to use the results of the tool to design a provider-specific VTE imaging dashboard, consisting of both utilization rate and diagnostic yield., Methods: Two physicians reviewed a training set of 400 lower extremity ultrasound (UTZ) and computed tomography pulmonary angiogram (CTPA) reports to understand the language used in VTE-positive and VTE-negative reports. The insights from this review informed the arguments to the five modifiable parameters of the NLP tool. A validation set of 2,000 studies was then independently classified by the reviewers and by the tool; the classifications were compared and the performance of the tool was calculated., Results: The tool was highly accurate in classifying the presence and absence of VTE for both the UTZ (sensitivity 95.7%; 95% CI 91.5-99.8, specificity 100%; 95% CI 100-100) and CTPA reports (sensitivity 97.1%; 95% CI 94.3-99.9, specificity 98.6%; 95% CI 97.8-99.4). The diagnostic yield was then calculated at the individual provider level and the imaging dashboard was created., Conclusions: We have created a novel NLP tool designed for users without a background in computer programming, which has been used to classify venous thromboembolism reports with a high degree of accuracy. The tool is open-source and available for download at http://iturrate.com/simpleNLP. Results obtained using this tool can be applied to enhance quality by presenting information about utilization and yield to providers via an imaging dashboard., (Copyright © 2017 Elsevier B.V. All rights reserved.)

Objective: To determine the clinical significance of tachycardia in the postoperative period., Patients and Methods: Individuals 18 years or older undergoing hip and knee arthroplasty were included in the study. Two data sets were collected from different time periods: development data set from January 1, 2011, through December 31, 2011, and validation data set from December 1, 2012, through September 1, 2014. We used the development data set to identify the optimal definition of tachycardia with the strongest association with the vascular composite outcome (pulmonary embolism and myocardial necrosis and infarction). The predictive value of this definition was assessed in the validation data set for each outcome of interest, pulmonary embolism, myocardial necrosis and infarction, and infection using multiple logistic regression to control for known risk factors., Results: In 1755 patients in the development data set, a maximum heart rate (HR) greater than 110 beats/min was found to be the best cutoff as a correlate of the composite vascular outcome. Of the 4621 patients who underwent arthroplasty in the validation data set, 40 (0.9%) had pulmonary embolism. The maximum HR greater than 110 beats/min had an odds ratio (OR) of 9.39 (95% CI, 4.67-18.87; sensitivity, 72.5%; specificity, 78.0%; positive predictive value, 2.8%; negative predictive value, 99.7%) for pulmonary embolism. Ninety-seven patients (2.1%) had myocardial necrosis (elevated troponin). The maximum HR greater than 110 beats/min had an OR of 4.71 (95% CI, 3.06-7.24; sensitivity, 47.4%; specificity, 78.1%; positive predictive value, 4.4%; negative predictive value, 98.6%) for this outcome. Thirteen (.3%) patients had myocardial infarction according to our predetermined definition, and the maximum HR greater than 110 beats/min had an OR of 1.72 (95% CI, 0.47-6.27)., Conclusion: Postoperative tachycardia within the first 4 days of surgery should not be dismissed as a postoperative variation in HR, but may precede clinically significant adverse outcomes., (Copyright © 2016 Mayo Foundation for Medical Education and Research. Published by Elsevier Inc. All rights reserved.)

Background: Computed tomography pulmonary angiography (CTA) is the gold standard for diagnosing pulmonary embolism (PE) but involves radiation and iodinated contrast exposure. Of orthopedic patients evaluated for PE, a minority have a positive CTA study. Herein, we evaluate end tidal carbon dioxide (ETCO2) as a method to identify patients at low risk for PE and may not require a CTA. We hypothesize that ETCO2 will be useful for predicting the absence of PE in postoperative orthopedic patients., Methods: In this prospective study, all patients older than 18 years who were admitted for orthopedic surgery and who had a CTA performed for PE were eligible. These patients underwent an ETCO2 measurement. Patients were determined to have PE if they had a positive PE-protocol CT., Results: Between May 2014 and April 2015, 121 patients met the inclusion criteria for the study. Of these patients, 84 had a negative CTA examination, 25 had a positive examination, and 12 had a nondiagnostic examination. We found a statistically significant difference (P = .03) when comparing the average ETCO2 values for the positive and negative CTA groups. An ETCO2 cutoff value of 43 mm Hg was 100% sensitive with a negative predictive value of 100% for absence of PE on CTA., Conclusion: This study demonstrates a significant difference in ETCO2 measurements between postoperative orthopedic patients with and without CTA-detected PE. A cutoff value of >43 mm Hg may be useful in excluding patients from undergoing CTA., (Copyright © 2016 Elsevier Inc. All rights reserved.)

Purpose: The purpose of this study is to decrease overutilization of laboratory testing by eliminating a feature of the electronic ordering system that allowed providers to order laboratory tests to occur daily without review., Methods: We collected rates of utilization of a group of commonly ordered laboratory tests (number of tests per patient per day) throughout the entire hospital from June 10, 2013 through June 10, 2015. Our intervention, which eliminated the ability to order daily recurring tests, was implemented on June 11, 2014. We compared pre- and postintervention rates in order to assess the impact and surveyed providers about their experience with the intervention., Results: We examined 1,296,742 laboratory tests performed on 92,799 unique patients over 434,059 patient days. Before the intervention, the target tests were ordered using this daily recurring mechanism 33% of the time. After the intervention we observed an 8.5% (P <.001) to 20.9% (P <.001) reduction in tests per patient per day. The reduction in rate for some of the target tests persisted during the study period, but not for the 2 most commonly ordered tests. We estimated an approximate reduction in hospital costs of $300,000 due to the intervention., Conclusion: A simple modification to the order entry system significantly and immediately altered provider practices throughout a large tertiary care academic center. This strategy is replicable by the many hospitals that use the same electronic health record system, and possibly, by users of other systems. Future areas of study include evaluating the additive effects of education and real-time decision support., (Copyright © 2016 Elsevier Inc. All rights reserved.)

Background: Late afternoon hospital discharges are thought to contribute to admission bottlenecks. We previously described an intervention that resulted in a statistically significant increase in the discharge before noon (DBN) rate on 2 inpatient medicine units., Objective: To evaluate (1) the effect of an increased DBN rate on the admission arrival time and the number of admissions per hour and (2) the sustainability of our DBN initiative., Design: Pre-/postintervention retrospective analysis., Setting: Two acute-care inpatient medicine units in a tertiary care, urban, academic medical center., Patients: For the admission arrival time and admissions per hour analysis, all inpatients admitted to the medical units from June 1, 2011 to June 31, 2013. For the sustainability analysis, all patients discharged from July 1, 2013 to December 31, 2014., Intervention: A multidisciplinary intervention to increase the DBN rate., Measurements: Date and time of arrival to all inpatient sites, and discharge date and time of all patients from 2 inpatient medicine units., Results: Concurrent with our increase in DBN rate, we found a statistically significant change in the median arrival time of emergency department (ED) admissions and transfers from 5 pm to 4 pm. High-frequency admission peaks were statistically significantly reduced for ED admissions. The statistically significant increase in DBN rate is sustained at 35%., Conclusions: Increasing the DBN rate correlates with admissions arriving earlier in the day and reductions in high-frequency peaks of ED admissions. Statistically significant improvements in DBN rates are sustainable., (© 2015 Society of Hospital Medicine.)