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Objectives: To assess whether the US News and World Report (USNWR) Urology specialty ranking methodology accurately captures and classifies complications following elective outpatient urology procedures., Methods: We conducted electronic health record chart review of n=80 elective, outpatient urology procedures with complications from 2019-2023 across four hospitals in our integrated US health system. We used the Solventum AM-PPC software and USNWR methodology to determine eligibility and measure complications. For each complication identified by the software, we assessed: 1.) Whether the procedure was performed by a urologist; 2.) Whether the adjudicator agreed with the complication type; and 3.) Whether the complication was a clinically-related sequelae of the index procedure. We reported Clavien-Dindo severity of each complication., Results: Our adjudication agreed on complication type in 62/80 (78%) complications, and 64/80 (80%) complications were clinically related to the index urology procedure. Combined, 57/80 (71%) complications were concordant on both complication type and clinical relatedness. However, 38/80 (48%) index procedures were conducted by interventional radiologists, not urologists. Furthermore, 11/80 (13.8%) complications were false positive urinary tract infections (UTIs)., Conclusions: The USNWR methodology for elective outpatient urology procedural complications showed reasonable clinical validity but detected several false positive UTIs. Further, USNWR should clarify the extent to which procedures performed by interventional radiologists belong in urology rankings., Competing Interests: Declaration of Competing Interest The authors 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 Elsevier Inc. All rights reserved.)

National performance metrics ultimately enhance patient decision-making and promote meaningful improvements in health care delivery, which makes having valid and reliable measures essential. This study examined US News and World Report metrics from 2019 to 2012 and used electronic health record data, combined with detailed chart review across 3 in-system hospitals, to assess the provision of care compared to the attribution of patients assigned to the ear, nose, and throat (ENT) mortality group. Of the initial 47 ENT-attributed deaths, 23 of those were verified, dimensioning the mortality rate from 1.7% to just 0.8%. These results underscore the necessity of rethinking measures and mortality attribution methodologies to be more accurate. Current methods use Medicare Severity Diagnosis Related Group billing coding to map the attribution. We suggest transitioning away from specialty ranking approaches and towards a procedure and condition "rating" approach to ensure that these ranking types capture data about the provision of care within a given encounter., (© 2024 American Academy of Otolaryngology–Head and Neck Surgery Foundation.)

Background: Perioperative blood transfusion is associated with adverse outcomes and higher costs after coronary artery bypass graft (CABG) surgery. We developed risk assessments for patients' probability of perioperative transfusion and the expected transfusion volume to improve clinical management and resource use., Methods: Among 1,266,545 consecutive (2008-2016) isolated CABG operations in The Society of Thoracic Surgeons Adult Cardiac Surgery Database, 657,821 (51.9%) received perioperative transfusions of red blood cells (RBC), fresh frozen plasma (FFP), cryoprecipitate, and/or platelets. We developed "full" models to predict perioperative transfusion of any blood product, and of RBC, FFP, or platelets. Using least absolute shrinkage and selection operator model selection, we built a rapid risk score based on 5 variables (age, body surface area, sex, preoperative hematocrit, and use of intra-aortic balloon pump)., Results: C statistics for the full model were 0.785, 0.815, 0.707, and 0.699 for any blood product, RBC, FFP, and platelets, respectively. C statistics for rapid risk assessments were 0.752, 0.785, 0.670, and 0.661 for any blood product, RBC, FFP, and platelets, respectively. The observed vs expected risk plots showed strong calibration for full models and risk assessment tools; absolute differences between observed and expected risks of transfusion were <10.8% in each percentile of expected risk. Risk assessment-predicted probabilities of transfusion were strongly and nonlinearly associated (P < .0001) with total units transfused., Conclusions: These robust and well-calibrated risk assessment tools for perioperative transfusion in CABG can inform surgeons regarding patients' risks and the number of RBC, FFP, and platelets units they can expect to need. This can aid in optimizing outcomes and increasing efficient use of blood products., Competing Interests: Disclosures The authors have no conflicts of interest to disclose., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

Background: The COVID-19 pandemic introduced unique challenges to healthcare systems, particularly in relation to patient safety and adverse events during hospitalization. There is limited understanding of COVID-19's association with some patient safety indicators (PSIs)., Objectives: This study aimed to investigate the impact of COVID-19 infection on the rate of PSI-3 events and its implications on quality metrics. We compared PSI-3 event rates between COVID-19-infected and uninfected patients and examined the clinical characteristics of COVID-19 patients experiencing PSI-3 events., Methods: This is a retrospective study at Mayo Clinic hospitals between January 2020 and February 2022, analyzing patients meeting PSI-3 denominator eligibility criteria. PSI-3 events were identified using AHRQ WinQI software. Patients were categorized based on COVID-19 status. Patient demographics, characteristics, and PSI-3 rates were compared. A case series analysis described clinical details of COVID-19 patients with PSI-3 events., Results: Of 126,781 encounters meeting PSI-3 criteria, 8674 (6.8%) had acute COVID-19 infection. COVID-19-infected patients were older, more likely to be male, non-white, and had private insurance. PSI-3 rates were significantly higher in COVID-19 patients (0.21% versus 0.06%, P < 0.0001), even after risk adjustment (adjusted risk ratio, 3.24, P < 0.0001). The case series of 17 COVID-19 patients with PSI-3 events showed distinctive clinical characteristics, including higher medical device-related pressure injuries, and greater predisposition for head, face, and neck region., Conclusions: Acute COVID-19 infection correlates with higher PSI-3 event rates. Current quality indicators may require adaptation to address the pandemic's complexities and impact on patient safety. Further research is needed to comprehensively understand the intricate relationship between COVID-19 and patient outcomes., Competing Interests: The authors disclose no conflict of interest., (Copyright © 2024 The Author(s). Published by Wolters Kluwer Health, Inc.)

This study investigated the accuracy of mortality attributions assigned by the US News and World Report (USNWR) to the diabetes and endocrinology specialty. We reviewed medical records of all consecutive Medicare fee-for-service inpatients at Mayo Clinic, Florida (Jacksonville, Florida) with a Medicare Severity Diagnosis Related Group included in the USNWR Diabetes & Endocrinology specialty cohort admitted from November 2018 to April 2022, with documented mortality in our institution's electronic health record within 30 days of the index admission. A clinician adjudicated the primary cause of death, categorizing it as diabetes or endocrine, cancer, failure to thrive, or other. Among 49 deceased patients, only 7 (14.3%) had diabetes or an endocrine-related cause of death. Cancer (49.0%) and failure to thrive (30.6%) were the leading causes. This substantial discrepancy (86% misattribution) suggests USNWR's methodology might not precisely reflect the quality of care, potentially misleading patients and impacting hospital rankings., Competing Interests: The authors report no competing interests., (© 2024 The Authors.)

Background: The Joint Commission uses nulliparous, term, singleton, vertex, cesarean delivery (NTSV-CD) rates to assess hospitals' perinatal care quality through the Cesarean Birth measurement (PC-02). However, these rates are not risk-adjusted for maternal health factors, putting this measure at odds with the risk adjustment paradigm of most publicly reported hospital quality measures. Here, the authors tested whether risk adjustment for readily documented maternal risk factors affected hospital-level NTSV-CD rates in a large health system., Methods: Included were all consecutive NTSV pregnancies from January 2019 to April 2023 across 10 hospitals in one health system. Logistic regression, adjusting for age, obesity, diabetes, and hypertensive disorders. was used to calculate hospital-level risk-adjusted NTSV-CD rates by multiplying observed vs. expected ratios for each hospital by the systemwide unadjusted NTSV-CD rate. The authors calculated intrahospital risk differences between unadjusted and risk-adjusted rates and calculated the percentage of hospitals qualifying for different reporting status after risk adjustment using the 30% Joint Commission reporting threshold rate., Results: Of 23,866 pregnancies, 6,550 (27.4%) had cesarean deliveries. Across 10 hospitals, the number of deliveries ranged from 393 to 7,671, with unadjusted NTSV-CD rates ranging from 21.0% to 30.5%. Risk-adjusted NTSV-CD rates ranged from 21.5% to 30.4%, with absolute intrahospital differences in risk-adjusted vs. unadjusted rates ranging from -1.33% (indicating lower rate after risk adjustment) to 3.37% (indicating higher rate after risk adjustment). Three of 10 (30.0%) hospitals qualified for different reporting statuses after risk adjustment., Conclusion: Risk adjustment for age, obesity, diabetes, and hypertensive disorders is feasible and resulted in meaningful changes in hospital-level NTSV-CD rates with potentially impactful consequences for hospitals near The Joint Commission reporting threshold., (Copyright © 2024 The Joint Commission. Published by Elsevier Inc. All rights reserved.)

Purpose: By assessing longitudinal associations between COVID-19 census burdens and hospital characteristics, such as bed size and critical access status, we can explore whether pandemic-era hospital quality benchmarking requires risk-adjustment or stratification for hospital-level characteristics., Methods: We used hospital-level data from the US Department of Health and Human Services including weekly total hospital and COVID-19 censuses from August 2020 to August 2023 and the 2021 American Hospital Association survey. We calculated weekly percentages of total adult hospital beds containing COVID-19 patients. We then calculated the number of weeks each hospital spent at Extreme (≥20% of beds occupied by COVID-19 patients), High (10%-19%), Moderate (5%-9%), and Low (<5%) COVID-19 stress. We assessed longitudinal hospital-level COVID-19 stress, stratified by 15 hospital characteristics including joint commission accreditation, bed size, teaching status, critical access hospital status, and core-based statistical area (CBSA) rurality., Findings: Among n = 2582 US hospitals, the median(IQR) weekly percentage of hospital capacity occupied by COVID-19 patients was 6.7%(3.6%-13.0%). 80,268/213,383 (38%) hospital-weeks experienced Low COVID-19 census stress, 28% Moderate stress, 22% High stress, and 12% Extreme stress. COVID-19 census burdens were similar across most hospital characteristics, but were significantly greater for critical access hospitals., Conclusions: US hospitals experienced similar COVID-19 census burdens across multiple institutional characteristics. Evidence-based inclusion of pandemic-era outcomes in hospital quality reporting may not require significant hospital-level risk-adjustment or stratification, with the exception of rural or critical access hospitals, which experienced differentially greater COVID-19 census burdens and may merit hospital-level risk-adjustment considerations., (© 2024 National Rural Health Association.)

▪ ▪ ▪., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Objectives: In the USA and UK, pandemic-era outcome data have been excluded from hospital rankings and pay-for-performance programmes. We assessed the relationship between US hospitals' pre-pandemic Centers for Medicare and Medicaid Services (CMS) Overall Hospital Star ratings and early pandemic 30-day mortality among both patients with COVID and non-COVID to understand whether pre-existing structures, processes and outcomes related to quality enabled greater pandemic resiliency., Design and Data Source: A retrospective, claim-based data study using the 100% Inpatient Standard Analytic File and Medicare Beneficiary Summary File including all US Medicare Fee-for-Service inpatient encounters from 1 April 2020 to 30 November 2020 linked with the CMS Hospital Star Ratings using six-digit CMS provider IDs., Outcome Measure: The outcome was risk-adjusted 30-day mortality. We used multivariate logistic regression adjusting for age, sex, Elixhauser mortality index, US Census Region, month, hospital-specific January 2020 CMS Star rating (1-5 stars), COVID diagnosis (U07.1) and COVID diagnosis×CMS Star Rating interaction., Results: We included 4 473 390 Medicare encounters from 2533 hospitals, with 92 896 (28.2%) mortalities among COVID-19 encounters and 387 029 (9.3%) mortalities among non-COVID encounters. There was significantly greater odds of mortality as CMS Star Ratings decreased, with 18% (95% CI 15% to 22%; p<0.0001), 33% (95% CI 30% to 37%; p<0.0001), 38% (95% CI 34% to 42%; p<0.0001) and 60% (95% CI 55% to 66%; p<0.0001), greater odds of COVID mortality comparing 4-star, 3-star, 2-star and 1-star hospitals (respectively) to 5-star hospitals. Among non-COVID encounters, there were 17% (95% CI 16% to 19%; p<0.0001), 24% (95% CI 23% to 26%; p<0.0001), 32% (95% CI 30% to 33%; p<0.0001) and 40% (95% CI 38% to 42%; p<0.0001) greater odds of mortality at 4-star, 3-star, 2-star and 1-star hospitals (respectively) as compared with 5-star hospitals., Conclusion: Our results support a need to further understand how quality outcomes were maintained during the pandemic. Valuable insights can be gained by including the reporting of risk-adjusted pandemic era hospital quality outcomes for high and low performing hospitals., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Competing Interests: Conflicts of interest Drs Fox, Rosenbach, and Mangold are members of the Society of Dermatology Hospitalists. The Society of Dermatology Hospitalists was not involved in the design of the study, data collection, analysis, or drafting of the manuscript. Author Puri, Dr Pollock, Authors Yousif and Bhullar, and Drs Boudreaux and Pittelkow have no conflicts of interest to declare.

Objective: To test the hypothesis that the Monoclonal Antibody Screening Score performs consistently better in identifying the need for monoclonal antibody infusion throughout each "wave" of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variant predominance during the coronavirus disease 2019 (COVID-19) pandemic and that the infusion of contemporary monoclonal antibody treatments is associated with a lower risk of hospitalization., Patients and Methods: In this retrospective cohort study, we evaluated the efficacy of monoclonal antibody treatment compared with that of no monoclonal antibody treatment in symptomatic adults who tested positive for SARS-CoV-2 regardless of their risk factors for disease progression or vaccination status during different periods of SARS-CoV-2 variant predominance. The primary outcome was hospitalization within 28 days after COVID-19 diagnosis. The study was conducted on patients with a diagnosis of COVID-19 from November 19, 2020, through May 12, 2022., Results: Of the included 118,936 eligible patients, hospitalization within 28 days of COVID-19 diagnosis occurred in 2.52% (456/18,090) of patients who received monoclonal antibody treatment and 6.98% (7,037/100,846) of patients who did not. Treatment with monoclonal antibody therapies was associated with a lower risk of hospitalization when using stratified data analytics, propensity scoring, and regression and machine learning models with and without adjustments for putative confounding variables, such as advanced age and coexisting medical conditions (eg, relative risk, 0.15; 95% CI, 0.14-0.17)., Conclusion: Among patients with mild to moderate COVID-19, including those who have been vaccinated, monoclonal antibody treatment was associated with a lower risk of hospital admission during each wave of the COVID-19 pandemic., Competing Interests: Dr O’Horo received grants from nference, Inc, and the MITRE Corporation and consulting fees from Bates College, all of which was outside the present work. Dr Razonable received grants from Roche, Regeneron, and Gilead; received honoraria from Integritas and Medscape; is on the Data Safety Monitoring Board or Advisory Board for Novartis; and has a leadership role in the American Society of Transplantation., (© 2023 The Authors.)

Objectives: Highly visible hospital quality reporting stakeholders in the USA such as the US News & World Report (USNWR) and the Centers for Medicare & Medicaid Services (CMS) play an important health systems role via their transparent public reporting of hospital outcomes and performance. However, during the pandemic, many such quality measurement stakeholders and pay-for-performance programmes in the USA and Europe have eschewed the traditional risk adjustment paradigm, instead choosing to pre-emptively exclude months or years of pandemic era performance data due largely to hospitals' perceived COVID-19 burdens. These data exclusions may lead patients to draw misleading conclusions about where to seek care, while also masking genuine improvements or deteriorations in hospital quality that may have occurred during the pandemic. Here, we assessed to what extent hospitals' COVID-19 burdens (proportion of hospitalised patients with COVID-19) were associated with their non-COVID 30-day mortality rates from March through November 2020 to inform whether inclusion of pandemic-era data may still be appropriate., Design: This was a retrospective cohort study using the 100% CMS Inpatient Standard Analytic File and Master Beneficiary Summary File to include all US Medicare inpatient encounters with admission dates from 1 April 2020 through 30 November 2020, excluding COVID-19 encounters. Using linear regression, we modelled the association between hospitals' COVID-19 proportions and observed/expected (O/E) ratios, testing whether the relationship was non-linear. We calculated alternative hospital O/E ratios after selective pandemic data exclusions mirroring the USNWR data exclusion methodology., Setting and Participants: We analysed 4 182 226 consecutive Medicare inpatient encounters from across 2601 US hospitals., Results: The association between hospital COVID-19 proportion and non-COVID O/E 30-day mortality was statistically significant (p<0.0001), but weakly correlated (r 2 =0.06). The median (IQR) pairwise relative difference in hospital O/E ratios comparing the alternative analysis with the original analysis was +3.7% (-2.5%, +6.7%), with 1908/2571 (74.2%) of hospitals having relative differences within ±10%., Conclusions: For non-COVID patient outcomes such as mortality, evidence-based inclusion of pandemic-era data is methodologically plausible and must be explored rather than exclusion of months or years of relevant patient outcomes data., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Background: As diagnostic tests for COVID-19 were broadly deployed under Emergency Use Authorization, there emerged a need to understand the real-world utilization and performance of serological testing across the United States., Methods: Six health systems contributed electronic health records and/or claims data, jointly developed a master protocol, and used it to execute the analysis in parallel. We used descriptive statistics to examine demographic, clinical, and geographic characteristics of serology testing among patients with RNA positive for SARS-CoV-2., Results: Across datasets, we observed 930,669 individuals with positive RNA for SARS-CoV-2. Of these, 35,806 (4%) were serotested within 90 days; 15% of which occurred <14 days from the RNA positive test. The proportion of people with a history of cardiovascular disease, obesity, chronic lung, or kidney disease; or presenting with shortness of breath or pneumonia appeared higher among those serotested compared to those who were not. Even in a population of people with active infection, race/ethnicity data were largely missing (>30%) in some datasets-limiting our ability to examine differences in serological testing by race. In datasets where race/ethnicity information was available, we observed a greater distribution of White individuals among those serotested; however, the time between RNA and serology tests appeared shorter in Black compared to White individuals. Test manufacturer data was available in half of the datasets contributing to the analysis., Conclusion: Our results inform the underlying context of serotesting during the first year of the COVID-19 pandemic and differences observed between claims and EHR data sources-a critical first step to understanding the real-world accuracy of serological tests. Incomplete reporting of race/ethnicity data and a limited ability to link test manufacturer data, lab results, and clinical data challenge the ability to assess the real-world performance of SARS-CoV-2 tests in different contexts and the overall U.S. response to current and future disease pandemics., Competing Interests: I have read the journal’s policy and the authors of this manuscript have the following competing interests: Natalie E Sheils is an employee of Optum Labs and owns stock in the parent company UnitedHealth group. Anthony M Louder is a paid employee of Aetion and hold Aetion stock options. Nancy D. Lin was an employee of Health Catalyst at the time the work was performed. Jennifer Gatz is a full-time employee of Regenstrief Institute, which provides independent research services to entities including those within the pharmaceutical and medical device industries. Shaun J. Grannis serves as Chief Medical Information Officer for the Indiana Health Information Exchange, and is a founding partner of Uppstroms, LLC. Carly Kabelac is a paid employee of Aetion and hold Aetion stock options. Carrie L. Byington has intellectual property in and receives royalties from BioFire, Inc. She serves as a scientific advisor to IDbyDNA (San Francisco, CA and Salt Lake City, UT). Dr. Byington is on the Board of the Commonwealth Fund. Atul J. Butte is a co-founder and consultant to Personalis and NuMedii; consultant to Samsung, Mango Tree Corporation, and in the recent past, 10x Genomics, Helix, Pathway Genomics, and Verinata (Illumina); has served on paid advisory panels or boards for Geisinger Health, Regenstrief Institute, Gerson Lehman Group, AlphaSights, Covance, Novartis, Genentech, Merck, and Roche; is a shareholder in Personalis and NuMedii; is a minor shareholder in Apple, Facebook, Alphabet (Google), Microsoft, Amazon, Snap, Snowflake, 10x Genomics, Illumina, Nuna Health, Assay Depot (Scientist.com), Vet24seven, Regeneron, Sanofi, Royalty Pharma, Pfizer, BioNTech, AstraZeneca, Moderna, Biogen, Twist Bioscience, Pacific Biosciences, Editas Medicine, Invitae, Doximity, and Sutro, and several other non-health related companies and mutual funds; and has received honoraria and travel reimbursement for invited talks from Johnson and Johnson, Roche, Genentech, Pfizer, Merck, Lilly, Takeda, Varian, Mars, Siemens, Optum, Abbott, Celgene, AstraZeneca, AbbVie, Westat, several investment and venture capital firms, and many academic institutions, medical or disease specific foundations and associations, and health systems. Atul Butte receives royalty payments through Stanford University, for several patents and other disclosures licensed to NuMedii and Personalis. Carla Rodriguez-Watson receives research support from Merck, Novartis, Pfizer, Lilly, Janssen, and AbbVie. She holds minor stock in Gilead., (Copyright: This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.)

Background: Real-world performance of COVID-19 diagnostic tests under Emergency Use Authorization (EUA) must be assessed. We describe overall trends in the performance of serology tests in the context of real-world implementation., Methods: Six health systems estimated the odds of seropositivity and positive percent agreement (PPA) of serology test among people with confirmed SARS-CoV-2 infection by molecular test. In each dataset, we present the odds ratio and PPA, overall and by key clinical, demographic, and practice parameters., Results: A total of 15,615 people were observed to have at least one serology test 14-90 days after a positive molecular test for SARS-CoV-2. We observed higher PPA in Hispanic (PPA range: 79-96%) compared to non-Hispanic (60-89%) patients; in those presenting with at least one COVID-19 related symptom (69-93%) as compared to no such symptoms (63-91%); and in inpatient (70-97%) and emergency department (93-99%) compared to outpatient (63-92%) settings across datasets. PPA was highest in those with diabetes (75-94%) and kidney disease (83-95%); and lowest in those with auto-immune conditions or who are immunocompromised (56-93%). The odds ratios (OR) for seropositivity were higher in Hispanics compared to non-Hispanics (OR range: 2.59-3.86), patients with diabetes (1.49-1.56), and obesity (1.63-2.23); and lower in those with immunocompromised or autoimmune conditions (0.25-0.70), as compared to those without those comorbidities. In a subset of three datasets with robust information on serology test name, seven tests were used, two of which were used in multiple settings and met the EUA requirement of PPA ≥87%. Tests performed similarly across datasets., Conclusion: Although the EUA requirement was not consistently met, more investigation is needed to understand how serology and molecular tests are used, including indication and protocol fidelity. Improved data interoperability of test and clinical/demographic data are needed to enable rapid assessment of the real-world performance of in vitro diagnostic tests., Competing Interests: AJB is a co-founder and consultant to Personalis and NuMedii; consultant to Samsung, Mango Tree Corporation, and in the recent past, 10x Genomics, Helix, Pathway Genomics, and Verinata (Illumina); has served on paid advisory panels or boards for Geisinger Health, Regenstrief Institute, Gerson Lehman Group, AlphaSights, Covance, Novartis, Genentech, Merck, and Roche; is a shareholder in Personalis and NuMedii; is a minor shareholder in Apple, Facebook, Alphabet (Google), Microsoft, Amazon, Snap, Snowflake, 10x Genomics, Illumina, Nuna Health, Assay Depot (Scientist.com), Vet24seven, Regeneron, Sanofi, Royalty Pharma, Pfizer, BioNTech, AstraZeneca, Moderna, Biogen, Twist Bioscience, Pacific Biosciences, Editas Medicine, Invitae, Doximity, and Sutro, and several other non-health related companies and mutual funds; and has received honoraria and travel reimbursement for invited talks from Johnson and Johnson, Roche, Genentech, Pfizer, Merck, Lilly, Takeda, Varian, Mars, Siemens, Optum, Abbott, Celgene, AstraZeneca, AbbVie, Westat, several investment and venture capital firms, and many academic institutions, medical or disease specific foundations and associations, and health systems. AJB receives royalty payments through Stanford University, for several patents and other disclosures licensed to NuMedii and Personalis. AJB’s research has been funded by NIH, Northrup Grumman (as the prime on an NIH contract), Genentech, Johnson and Johnson, FDA, Robert Wood Johnson Foundation, Leon Lowenstein Foundation, Intervalien Foundation, Priscilla Chan and Mark Zuckerberg, the Barbara and Gerson Bakar Foundation, and in the recent past, the March of Dimes, Juvenile Diabetes Research Foundation, California Governor’s Office of Planning and Research, California Institute for Regenerative Medicine, L’Oreal, and Progenity. CLB has intellectual property in and receives royalties from BioFire, Inc. She serves as a scientific advisor to IDbyDNA (San Francisco, CA and Salt Lake City, UT); and is on the Board of the Commonwealth Fund. CK is a paid employee of Aetion and hold Aetion stock options. NES is an employee of Optum Labs and owns stock in the parent company UnitedHealth group. NDL was an employee of Health Catalyst at the time the work was performed. JLG is a full-time employee of Regenstrief Institute, which provides independent research services to entities including those within the pharmaceutical and medical device industries. SJG serves as Chief Medical Information Officer for the Indiana Health Information Exchange, and is a founding partner of Uppstroms, LLC. This does not alter our adherence to PLOS ONE policies on sharing data and materials., (Copyright: © 2023 Watson et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

To date, there has been a notable lack of peer-reviewed or publicly available data documenting rates of hospital quality outcomes and patient safety events during the coronavirus disease 2019 pandemic era. The dearth of evidence is perhaps related to the US health care system triaging resources toward patient care and away from reporting and research and also reflects that data used in publicly reported hospital quality rankings and ratings typically lag 2-5 years. At our institution, a learning health system assessment is underway to evaluate how patient safety was affected by the pandemic. Here we share and discuss early findings, noting the limitations of self-reported safety event reporting, and suggest the need for further widespread investigations at other US hospitals. During the 2-year study period from January 1, 2020, through December 31, 2021 across 3 large US academic medical centers at our institution, we documented an overall rate of 25.8 safety events per 1000 inpatient days. The rate of events meeting "harm" criteria was 12.4 per 1000 inpatient days, the rate of nonharm events was 11.1 per 1000 inpatient days, and the fall rate was 2.3 per 1000 inpatient days. This descriptive exploratory analysis suggests that patient safety event rates at our institution did not increase over the course of the pandemic. However, increasing health care worker absences were nonlinearly and strongly associated with patient safety event rates, which raises questions regarding the mechanisms by which patient safety event rates may be affected by staff absences during pandemic peaks., (© 2022 The Authors.)

Objective: To develop a simple, interpretable value metric (VM) to assess the value of care of hospitals for specific procedures or conditions by operationalizing the value equation: Value = Quality/Cost., Patients and Methods: The present study was conducted on a retrospective cohort from 2015 to 2018 drawn from the 100% US sample of Medicare inpatient claims. The final cohort comprised 637,341 consecutive inpatient encounters with a cancer-related Medicare Severity-Diagnosis Related Grouping and 13,307 consecutive inpatient encounters with the International Classification of Diseases, Ninth Revision or International Classification of Diseases, Tenth Revision procedure code for partial or total gastrectomy. Claims-based demographic and clinical variables were used for risk adjustment, including age, sex, year, dual eligibility, reason for Medicare entitlement, and binary indicators for each of the Elixhauser comorbidities used in the Elixhauser mortality index. Risk-adjusted 30-day mortality and risk-adjusted encounter-specific costs were combined to form the VM, which was calculated as follows: number needed to treat = 1/(Mortality national  - Mortality hospital ), and VM = number needed to treat × risk-adjusted cost per encounter., Results: Among hospitals with better-than-average 30-day cancer mortality rates, the cost to prevent 1 excess 30-day mortality for an inpatient cancer encounter ranged from $71,000 (best value) to $1.4 billion (worst value), with a median value of $543,000. Among hospitals with better-than-average 30-day gastrectomy mortality rates, the cost to prevent 1 excess 30-day mortality for an inpatient gastrectomy encounter ranged from $710,000 (best value) to $95 million (worst value), with a median value of $1.8 million., Conclusion: This simple VM may have utility for interpretable reporting of hospitals' value of care for specific conditions or procedures. We found substantial inter- and intrahospital variation in value when defined as the costs of preventing 1 excess cancer or gastrectomy mortality compared with the national average, implying that hospitals with similar quality of care may differ widely in the value of that care., (© 2022 The Authors.)

The availability of large state and federally run administrative health-care databases provides potentially comprehensive population-wide information that can dramatically impact both medical and health-policy decision-making. Specific opportunities and important limitations exist with all administrative databases based on what information is collected and how reliably specific data elements are reported. Access to patient identifiable-level information can be critical for certain long-term outcome studies but can be difficult (although not impossible) due to patient privacy protections, while more easily available de-identified information can provide important insights that may be more than sufficient for some short-term operative or in-hospital outcome questions. The first section of this paper by Sarah K. Meier and Benjamin D. Pollock discusses Medicare and the different data files available to health-care researchers. They describe what is and is not generally available from even the most granular Medicare Standard Analytic Files, and provide an analysis of the strengths and weaknesses of Medicare administrative data as well as the resulting best and inappropriate uses of these data. In the second section, the Nationwide Inpatient Sample and complementary State Inpatient Database programs are reviewed by Steven M. Kurtz and Edmund Lau, with insights into the origins of these programs, the data elements that are recorded relating to the operative procedure and hospital stay, and examples of the types of studies that optimally utilize these data sources. They also detail the limitations of these databases and identify studies that they are not well-suited for, especially those involving linkage or longitudinal studies over time. Both sections provide useful guidance on the best uses and pitfalls related to these important large representative national administrative data sources., Competing Interests: Disclosure: This work was funded by a grant from the National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS) (P30AR76312) and the American Joint Replacement Research-Collaborative (AJRR-C) https://ajrrc.org/. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. The Disclosure of Potential Conflicts of Interest forms are provided with the online version of the article (http://links.lww.com/JBJS/H174)., (Copyright © 2022 by The Journal of Bone and Joint Surgery, Incorporated.)

We followed 106 349 primary care patients for 22 385 3099 person-days across 21 calendar months and documented 69 breakthrough coronavirus disease 2019 (COVID-19) hospitalizations: 65/102,613 (0.06%) among those fully vaccinated, 3/11 047 (0.03%) among those previously infected, and 1/7,313 (0.01%) among those with both statuses. These data give providers real-world context regarding breakthrough COVID-19 hospitalization risk., Competing Interests: Potential conflicts of interest. A. J. T. reports receiving payment from UpToDate for writing a treatment section on osteomyelitis and reports playing an unpaid role as a board member for the Musculoskeletal Infection Society. All other authors report no potential 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) 2022. Published by Oxford University Press for the Infectious Diseases Society of America. All rights reserved. For permissions, e-mail: journals.permissions@oup.com.)

US hospital quality rankings and ratings use disparate methodologies and are weakly correlated. This causes confusion for patients and hospital quality staff. At the authors' institution, a Composite Hospital Quality Index (CHQI) was developed to combine hospital quality ratings. This approach is described and a calculator is shared here for other health systems to explore their performance. Among the US News and World Report Top 50 Hospitals, hospital-specific numeric summary scores were aggregated from the 2021 Centers for Medicare and Medicaid Services (CMS) Hospital Overall Star Rating, the Spring 2021 Leapfrog Safety Grade, and the April 2021 Hospital Consumer Assessment of Healthcare Providers and Systems Star Rating. The CHQI is the hospital-specific sum of the national percentile-rankings across these 3 ratings. In this example, mean (SD) percentiles were as follows: CMS Stars 74 (19), Hospital Consumer Assessment of Healthcare Providers and Systems 63 (19), Leapfrog 65 (24), with mean (SD) CHQI of 202 (49). The CHQI is used at the authors' institution to identify improvement opportunities and ensure that high-quality care is delivered across the health system., (Copyright © 2022 the American College of Medical Quality.)

We characterized coronavirus disease 2019 (COVID-19) breakthrough cases admitted to a single center in Florida. With the emergence of delta variant, an increased number of hospitalizations was seen due to breakthrough infections. These patients were older and more likely to have comorbidities. Preventive measures should be maintained even after vaccination., (© The Author(s) 2021. Published by Oxford University Press for the Infectious Diseases Society of America. All rights reserved. For permissions, e-mail: journals.permissions@oup.com.)

Background: While COVID-19 immunization programs attempted to reach targeted rates, cases rose significantly since the emergence of the delta variant. This retrospective cohort study describes the correlation between antispike antibodies and outcomes of hospitalized, breakthrough cases during the delta variant surge., Methods: All patients with positive SARS-CoV-2 polymerase chain reaction hospitalized at Mayo Clinic Florida from 19 June 2021 to 11 November 2021 were considered for analysis. Cases were analyzed by vaccination status. Breakthrough cases were then analyzed by low and high antibody titers against SARS-CoV-2 spike protein, with a cut-off value of ≥132 U/ml. Outcomes included hospital length of stay (LOS), need for intensive care unit (ICU), mechanical ventilation, and mortality. We used 1:1 nearest neighbor propensity score matching without replacement to assess for confounders., Results: Among 627 hospitalized patients with COVID-19, vaccine breakthrough cases were older with more comorbidities compared to unvaccinated. After propensity score matching, the unvaccinated patients had higher mortality (27 [28.4%] vs. 12 [12.6%], p = 0.002) and LOS (7 [1.0-57.0] vs. 5 [1.0-31.0] days, p = 0.011). In breakthrough cases, low-titer patients were more likely to be solid organ transplant recipients (16 [34.0%] vs. 9 [12.3%], p = 0.006), with higher need for ICU care (24 [51.1%] vs. 22 [11.0%], p = 0.034), longer hospital LOS (median 6 vs. 5 days, p = 0.013), and higher mortality (10 [21.3%] vs. 5 [6.8%], p = 0.025) than high-titer patients., Conclusions: Hospitalized breakthrough cases were more likely to have underlying risk factors than unvaccinated patients. Low-spike antibody titers may serve as an indicator for poor prognosis in breakthrough cases admitted to the hospital., (© 2022 The Association for the Publication of the Journal of Internal Medicine.)

Objectives: The emergence of SARS-CoV-2 variants of concern has led to significant phenotypical changes in transmissibility, virulence, and public health measures. Our study used clinical data to compare characteristics between a Delta variant wave and a pre-Delta variant wave of hospitalized patients., Methods: This single-center retrospective study defined a wave as an increasing number of COVID-19 hospitalizations, which peaked and later decreased. Data from the United States Department of Health and Human Services were used to identify the waves' primary variant. Wave 1 (August 8, 2020-April 1, 2021) was characterized by heterogeneous variants, whereas Wave 2 (June 26, 2021-October 18, 2021) was predominantly the Delta variant. Descriptive statistics, regression techniques, and machine learning approaches supported the comparisons between waves., Results: From the cohort (N = 1318), Wave 2 patients (n = 665) were more likely to be younger, have fewer comorbidities, require more care in the intensive care unit, and show an inflammatory profile with higher C-reactive protein, lactate dehydrogenase, ferritin, fibrinogen, prothrombin time, activated thromboplastin time, and international normalized ratio compared with Wave 1 patients (n = 653). The gradient boosting model showed an area under the receiver operating characteristic curve of 0.854 (sensitivity 86.4%; specificity 61.5%; positive predictive value 73.8%; negative predictive value 78.3%)., Conclusion: Clinical and laboratory characteristics can be used to estimate the COVID-19 variant regardless of genomic testing availability. This finding has implications for variant-driven treatment protocols and further research., (Published by Elsevier Ltd.)

Background: Patient Safety Indicator (PSI)-12, a hospital quality measure designed by Agency for Healthcare Research and Quality (AHRQ) to capture potentially preventable adverse events, captures perioperative venous thromboembolism (VTE). It is unclear how COVID-19 has affected PSI-12 performance., Objective: We sought to compare the cumulative incidence of PSI-12 in patients with and without acute COVID-19 infection., Design, Setting, and Participants: This was a retrospective cohort study including PSI-12-eligible events at three Mayo Clinic medical centers (4/1/2020-10/5/2021)., Exposure, Main Outcomes, and Measures: We compared the unadjusted rate and adjusted risk ratio (aRR) for PSI-12 events among patients with and without COVID-19 infection using Fisher's exact χ 2  test and the AHRQ risk-adjustment software, respectively. We summarized the clinical outcomes of COVID-19 patients with a PSI-12 event., Results: Our cohort included 50,400 consecutive hospitalizations. Rates of PSI-12 events were significantly higher among patients with acute COVID-19 infection (8/257 [3.11%; 95% confidence interval {CI}, 1.35%-6.04%]) compared to patients without COVID-19 (210/50,143 [0.42%; 95% CI, 0.36%-0.48%]) with a PSI-12 event during the encounter (p < .001). The risk-adjusted rate of PSI-12 was significantly higher in patients with acute COVID-19 infection (1.50% vs. 0.38%; aRR, 3.90; 95% CI, 2.12-7.17; p < .001). All COVID-19 patients with PSI-12 events had severe disease and 4 died. The most common procedure was tracheostomy (75%); the mean (SD) days from surgical procedure to VTE were 0.12 (7.32) days., Conclusion: Patients with acute COVID-19 infection are at higher risk for PSI-12. The present definition of PSI-12 does not account for COVID-19. This may impact hospitals' quality performance if COVID-19 infection is not accounted for by exclusion or risk adjustment., (© 2022 Society of Hospital Medicine.)

Objective: We examined the association between stay-at-home order implementation and the incidence of COVID-19 infections and deaths in rural versus urban counties of the United States., Design: We used an interrupted time-series analysis using a mixed effects zero-inflated Poisson model with random intercept by county and standardised by population to examine the associations between stay-at-home orders and county-level counts of daily new COVID-19 cases and deaths in rural versus urban counties between 22 January 2020 and 10 June 2020. We secondarily examined the association between stay-at-home orders and mobility in rural versus urban counties using Google Community Mobility Reports., Interventions: Issuance of stay-at-home orders., Primary and Secondary Outcome Measures: Co-primary outcomes were COVID-19 daily incidence of cases (14-day lagged) and mortality (26-day lagged). Secondary outcome was mobility., Results: Stay-at-home orders were implemented later (median 30 March 2020 vs 28 March 2020) and were shorter in duration (median 35 vs 54 days) in rural compared with urban counties. Indoor mobility was, on average, 2.6%-6.9% higher in rural than urban counties both during and after stay-at-home orders. Compared with the baseline (pre-stay-at-home) period, the number of new COVID-19 cases increased under stay-at-home by incidence risk ratio (IRR) 1.60 (95% CI, 1.57 to 1.64) in rural and 1.36 (95% CI, 1.30 to 1.42) in urban counties, while the number of new COVID-19 deaths increased by IRR 14.21 (95% CI, 11.02 to 18.34) in rural and IRR 2.93 in urban counties (95% CI, 1.82 to 4.73). For each day under stay-at-home orders, the number of new cases changed by a factor of 0.982 (95% CI, 0.981 to 0.982) in rural and 0.952 (95% CI, 0.951 to 0.953) in urban counties compared with prior to stay-at-home, while number of new deaths changed by a factor of 0.977 (95% CI, 0.976 to 0.977) in rural counties and 0.935 (95% CI, 0.933 to 0.936) in urban counties. Each day after stay-at-home orders expired, the number of new cases changed by a factor of 0.995 (95% CI, 0.994 to 0.995) in rural and 0.997 (95% CI, 0.995 to 0.999) in urban counties compared with prior to stay-at-home, while number of new deaths changed by a factor of 0.969 (95% CI, 0.968 to 0.970) in rural counties and 0.928 (95% CI, 0.926 to 0.929) in urban counties., Conclusion: Stay-at-home orders decreased mobility, slowed the spread of COVID-19 and mitigated COVID-19 mortality, but did so less effectively in rural than in urban counties. This necessitates a critical re-evaluation of how stay-at-home orders are designed, communicated and implemented in rural areas., Competing Interests: Competing interests: In the past 36 months, RGM also received support from NIDDK, the Patient Centred Outcomes Research Institute (PCORI) and AARP. In the past 36 months, NDS has received research support through Mayo Clinic from the Food and Drug Administration to establish Yale-Mayo Clinic Centre for Excellence in Regulatory Science and Innovation (CERSI) programme; the Centres of Medicare and Medicaid Innovation under the Transforming Clinical Practice Initiative (TCPI); the Agency for Healthcare Research and Quality; the National Heart, Lung and Blood Institute of the NIH; the National Science Foundation and PCORI to develop a Clinical Data Research Network (LHSNet)., (© Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Objective: Are diets with a greater environmental impact less healthy? This is a key question for nutrition policy, but previous research does not provide a clear answer. To address this, our objective here was to test whether American diets with the highest carbon footprints predicted greater population-level mortality from diet-related chronic disease than those with the lowest., Design: Baseline dietary recall data were combined with a database of greenhouse gases emitted in the production of foods to estimate a carbon footprint for each diet. Diets were ranked on their carbon footprints and those in the highest and lowest quintiles were studied here. Preventable Risk Integrated Model (PRIME), an epidemiological modelling software, was used to assess CVD and cancer mortality for a simulated dietary change from the highest to the lowest impact diets. The diet-mortality relationships used by PRIME came from published meta-analyses of randomised controlled trials and prospective cohort studies., Setting: USA., Participants: Baseline diets came from adults (n 12 865) in the nationally representative 2005-2010 National Health and Nutrition Examination Survey., Results: A simulated change at the population level from the highest to the lowest carbon footprint diets resulted in 23 739 (95 % CI 20 349, 27 065) fewer annual deaths from CVD and cancer. This represents a 1·83 % (95 % CI 1·57 %, 2·08 %) decrease in total deaths. About 95 % of deaths averted were from CVD., Conclusions: Diets with the highest carbon footprints were associated with a greater risk of mortality than the lowest, suggesting that dietary guidance could incorporate sustainability information to reinforce health messaging.

Diagnosis codes are used to study SARS-CoV2 infections and COVID-19 hospitalizations in administrative and electronic health record (EHR) data. Using EHR data (April 2020-March 2021) at the Yale-New Haven Health System and the three hospital systems of the Mayo Clinic, computable phenotype definitions based on ICD-10 diagnosis of COVID-19 (U07.1) were evaluated against positive SARS-CoV-2 PCR or antigen tests. We included 69,423 patients at Yale and 75,748 at Mayo Clinic with either a diagnosis code or a positive SARS-CoV-2 test. The precision and recall of a COVID-19 diagnosis for a positive test were 68.8% and 83.3%, respectively, at Yale, with higher precision (95%) and lower recall (63.5%) at Mayo Clinic, varying between 59.2% in Rochester to 97.3% in Arizona. For hospitalizations with a principal COVID-19 diagnosis, 94.8% at Yale and 80.5% at Mayo Clinic had an associated positive laboratory test, with secondary diagnosis of COVID-19 identifying additional patients. These patients had a twofold higher inhospital mortality than based on principal diagnosis. Standardization of coding practices is needed before the use of diagnosis codes in clinical research and epidemiological surveillance of COVID-19., (© 2022. The Author(s).)

Background: Several vaccines are now available under emergency use authorization in the United States and have demonstrated efficacy against symptomatic COVID-19. Vaccine impact on asymptomatic severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is largely unknown., Methods: We conducted a retrospective cohort study of consecutive, asymptomatic adult patients (n = 39 156) within a large US healthcare system who underwent 48 333 preprocedural SARS-CoV-2 molecular screening tests between 17 December 2020 and 8 February 2021. The primary exposure of interest was vaccination with ≥1 dose of an mRNA COVID-19 vaccine. The primary outcome was relative risk (RR) of a positive SARS-CoV-2 molecular test among those asymptomatic persons who had received ≥1 dose of vaccine compared with persons who had not received vaccine during the same time period. RR was adjusted for age, sex, race/ethnicity, patient residence relative to the hospital (local vs nonlocal), healthcare system regions, and repeated screenings among patients using mixed-effects log-binomial regression., Results: Positive molecular tests in asymptomatic individuals were reported in 42 (1.4%) of 3006 tests and 1436 (3.2%) of 45 327 tests performed on vaccinated and unvaccinated patients, respectively (RR, .44; 95% CI, .33-.60; P < .0001). Compared with unvaccinated patients, risk of asymptomatic SARS-CoV-2 infection was lower among those >10 days after the first dose (RR, .21; 95% CI, .12-.37; P < .0001) and >0 days after the second dose (RR, .20; 95% CI, .09-.44; P < .0001) in the adjusted analysis., Conclusions: COVID-19 vaccination with an mRNA-based vaccine showed a significant association with reduced risk of asymptomatic SARS-CoV-2 infection as measured during preprocedural molecular screening. Results of this study demonstrate the impact of the vaccines on reduction in asymptomatic infections supplementing the randomized trial results on symptomatic patients., (© The Author(s) 2021. Published by Oxford University Press for the Infectious Diseases Society of America.)

Objective: We evaluated the risk of patients contracting coronavirus disease 2019 (COVID-19) during their hospital stay to inform the safety of hospitalization for a non-COVID-19 indication during this pandemic., Methods: A case series of adult patients hospitalized for 2 or more nights from May 15 to June 15, 2020 at large tertiary-care hospital in the midwestern United States was reviewed. All patients were screened at admission with the severe acute respiratory coronavirus virus 2 (SARS-CoV-2) polymerase chain reaction (PCR) test. Selected adult patients were also tested by IgG serology. After dismissal, patients with negative serology and PCR at admission were asked to undergo repeat serologic testing at 14-21 days after discharge. The primary outcome was healthcare-associated COVID-19 defined as a new positive SARS-CoV-2 PCR test on or after day 4 of hospital stay or within 7 days of hospital dismissal, or seroconversion in patients previously established as seronegative., Results: Of the 2,068 eligible adult patients, 1,778 (86.0%) completed admission PCR testing, while 1,339 (64.7%) also completed admission serology testing. Of the 1,310 (97.8%) who were both PCR and seronegative, 445 (34.0%) repeated postdischarge serology testing. No healthcare-associated COVID-19 cases were detected during the study period. Of 1,310 eligible PCR and seronegative adults, no patients tested PCR positive during hospital admission (95% confidence interval [CI], 0.0%-0.3%). Of the 445 (34.0%) who completed postdischarge serology testing, no patients seroconverted (0.0%; 95% CI, 0.0%-0.9%)., Conclusion: We found low likelihood of hospital-associated COVID-19 with strict adherence to universal masking, physical distancing, and hand hygiene along with limited visitors and screening of admissions with PCR.

Predictive models have played a critical role in local, national, and international response to the COVID-19 pandemic. In the United States, health care systems and governmental agencies have relied on several models, such as the Institute for Health Metrics and Evaluation, Youyang Gu (YYG), Massachusetts Institute of Technology, and Centers for Disease Control and Prevention ensemble, to predict short- and long-term trends in disease activity. The Mayo Clinic Bayesian SIR model, recently made publicly available, has informed Mayo Clinic practice leadership at all sites across the United States and has been shared with Minnesota governmental leadership to help inform critical decisions during the past year. One key to the accuracy of the Mayo Clinic model is its ability to adapt to the constantly changing dynamics of the pandemic and uncertainties of human behavior, such as changes in the rate of contact among the population over time and by geographic location and now new virus variants. The Mayo Clinic model can also be used to forecast COVID-19 trends in different hypothetical worlds in which no vaccine is available, vaccinations are no longer being accepted from this point forward, and 75% of the population is already vaccinated. Surveys indicate that half of American adults are hesitant to receive a COVID-19 vaccine, and lack of understanding of the benefits of vaccination is an important barrier to use. The focus of this paper is to illustrate the stark contrast between these 3 scenarios and to demonstrate, mathematically, the benefit of high vaccine uptake on the future course of the pandemic., (Copyright © 2021. Published by Elsevier Inc.)

In March 2020, our institution developed an interdisciplinary predictive analytics task force to provide coronavirus disease 2019 (COVID-19) hospital census forecasting to help clinical leaders understand the potential impacts on hospital operations. As the situation unfolded into a pandemic, our task force provided predictive insights through a structured set of visualizations and key messages that have helped the practice to anticipate and react to changing operational needs and opportunities. The framework shared here for the deployment of a COVID-19 predictive analytics task force could be adapted for effective implementation at other institutions to provide evidence-based messaging for operational decision-making. For hospitals without such a structure, immediate consideration may be warranted in light of the devastating COVID-19 third-wave which has arrived for winter 2020-2021., (Copyright © 2021 Mayo Foundation for Medical Education and Research. Published by Elsevier Inc. All rights reserved.)

Objective: To investigate the impact of limiting the definition of post-coronary artery bypass graft (CABG) atrial fibrillation (AF) to AF/flutter requiring treatment-as in the Society of Thoracic Surgeons' (STS) database- on the association with survival., Patients and Methods: We assessed in-hospital incidence of post-CABG AF in 7110 consecutive isolated patients with CABG without preoperative AF at 4 hospitals (January 1, 2004 to December 31, 2010). Patients with ≥1 episode of post-CABG AF detected via continuous in-hospital electrocardiogram (ECG)/telemetry monitoring documented by physicians were assigned to the following: Group 1, identified as having post-CABG AF in STS data and Group 2, not identified as having post-CABG AF in STS data. Patients without documented post-CABG AF constituted Group 3. Survival was compared via a Cox model, adjusted for STS risk of mortality and accounting for site differences., Results: Over 7 years' follow-up, 16.0% (295 of 1841) of Group 1, 18.7% (79 of 422) of Group 2, and 7.9% (382 of 4847) of Group 3 died. Group 2 had a significantly greater adjusted risk of death than both Group 1 (hazard ratio [HR]: 1.16; 95% confidence interval [CI], 1.02 to 1.33) and Group 3 (HR: 1.94; 95% CI, 1.69 to 2.22)., Conclusions: The statistically significant 16% higher risk of death for patients with AF post-CABG missed vs captured in STS data suggests treatment and postdischarge management should be investigated for differences. The historical misclassification of "missed" patients as experiencing no AF in the STS data weakens the ability to observe differences in risk between patients with and without post-CABG AF. Therefore, STS data should not be used for research examining post-CABG AF., (© 2020 Mayo Foundation for Medical Education and Research. Published by Elsevier Inc.)

Importance: The Centers for Medicare and Medicaid Services's (CMS's) 30-day risk-standardized mortality rate (RSMR) and risk-standardized readmission rate (RSRR) models do not adjust for do-not-resuscitate (DNR) status of hospitalized patients and may bias Hospital Readmissions Reduction Program (HRRP) financial penalties and Overall Hospital Quality Star Ratings., Objective: To identify the association between hospital-level DNR prevalence and condition-specific 30-day RSMR and RSRR and the implications of this association for HRRP financial penalty., Design, Setting, and Participants: This cross-sectional study obtained patient-level data from the Medicare Limited Data Set Inpatient Standard Analytical File and hospital-level data from the CMS Hospital Compare website for all consecutive Medicare inpatient encounters from July 1, 2015, to June 30, 2018, in 4484 US hospitals. Hospitalized patients had a principal diagnosis of acute myocardial infarction (AMI), heart failure (HF), stroke, pneumonia, or chronic obstructive pulmonary disease (COPD). Incoming acute care transfers, discharges against medical advice, and patients coming from or discharged to hospice were among those excluded from the analysis., Exposures: Present-on-admission (POA) DNR status was defined as an International Classification of Diseases, Ninth Revision diagnosis code of V49.86 (before October 1, 2015) or as an International Statistical Classification of Diseases and Related Health Problems, Tenth Revision diagnosis code of Z66 (beginning October 1, 2015). Hospital-level prevalence of POA DNR status was calculated for each of the 5 conditions., Main Outcomes and Measures: Hospital-level 30-day RSMRs and RSRRs for 5 condition-specific cohorts (mortality cohorts: AMI, HF, stroke, pneumonia, and COPD; readmission cohorts: AMI, HF, pneumonia, and COPD) and HRRP financial penalty status (yes or no)., Results: Included in the study were 4 884 237 inpatient encounters across condition-specific 30-day mortality cohorts (patient mean [SD] age, 78.8 [8.5] years; 2 608 182 women [53.4%]) and 4 450 378 inpatient encounters across condition-specific 30-day readmission cohorts (patient mean [SD] age, 78.6 [8.5] years; 2 349 799 women [52.8%]). Hospital-level median (interquartile range [IQR]) prevalence of POA DNR status in the mortality cohorts varied: 11% (7%-16%) for AMI, 13% (7%-23%) for HF, 14% (9%-22%) for stroke, 17% (9%-26%) for pneumonia, and 10% (5%-18%) for COPD. For the readmission cohorts, the hospital-level median (IQR) POA DNR prevalence was 9% (6%-15%) for AMI, 12% (6%-22%) for HF, 16% (8%-24%) for pneumonia, and 9% (4%-17%) for COPD. The 30-day RSMRs were significantly higher for hospitals in the highest quintiles vs the lowest quintiles of DNR prevalence (eg, AMI: 12.9 [95% CI, 12.8-13.1] vs 12.5 [95% CI, 12.4-12.7]; P < .001). The inverse was true among the readmission cohorts, with the highest quintiles of DNR prevalence exhibiting the lowest RSRRs (eg, AMI: 15.3 [95% CI, 15.1-15.5] vs 15.9 [95% CI, 15.7-16.0]; P < .001). A 1% absolute increase in risk-adjusted hospital-level DNR prevalence was associated with greater odds of avoiding HRRP financial penalty (odds ratio, 1.06; 95% CI, 1.04-1.08; P < .001)., Conclusions and Relevance: This cross-sectional study found that the lack of adjustment in CMS 30-day RSMR and RSRR models for POA DNR status of hospitalized patients may be associated with biased readmission penalization and hospital-level performance.

Background: New-onset atrial fibrillation (AF) after coronary artery bypass graft surgery (CABG) is associated with poor outcomes, but data on the effects of its characteristics are lacking and conflicting. We examined the effect number of post-CABG AF events has on long-term mortality risk, and whether this is sex dependent., Methods: Routinely collected Society of Thoracic Surgeons (STS) data were supplemented with details on new-onset post-CABG AF (detected in-hospital by continuous electrocardiogram/telemetry monitoring) and long-term survival for 9203 consecutive patients with isolated-CABG (2002-2010). With the use of Cox regression, we determined the propensity-adjusted (STS-recognized risk factors) effect of number of AF events on survival, testing for effect modification by sex and controlling for AF duration., Results: AF occurred in 739 women (29.4%) and 2157 men (32.3%) (P < .001). Adjusted results showed 2 or more AF events significantly (P < .001) increased 5-year mortality risk, independently of total AF duration. However, mortality risk differed between the sexes (P < .001): women with 2 AF episodes had the greatest increase (hazard ratio [HR] = 2.98; 95% confidence interval [CI], 1.43-4.83; versus women without AF), followed by women and men with 4 or more AF events (HR = 2.76 [95% CI, 1.27-4.55] and HR = 2.73 [95% CI, 2.30-3.19], respectively). A single post-CABG AF episode was not associated with increased mortality risk., Conclusions: Both men and women who experienced 2 or more post-CABG AF episodes showed increased risk of 5-year mortality, independent of total AF duration. Although men's risk increased as the number of AF events increased, women's risk peaked at 2 AF events. Future research needs to determine whether this divergence stems from differences in treatment/management or underlying biology., (Copyright © 2020 The Society of Thoracic Surgeons. Published by Elsevier Inc. All rights reserved.)

Background: We sought to fill important gaps in the existing evidence regarding new-onset atrial fibrillation (AF) after coronary artery bypass graft surgery (CABG) by comparing the incidence, characteristics, and effect on long-term survival between men and women., Methods: Nine thousand two hundred three consecutive patients without preoperative AF underwent isolated CABG from 2002 to 2010 at 3 US academic medical centers and 1 high-volume specialty cardiac hospital. Detailed data on CABG AF events detected via continuous in-hospital electrocardiogram/telemetry monitoring were supplemented with Society of Thoracic Surgeons data, and survival data, censored at October 31, 2011, using a copy of the Social Security Death Master File archived before state-owned data were removed (November 1, 2011)., Results: Propensity-adjusted (Society of Thoracic Surgeons-recognized risk factors) incidence of post-CABG AF was 31.5% overall, 32.8% in men, and 27.4% in women. Over the 9-year study period, women had a significantly lower risk of post-CABG AF (absolute difference, -5.3% [95% confidence interval (CI), -10.5% to -0.6%]), and significantly shorter first (-2.9 hours; 95% CI, -5.8 to 0.0), and longest (-4.3 hours; 95% CI, -8.3 to -0.3) AF duration. Post-CABG AF was associated with significantly increased risk of long-term mortality (overall hazard ratio [HR], 1.56; 95% CI, 1.45-1.67; men HR, 1.57; 95% CI, 1.49-1.65; women HR, 1.54; 95% CI, 1.14-2.07)., Conclusions: In our study, women had lower adjusted risk of post-CABG AF and experienced shorter episodes. The adjusted risk of long-term mortality was 56% greater among patients who developed post-CABG AF compared with those who did not. The effect of post-CABG AF on long-term survival did not differ between the sexes., (Copyright © 2019. Published by Elsevier Inc.)

Background: Two quality measures used in public reporting and value-based payment programs require β-blockers be administered less than 24 hours before isolated coronary artery bypass graft surgery to prevent atrial fibrillation and mortality. Questions have arisen about continued use of these measures., Methods: We conducted a systematic search for randomized controlled trials (RCTs) examining the impact of preoperative β-blockers on atrial fibrillation or mortality after isolated coronary artery bypass graft surgery to determine what evidence of efficacy supports the measures., Results: We identified 11 RCTs. All continued β-blockers postoperatively, making it unfeasible to separate the benefits of preoperative vs postoperative administration. Meta-analysis was precluded by methodologic variation in β-blocker utilized, timing and dosage, and supplemental and comparison treatments. Of the eight comparisons of β-blockers/β-blocker plus digoxin versus placebo (n = 826 patients), six showed significant reductions in atrial fibrillation/supraventricular arrhythmias. Of the three comparisons (n = 444) of β-blockers versus amiodarone, two found no significant difference in atrial fibrillation; the third showed significantly lower incidence with amiodarone. One RCT compared β-blocker plus amiodarone versus each of those drugs separately; the combination reduced atrial fibrillation significantly better than the β-blocker alone, but not amiodarone alone. Seven RCTs reported short-term mortality, but this outcome was too rare and the sample sizes too small to provide any meaningful comparisons., Conclusions: Existing RCT evidence does not support the structure of quality measures that require β-blocker administration specifically within 24 hours before coronary artery bypass graft surgery to prevent postoperative atrial fibrillation or short-term mortality. Quality measures should be revised to align with the evidence, and further studies conducted to determine optimal timing and method of prophylaxis., (Copyright © 2020 The Society of Thoracic Surgeons. Published by Elsevier Inc. All rights reserved.)

Objective: Studies with authors trained in research methods are of higher quality than those without. We examined inclusion of authors with master's or doctoral degrees incorporating advanced research methods training on original research articles in high-impact journals, investigating differences between journals and by first-author sex., Methods: Using all original research articles from 1 issue of The New England Journal of Medicine ( NEJM ), Journal of the American Medical Association ( JAMA ), Annals of Internal Medicine ( Annals ), and JAMA-Internal Medicine/Archives of Internal Medicine ( Archives ) every alternate month, February 1994 to October 2016, we assessed the prevalence of articles listing authors with master's/doctoral research degrees and its adjusted associations with time of publication, journal, and first-author sex via multivariable logistic regression models (accounting for number of authors, study type, specialty/topic, and continent and for interactions between journal and time of publication, study type, and continent)., Results: Of 3009 articles examined, 84.4% (n=2539) had authors listing research degrees. After adjustment, the prevalence of such articles increased from 1994 to 2016 ( P <.001), but patterns differed among journals. Annals and NEJM increased to approximately100% by 2016; JAMA and Archives peaked around 2010 to 2011, then declined. Articles with female first authors were more likely to list authors with research degrees (adjusted odds ratio=1.66; 95% CI, 1.29-2.13; P <.001)., Conclusion: The prevalence of original research articles listing authors trained in research methods in high-impact journals increased significantly but is now declining at some journals, with potential effects on quality. The greater prevalence among female first-authored articles suggests possible sex differences in structuring/crediting research teams or subconscious sex bias during review.

Background and Aims: In this analysis, we estimated population-level trajectory groups of life course cardiovascular risk to explore their impact on mid-life atherosclerotic and metabolic outcomes., Methods: This prospective study followed n = 1269 Bogalusa Heart participants, each with at least 4 study visits from childhood in 1973 through adulthood in 2016. We used discrete mixture modeling to determine trajectories of cardiovascular risk percentiles from childhood to adulthood. Outcomes included mid-life subclinical atherosclerotic measures [(carotid intima-media thickness (cIMT), pulse wave velocity (PWV)], metabolic indicators [(diabetes and body mass index (BMI)], and short physical performance battery (SPPB)., Results: Between the mean ages of 9.6-48.3 years, we estimated five distinct trajectory groups of life course cardiovascular risk (High-Low, High-High, Mid-Low, Low-Low, and Low-High). Adult metabolic and vascular outcomes were significantly determined by life course cardiovascular risk trajectory groups (all p < 0.01). Those in the High-Low group had lower risks of diabetes (20% vs. 28%, respectively; p = .12) and lower BMIs (32.4 kg/m 2 vs. 34.6 kg/m 2 ; p = .06) than those who remained at high risk (High-High) throughout life. However, the High-Low group had better cIMT (0.89 mm vs. 1.05 mm; p < .0001) and PWV (7.8 m/s vs. 8.2 m/s; p = .03) than the High-High group. For all outcomes, those in the Low-Low group fared best., Conclusions: We found considerable movement between low- and high-relative cardiovascular risk strata over the life course. Children who improved their relative cardiovascular risk over the life course achieved better mid-life atherosclerotic health despite maintaining relatively poor metabolic health through adulthood., (Copyright © 2018 Elsevier B.V. All rights reserved.)

Background: A validated model for predicting 1-year outcomes after transcatheter aortic valve replacement (TAVR) does not exist. TAVR-specific risk models may benefit from frailty markers, and sarcopenia may represent an objective frailty marker. This study assessed the predictive ability of sarcopenia and frailty markers on 1-year mortality after TAVR., Methods: We evaluated 470 patients undergoing TAVR at a single center. Frailty was assessed using four markers: gait speed, hand grip strength, serum albumin, and Katz activities of daily living. Sarcopenia was measured as the cross-sectional psoas muscle area on pre-TAVR computed tomography. Performance of four models incorporating The Society of Thoracic Surgeons Predicted Risk of Mortality, frailty, or sarcopenia metrics, or both, for predicting 1-year mortality was assessed with area under the curve, Hosmer-Lemeshow statistics, and calibration plots., Results: A total of 63 deaths (13.4%) deaths occurred by 1 year. The Society of Thoracic Surgeons Predicted Risk of Mortality alone was poorly predictive of 1-year mortality (area under the curve, 0.52; 95% confidence interval, 0.42 to 0.68). Only the model including sarcopenia and all frailty markers (area under the curve, 0.61; 95% confidence interval, 0.53 to 0.68) significantly improved predictive ability compared with The Society of Thoracic Surgeons Predicted Risk of Mortality alone (p = 0.05). Albumin was the only frailty marker significantly associated with increased risk for 1-year mortality (p = 0.03). Psoas muscle area, as a surrogate for sarcopenia, was not significantly associated with increased risk for 1-year mortality., Conclusions: Most of the commonly used pre-TAVR risk assessments are poorly predictive of 1-year mortality. Albumin was the only frailty marker that was associated with higher mortality. Future studies should investigate whether optimization of nutritional status can improve outcomes after TAVR., (Copyright © 2018 The Society of Thoracic Surgeons. Published by Elsevier Inc. All rights reserved.)

Objectives: Due to increasing clinical experience with transcatheter aortic valve implantation (TAVI) procedures, sophisticated imaging and advanced device technology, TAVI complication rates are low; however, patients requiring conversion to surgery are confronted with an increased mortality risk. In this retrospective study, we evaluated the predictors for conversion and the outcomes of these patients., Methods: We analysed the records of all patients undergoing TAVI in our centre from 2011 to 2016 and focused on cases that required conversion to sternotomy. We investigated reasons and risk factors for conversion as well as 30-day and 1-year outcomes., Results: During the study period, 32 (2.1%) of 1775 patients undergoing TAVI required immediate conversion to sternotomy. Annular rupture (5 of 32; 16%), device embolization (9 of 32; 28%) and pericardial tamponade (15 of 32; 47%) were the most common reasons for conversion. Usage of a self-expandable valve showed to be the only predictor for conversion (odds ratio 0.38, 95% confidence interval 0.16-0.90; P = 0.03). Survival at 30 days and 1 year was 56% and 41%, respectively. Patients who survived 30 days after conversion showed higher preoperative ejection fraction, shorter duration of surgery and shorter perfusion time., Conclusions: In this high-volume, single-centre experience, conversion to sternotomy during TAVI occurred in about 2%, with annular rupture, device embolization and pericardial tamponade being the most common causes. Complications requiring conversion showed to be unpredictable. However, in view of these life-threatening complications, the 30-day survival rate exceeding 50% emphasizes the importance of an experienced and well-attuned heart team providing immediate access to surgical bailout procedures.

Objectives: Postoperative atrial fibrillation (AF) following coronary artery bypass graft surgery (CABG) is significantly associated with reduced survival, but poor characterisation and inconsistent definitions present barriers to developing effective prophylaxis and management. We sought to address this knowledge gap., Methods: From 2002 to 2010, 11 239 consecutive patients without AF underwent isolated CABG at five sites. Clinical data collected for the Society of Thoracic Surgeons (STS) Database were augmented with details on AF detected via continuous in-hospital ECG/telemetry monitoring to assess new-onset post-CABG AF (adjusted for STS risk of mortality); time to first AF; durations of first and longest AF episodes; total in-hospital time in AF; number of in-hospital AF episodes; operative mortality; stroke; discharge in AF; and length of stay (LOS)., Results: Unadjusted incidence of new-onset post-CABG AF was 29.5%. Risk-adjusted incidence was 33.1% and varied little over time (P=0.139). Among 3312 patients with post-CABG AF, adjusted median time to first AF was 52 (IQR: 48-55) hours; mean (SD) duration of first and longest events were 7.2 (5.3,9.1) and 13.1 (10.4,15.9) hours, respectively, and adjusted median total time in AF was 22 (IQR: 18-26) hours. Adjusted rates of operative mortality, stroke and discharge in AF did not vary significantly over time (P=0.156, P=0.965 and P=0.347, respectively). LOS varied (P=0.035), but in no discernible pattern., Conclusions: Each year, ~800 000 people undergo CABG worldwide; >264 000 will develop post-CABG AF. Onset is typically 2-3 days post-CABG and episodes last, on average, several hours. Effective prophylaxis and management is urgently needed to reduce associated risks of adverse outcomes., Competing Interests: Competing interests: None declared., (© Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.)