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The risks and benefits of anticoagulation for patients with both heart failure and atrial fibrillation are unclear. We hypothesized that anticoagulation was associated with improved clinical outcomes of heart failure patients with atrial fibrillation independent of other risk factors. We conducted a retrospective cohort study of clinical registry data linked to Medicare claims for new users of oral anticoagulation (warfarin) without contraindications, discharged home alive, and stratified by CHADS2 score. Outcomes of interest were propensity score-adjusted estimates of the effects of warfarin at discharge on all-cause mortality, thromboembolic events, major adverse cardiovascular events, and bleeding events. Among 10,494 patients with heart failure and atrial fibrillation, the 2249 patients newly treated with warfarin had lower 1-year mortality (27.7% vs 39.3% for CHADS2 score ≤ 3 [P < .001]; 31.6% vs 41.8% for CHADS2 score > 3 [P < .001]) than patients not treated with warfarin. There was no significant difference in thromboembolic events, major adverse cardiovascular events, or bleeding events at 1 year. After multivariate adjustment, exposed individuals in both CHADS2 subgroups had lower adjusted 1-year mortality (CHADS2 ≤ 3: hazard ratio, 0.78 [95% confidence interval, 0.69-0.89]; CHADS 2 > 3: 0.78 [0.66-0.93]). In conclusion, warfarin use in heart failure patients with atrial fibrillation was associated with improved survival at 1 year independent of baseline CHADS2 score. However, there was no significant reduction in clinical events, such as thromboembolic or major adverse cardiovascular events at 1 year that might simply explain the survival benefit associated with warfarin.

Background: Inpatient clinical registries generally have limited ability to provide a longitudinal perspective on care beyond the acute episode. We present a method to link hospitalization records from registries with Medicare inpatient claims data, without using direct identifiers, to create a unique data source that pairs rich clinical data with long-term outcome data.Methods and Results: The method takes advantage of the hospital clustering observed in each database by demonstrating that different combinations of indirect identifiers within hospitals yield a large proportion of unique patient records. This high level of uniqueness also allows linking without advance knowledge of the Medicare provider number of each registry hospital. We applied this method to 2 inpatient databases and were able to identify 81% of 39,178 records in a large clinical registry of patients with heart failure and 91% of 6,581 heart failure records from a hospital inpatient database. The quality of the link is high, and reasons for incomplete linkage are explored. Finally, we discuss the unique opportunities afforded by combining claims and clinical data for specific analyses.Conclusions: In the absence of direct identifiers, it is possible to create a high-quality link between inpatient clinical registry data and Medicare claims data. The method will allow researchers to use existing data to create a linked claims-clinical database that capitalizes on the strengths of both types of data sources. [ABSTRACT FROM AUTHOR]

Objective: To explore relationships between beta-cell function and incident cardiovascular events, death, and medical costs among elderly individuals.Research Design and Methods: In a prospective, population-based cohort of 4555 elderly individuals, we examined the effect of beta-cell function on incident cardiovascular events and mortality. We also examined costs for 3715 of these individuals. We used the computer-based homeostasis model assessment (HOMA) to calculate indices of beta-cell function (HOMA-%B) and insulin sensitivity (HOMA-%S) using baseline fasting glucose and insulin levels. All subjects were followed from 1992/1993 for 6 years or until death.Main Outcome Measures: Discrete-time survival model of the effects of beta-cell function on incident cardiovascular events and all-cause mortality; and semiparametric estimators for calculations of mean 6-year costs.Results: Controlling for HOMA-%S, a 20% decrease in HOMA-%B was associated with increased odds of incident cardiovascular events (odds ratio [OR], 1.09; 95% confidence interval [CI], 1.05-1.14) and death (OR, 1.10; 95% CI, 1.07-1.14). The relationships persisted after controlling for clinical and sociodemographic confounders. A 20% decrease in HOMA-%B was also associated with increased costs (cost ratio, 1.03; 95% CI, 1.01-1.05). The significant association did not persist after controlling for confounders.Limitations: The sample comprises relatively healthy elderly individuals and is based on data from 1992 through 1999, which may not reflect current experience. The measure of beta-cell function is an estimate generated from single measures of glucose and insulin.Conclusions: Beta-cell function as measured by HOMA-%B is a significant predictor of incident cardiovascular events and mortality but not of costs, controlling for HOMA-%S and sociodemographic and clinical confounders. [ABSTRACT FROM AUTHOR]

OBJECTIVE: The cardiovascular consequences of the metabolic syndrome and its component risk factors have been documented in elderly individuals. Little is known about how the metabolic syndrome and its individual components translate into long-term medical costs. RESEARCH DESIGN AND METHODS: We used log-linear regression models to assess the independent contributions of the metabolic syndrome and its individual components to 10-year medical costs among 3,789 individuals aged > or = 65 years in the Cardiovascular Health Study. RESULTS: As defined by the National Cholesterol Education Program Third Adult Treatment Panel report, the metabolic syndrome was present in 47% of the sample. Total costs to Medicare were 20% higher among participants with the metabolic syndrome ($40,873 vs. $33,010; P < 0.001). Controlling for age, sex, race/ethnicity, and other covariates, we found that abdominal obesity, low HDL cholesterol, and elevated blood pressure were associated with 15% (95% CI 4.3-26.7), 16% (1.7-31.8), and 20% (10.1-31.7) higher costs, respectively. When added to the model, the metabolic syndrome composite variable did not contribute significantly (P = 0.32). CONCLUSIONS: Abdominal obesity, low HDL cholesterol, and hypertension but not the metabolic syndrome per se are important predictors of long-term costs in the Medicare population. [ABSTRACT FROM AUTHOR]

Background: Despite continuing debate over a prescription drug benefit for the Medicare program, there has been relatively little research estimating the potential cost of providing such a benefit.Objective: The objective of this study was to estimate the effect of prescription drug insurance on outpatient prescription drug expenditures among the elderly.Research Design: We studied respondents aged > or =65 years to the 1997 Medical Expenditure Panel Survey, a representative survey of the U.S. noninstitutionalized population. Survey-weighted linear regression models were used to estimate the probability of any expenditures and total expenditures while controlling for sociodemographic characteristics, chronic conditions, and health status.Measures: We used prescription drug insurance status and outpatient prescription drug expenditures.Results: An estimated 34 million elderly people filled 630 million prescriptions in 1997. Thirty-seven percent did not have prescription drug insurance. Total prescription drug expenditures exceeded $23 billion. Persons without prescription drug insurance spent slightly less than $7 billion; those with insurance spent more than $16 billion. After controlling for health status, comorbidity, and demographic characteristics, prescription drug insurance increased expenditures by $183 per person. The marginal increase in total expenditures of extending the average observed benefit to those currently uninsured is $2.3 billion (95% confidence interval, $1.2-3.5 billion).Conclusions: Proposals for a Medicare drug benefit provide high copayments to protect against insurance effects and to address uncertainty in cost estimates of the proposed benefit. By quantifying the insurance effect on expenditures among the elderly, the data reported here could reduce uncertainty in the budget estimation process. [ABSTRACT FROM AUTHOR]

OBJECTIVES: To determine differences in mortality after admission for acute myocardial infarction (AMI) and in use of noninvasive and invasive treatments for AMI between patients with and without dementia. DESIGN: Retrospective chart review. SETTING: Cooperative Cardiovascular Project. PATIENTS: Medicare patients admitted for AMI (N=129,092) in 1994 and 1995. MEASUREMENTS: Dementia noted on medical chart as history of dementia, Alzheimer's disease, chronic confusion, or senility. Outcome measures included mortality at 30 days and 1-year postadmission; use of aspirin, beta-blocker, angiotensin-converting enzyme (ACE) inhibitor, thrombolytic therapy, cardiac catheterization, coronary angioplasty, and cardiac bypass surgery compared by dementia status. RESULTS: Dementia was associated with higher mortality at 30 days (relative risk (RR)=1.16, 95% confidence interval (CI)=1.09-1.22) and at 1-year postadmission (RR=1.18, 95% CI=1.13-1.23). There were few to no differences in the use of aspirin and beta-blockers between patients with and without a history of dementia. Patients with a history of dementia were less likely to receive ACE inhibitors during the stay (RR=0.89, 95% CI=0.86-0.93) or at discharge (RR=0.90, 95% CI=0.86-0.95), thrombolytic therapy (RR=0.82, 95% CI=0.74-0.90), catheterization (RR=0.51, 95% CI=0.47-0.55), coronary angioplasty (RR=0.58, 95% CI=0.51-0.66), and cardiac bypass surgery (RR=0.41, 95% CI=0.33-0.50) than patients without a history of dementia. CONCLUSION: The results imply that the presence of dementia had a major effect on mortality and care patterns for this condition. [ABSTRACT FROM AUTHOR]

Background: Risk stratification for comparison of outcomes after coronary artery bypass grafting (CABG) typically includes only clinical measures of risk. Patient-reported health status may be an important independent predictor of short-term health outcomes.Objective: To determine whether patient-reported health status, as measured by the Physical and Mental Component Summary scores of the SF-36, predicts in-hospital mortality and prolonged length of stay after CABG, after controlling for other clinical predictors of those outcomes.Research Design: Prospective cohort study conducted from September 1993 to November 1995.Subjects: One thousand seven hundred seventy-eight adults who underwent isolated CABG for myocardial ischemia.Measures: In-hospital mortality and prolonged length of stay (> 14 days).Results: There were 27 deaths and 223 patients with prolonged length of stay in the study sample. A 10-point decrease in the Physical Component Summary (PCS) score increased the odds of in-hospital mortality by 61% (OR, 1.61; 95% CI, 1.04-2.49), independent of established clinical risk factors. Similarly, a 10-point decrease in the PCS score increased the odds of prolonged length of stay by 33% (OR, 1.33; 95% CI, 1.13-1.57). A 10-point decrease in the Mental Component Summary score (MCS) decreased the odds of mortality by 36% (OR, 0.64; 95% CI, 0.43-0.95).Conclusions: The PCS score is independently and significantly associated with in-hospital mortality and prolonged length of stay, after controlling for clinical risk factors. The MCS score is independently and significantly associated only with mortality, though the direction of the effect is unexpected. The result likely reflects a property of the scoring of the MCS and not a finding of clinical substance. Although caution must be taken when interpreting the summary scores, the SF-36 yields information not otherwise captured by clinical data and may be useful in risk stratification for in-hospital mortality and prolonged length of stay after CABG. [ABSTRACT FROM AUTHOR]

STUDY OBJECTIVE: Although regionalized care for ST-segment elevation myocardial infarction (STEMI) has improved the use of timely reperfusion therapy, its effect on patient outcomes has been difficult to assess. Our objective is to explore temporal trends in STEMI mortality with the implementation of a statewide STEMI regionalization program (Reperfusion of Acute Myocardial Infarction in North Carolina Emergency Departments [RACE]). METHODS: We compared trends in inpatient mortality among STEMI patients treated at North Carolina (NC) hospitals participating in the RACE program, relative to those not participating, using state inpatient claims data. Using Medicare claims data, we compared trends in 30-day mortality among Medicare beneficiaries in NC with those nationally. Logistic models with random effects were used to evaluate the association of the program with mortality. RESULTS: From 2005 to 2007, inpatient mortality for 6,565 STEMI patients treated at NC hospitals participating in RACE decreased from 11.6% to 10.1% (risk difference -1.5%; 95% confidence interval [CI] -3.0% to 0.04%), whereas inpatient mortality among 5,850 STEMI patients treated at NC nonparticipating hospitals decreased from 10.2% to 8.6% (risk difference -1.6%; 95% CI -3.1% to 0.10%); (adjusted odds ratio 1.28; 95% CI 0.88 to 1.85 for temporal differences between groups). During the same period, 30-day STEMI mortality among Medicare beneficiaries decreased from 22.7% to 21.4% in NC (risk difference -1.28%; 95% CI -3.60% to 1.03%) and from 22.3% to 21.6% nationally (risk difference -0.71%, 95% CI -1.13% to -0.29%; adjusted odds ratio 0.99, 95% CI 0.85 to 1.15 for temporal differences between regions). CONCLUSION: The initiation of a statewide STEMI collaborative care model was associated with a reduction in mortality rates according to claims data, yet these changes were similar to those seen nationally. Further study is needed to evaluate regionalized systems of STEMI care and to determine the role of claims data to evaluate population-based STEMI outcomes. [ABSTRACT FROM AUTHOR]

Background: Administrative claims are a rich source of information for epidemiological and health services research; however, the ability to accurately capture specific diseases or complications using claims data has been debated. In this study, the authors examined the validity of International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) diagnosis codes for the identification of hyponatremia in an outpatient managed care population.Methods: We analyzed outpatient laboratory and professional claims for patients aged 18 years and older in the National Managed Care Benchmark Database from Integrated Healthcare Information Services. We obtained all claims for outpatient serum sodium laboratory tests performed in 2004 and 2005, and all outpatient professional claims with a primary or secondary ICD-9-CM diagnosis code of hyponatremia (276.1).Results: A total of 40,668 outpatient serum sodium laboratory results were identified as hyponatremic (serum sodium < 136 mmol/L). The sensitivity of ICD-9-CM codes for hyponatremia in outpatient professional claims within 15 days before or after the laboratory date was 3.5%. Even for severe cases (serum sodium < or = 125 mmol/L), sensitivity was < 30%. Specificity was > 99% for all cutoff points.Conclusion: ICD-9-CM codes in administrative data are insufficient to identify hyponatremia in an outpatient population. [ABSTRACT FROM AUTHOR]

Purpose: In the absence of evidence from large clinical trials, optimal therapy for localized prostate cancer remains unclear; however, treatment patterns continue to change. We examined changes in the management of patients with prostate cancer in the Medicare population.Methods and Materials: We conducted a retrospective claims-based analysis of the use of radiation therapy, surgery, and androgen deprivation therapy in the 12 months after diagnosis of prostate cancer in a nationally representative 5% sample of Medicare claims. Patients were Medicare beneficiaries 67 years or older with incident prostate cancer diagnosed between 1999 and 2007.Results: There were 20,918 incident cases of prostate cancer between 1999 and 2007. The proportion of patients receiving androgen deprivation therapy decreased from 55% to 36%, and the proportion of patients receiving no active therapy increased from 16% to 23%. Intensity-modulated radiation therapy replaced three-dimensional conformal radiation therapy as the most common method of radiation therapy, accounting for 77% of external beam radiotherapy by 2007. Minimally invasive radical prostatectomy began to replace open surgical approaches, being used in 49% of radical prostatectomies by 2007.Conclusions: Between 2002 and 2007, the use of androgen deprivation therapy decreased, open surgical approaches were largely replaced by minimally invasive radical prostatectomy, and intensity-modulated radiation therapy replaced three-dimensional conformal radiation therapy as the predominant method of radiation therapy in the Medicare population. The aging of the population and the increasing use of newer, higher-cost technologies in the treatment of patients with prostate cancer may have important implications for nationwide health care costs. [ABSTRACT FROM AUTHOR]

The limitations of the explanatory clinical trial framework include the high expense of implementing explanatory trials, restrictive entry criteria for participants, and redundant logistical processes. These limitations can result in slow evidence generation that is not responsive to population health needs, yielding evidence that is not generalizable. Clinically integrated trials, which integrate clinical research into routine care, represent a potential solution to this challenge and an opportunity to support learning health systems. The operational and design features of clinically integrated trials include a focused scope, simplicity in design and requirements, the leveraging of existing data structures, and patient participation in the entire trial process. These features are designed to minimize barriers to participation and trial execution and reduce additional research burdens for participants and clinicians alike. Broad adoption and scalability of clinically integrated trials are dependent, in part, on continuing regulatory, healthcare system, and payer support. This analysis presents a framework of the strengths and challenges of clinically integrated trials and is based on a multidisciplinary expert "Think Tank" panel discussion that included representatives from patient populations, academia, non-profit funding agencies, the U.S. Food and Drug Administration, and industry., Competing Interests: Disclosures Dr. Peters is supported by the National Heart Lung and Blood Institute (T32HL069749) and has received honoraria from Cytokinetics. Dr. Jones has received grants from Bayer, Boehringer Ingelheim, and Merck. Dr. Broedl is an employee of Boehringer Ingelheim. Dr. Hornik received a research grant from Before Brands and consulting fees from SC Pharma. Dr. Knowlton received a salary from Intermountain Health Care. Dr. Krofah had leadership roles in Protas, the Reagan Udall Foundation, Clinical Trials Transformation Initiative (CTTI), Duke Margolis Center for Health Policy, Alliance for a Stronger FDA, Patient Focused Medicines Development (PFMD), and Medical Device Innovation Consortium (MDIC). Dr. Landray received grants from Janssen, FluLab, Schmidt Futures, Google Ventures, the National Institute for Health Research, UK Research & Innovation, Wellcome, and the Bill & Melinda Gates Foundation, as well as study drugs from Regeneron, Roche, AbbVie, and GSK. Dr. Rockhold received grants from the NIH, PCORI, BMS, AstraZeneca, American Regent, the Gates Foundation, and Eidos and consulting fees from Janssen, Clover, Doctor Evidence, and Intercept. He also participated on Data Safety Monitoring Boards for Lilly, AstraZeneca, Merck, Gilead, Novartis, Icosavax, Sanofi, UCB, Amgen, Biogen, BMS, Pulmocide, Alkermes, and Diurnal. He had an unpaid leadership role for the Frontier Science Foundation. He has stock or stock options for GSK, Clover, Athira, Doctor Evidence, DataVant, Spencer Health Solutions, and Adaptic Health. Dr. Roessig is a full-time employee of Bayer AG. Dr. Rothman has received grants from PCORI, the CDC, NIH, and AHRQ. Lesley Schofield is an employee of Novartis and has stock or stock options from Novartis. Dr. Tenaerts is an employee of Medable, Inc., and has a stock option grant with Medable, Inc. Dr. Tenaerts also received an honorarium for participation on a data monitoring committee., (Copyright © 2024. Published by Elsevier Inc.)

Importance: Pragmatic randomized clinical trials (RCTs) often use multiple data sources to examine clinical events, but the relative contribution of data sources to clinical end-point rates is understudied., Objective: To assess the contribution of data sources (electronic health records [EHRs], public/private insurance claims, and/or participant-reported data) to clinical end points among ADAPTABLE participants who had available data., Design, Setting, and Participants: The ADAPTABLE study was an open-label, pragmatic RCT from April 2016 through June 2019 conducted in research networks within clinical practice. Participants had existing atherosclerotic cardiovascular disease and available data to analyze. The characteristics of patients by combinations of data source availability were compared to examine the contribution of each of the data sources to end-point ascertainment. Data for this prespecified analysis were examined from January 2022 to June 2023., Exposures: Randomized exposure to 81 mg or 325 mg of aspirin daily., Main Outcomes and Measures: Number of events for the primary end point (composite of death, hospitalization for myocardial infarction, and hospitalization for stroke) that were contributed by EHR or claims data and then number of events contributed by each additional data source., Results: Of 15 006 participants randomized with at least 1 other source of data available beyond participant-reported data, there were 8756 (58.3%) with participant-reported and EHR data; 4291 (28.6%) with participant-reported, EHR, and claims data; 1412 (9.4%) with EHR-only data; 262 (1.7%) with participant-reported and claims data; 202 (1.3%) with EHR and claims data; and 83 (0.6%) with claims-only data. Participants with EHR-only data were younger (median age, 63.7 years; IQR, 55.8-71.4) compared with the other groups (range, 65.6-71.9 years). Among participants with both EHR and claims data, with or without participant-reported data (n = 4493), for each outcome, most events (92%-100%) were identified in the EHR or in claims data. For all clinical end points, participant-reported data contributed less than 10% of events not otherwise available from claims or EHR data., Conclusions and Relevance: In this analysis of a pragmatic RCT, claims and EHR data provided the most clinical end-point data when compared with participant-reported events. These findings provide a framework for collecting end points in pragmatic clinical trials. Further work is needed to understand the data source combinations that most effectively provide clinical end-point data in RCTs.

Importance: The US leads the world in bringing new medical products to market, but the ability to generate evidence to inform clinical practice in postmarket settings needs improvement. Although a diverse group of stakeholders is working to improve postmarket evidence generation, the role of private payers has been underappreciated., Observations: Payers are crucial allies in improving evidence generation because better data would better inform coverage decisions, their policies and practices influence the conduct of care and research, and their claims data are a source of real-world evidence used in medical product evaluation. In addition, payers have a stake in improving evidence generation because the kinds of evidence needed to inform health care and coverage decisions are often not available when a product enters the market and may not be generated without their involvement. Here, we describe several key steps payers could take to improve evidence generation, including participating in efforts to reduce administrative and financial barriers to the conduct of clinical trials, directly incentivizing evidence generation on high-priority questions by funding potential cost-saving trials, increasing engagement with the medical products industry on evidentiary needs for coverage decisions, and improving usability of claims data by reducing data lags and routinely recording unique device identifiers. Broad payer engagement with US Food and Drug Administration recommendations regarding evidence generation will ensure that the opportunities to participate in clinical research are extended to all communities and that evidence needed to inform care is generated in trials and surveillance systems that reflect the clinical reality across the US., Conclusions and Relevance: Increasing payer involvement in evidence generation can benefit all participants in the medical innovation ecosystem. The importance of payers in these efforts will continue to grow in response to imperatives to increase integration of care and research, engage a diverse set of communities in clinical research, and move toward alternative payment models.

The global pharmaceutical industry portfolio is skewed towards cancer and rare diseases due to more predictable development pathways and financial incentives. In contrast, drug development for major chronic health conditions that are responsible for a large part of mortality and disability worldwide is stalled. To examine the processes of novel drug development for common chronic health conditions, a multistakeholder Think Tank meeting, including thought leaders from academia, clinical practice, non-profit healthcare organizations, the pharmaceutical industry, the Food and Drug Administration (FDA), payors as well as investors, was convened in July 2022. Herein, we summarize the proceedings of this meeting, including an overview of the current state of drug development for chronic health conditions and key barriers that were identified. Six major action items were formulated to accelerate drug development for chronic diseases, with a focus on improving the efficiency of clinical trials and rapid implementation of evidence into clinical practice., Competing Interests: Conflict of interest Konstantin A. Krychtiuk: advisory boards Novartis, Sanofi, Amgen; speaker fees Amgen, Daichii Sankyo, Zoll Medical Tomas LG Andersson: employed by AstraZeneca, owns stock in AstraZeneca, travel support by AstraZeneca Ulrike Bodesheim employed by Bayer AG; Javed Butler: Consulting fees: 3ivelabs, Abbott, Amgen, American Regent, Applied Therapeutics, AstraZeneca, Bayer, Boehringer Ingelheim, Bristol Myers Squibb, Cardiac Dimension, Cardior, CVRx, Cytokinetics, Edwards, Element, Faraday, G3 Pharmaceutical, Imbria, Impulse Dynamics, Innolife, Inventiva, Ionis, Janssen, LivaNova, Lexicon, Medtronic, Merck, Novartis, Novo Nordisk, Otsuka, Occlutech, PharmaCosmos, Roche, Sanofi, Secretome, Sequana, Tricog, Vifor; Speaker Fees: Novartis, Boehringer Ingelheim-Lilly, Astra Zeneca, Impulse Dynamics; Lesley H Curtis: Fees Boehringer Ingleheim, NIH, and Regeneron Pharmaceuticals Mitchell Elkind: Grants: Roche; Lecture Fees: Atria Academy of Science and Medicine; Travel Support: American Heart Association; Adrian F. Hernandez: Consulting fees Amgen, AstraZeneca, Bayer, Boehringer Ingelheim, Boston Scientific, CSL Behring, Cytokinetics, Eli Lilly, Intellia Therapeutics, Merck, Novartis, Novo Nordisk, Prolaio; Grants/Contracts: American Regent, AstraZeneca, Bayer, Boehringer Ingelheim, Intellia Therapeutics, Merck, Novartis, Novo Nordisk, Verily; Christoph Hornik: None declared; Gary H Lyman: Consulting Fees: Sandoz, Astra Zeneca, Beyond Spring, G1 Therapeutics, Merck, Partners Healthcare, ER Squibb, Samsung, Fresenius Kabi; Pooja Khatri: grants from Cerenovus; serving on the scientific advisory boards of Lumosa; Shionogi, Bayer, and Basking Biosciences; andreceiving online publication royalties from UpToDate; Michael Mbagwu: Stocks in Verana Health as employee Masahiro Murakami: employed by Eli Lilly; Gwen Nichols: None declared; Lothar Roessig: employed by Bayer; Anne Quinn Young: None declared; Richard L. Schilsky Consulting Fees: Cellworks, EQRx, Zephyr AI, Clarified Precision Medicine, Illumina, Member, DSMB, Baseline Study sponsored by Verily Chairman, Scientific Advisory Board, Ontario Institute for Cancer Research Member, Strategic External Advisory Committee for Canadian Cancer Trials Group Chairman, Board of Directors, Reagan-Udall Foundation for the FDA, Member, Board of Directors, Friends of Cancer Research, Member, Board of Directors, Leap Therapeutics; Neha Pagidipati: Research support from Alnylam, Amgen, Boehringer Ingelheim, Eggland's Best, Eli Lilly, Novartis, Novo Nordisk, Verily Life Sciences; Consultation/Advisory Panels for Bayer, Boehringer Ingelheim, CRISPR Therapeutics, Eli Lilly, Esperion, AstraZeneca, Merck, Novartis, and Novo Nordisk; Executive Committee member for trials sponsored by Novo Nordisk and by Amgen; DSMB for trials sponsored by J+J and Novartis; Medical advisory board for Miga Health., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Several years ago, the US News and World Report changed their risk-adjustment methodology, now relying almost exclusively on chronic conditions for risk adjustment. The impacts of adding selected acute conditions like pneumonia, sepsis, and electrolyte disorders ("augmented") to their current risk models ("base") for 4 specialties-cardiology, neurology, oncology, and pulmonology-on estimates of hospital performance are reported here. In the augmented models, many acute conditions were associated with substantial risks of mortality. Compared to the base models, the discrimination and calibration of the augmented models for all specialties were improved. While estimated hospital performance was highly correlated between the 2 models, the inclusion of acute conditions in risk-adjustment models meaningfully improved the predictive ability of those models and had noticeable effects on hospital performance estimates. Measures or conditions that address disease severity should always be included when risk-adjusting hospitalization outcomes, especially if the goal is provider profiling., (Copyright © The Authors 2024.)

While the coronavirus disease 2019 (COVID-19) pandemic continues to present global challenges, sufficient time has passed to reflect on lessons learned and use those insights to inform policy and approaches to prepare for the next pandemic. In May 2022, the Duke Clinical Research Institute convened a think tank with thought leaders from academia, clinical practice, the pharmaceutical industry, patient advocacy, the National Institutes of Health, the US Food and Drug Administration, and the Centers for Disease Control and Prevention to share, firsthand, expert knowledge of the insights gained from the COVID-19 pandemic and how this acquired knowledge can help inform the next pandemic response. The think tank focused on pandemic preparedness, therapeutics, vaccines, and challenges related to clinical trial design and scale-up during the early phase of a pandemic. Based on the multi-faceted discussions, we outline 10 key steps to an improved and equitable pandemic response., Competing Interests: Potential conflicts of interest. A. F. H. reports contracts with Pfizer and Merck and consulting fees from Merck. B. L. is an employee of and owns stock in Moderna and reports support for travel to a meeting from Moderna. C. W. W. reports consulting fees from Arena Pharmaceuticals, BioFire, FHI Clinical, Giner, Karius, and SeLux Diagnostics; grants or contracts (paid to institution) from Defense Advanced Research Projects Agency, National Institutes of Health (NIH)-Antibacterial Resistance Leadership Group/National Institute of Allergy and Infectious Diseases/NIH Vaccine and Treatment Evaluation Units/National Institute of Mental Health/National Institute of General Medical Sciences, Sanofi, Najit, the Centers for Disease Control and Prevention (CDC), Patient-Centered Outcomes Research, United States Army Medical Research Acquisition Activity, Department of Defence, Abbott, and Pfizer; support for attending meetings and/or travel from the American Society for Microbiology (ASM); participation on a data and safety monitoring board (DSMB) or advisory board for IDbyDNA, Janssen, Regeneron, Roche Molecular Sciences; a leadership or fiduciary role for ASM and the American Society of Tropical Medicine and Hygiene; being employed by Duke University, Durham Veterans Affairs Hospital, Biomeme, and Equity/Founder of Predigen, Inc; and planned, issued, or pending patents for biomarkers for the molecular classification of bacterial infection, methods to diagnose and treat acute respiratory infections, gene expression signatures useful to predict or diagnose sepsis and methods of using the same, host-based molecular signatures of human infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2 (coronavirus disease 2019 [COVID-19]), methods of identifying infectious disease and assays for identifying infectious disease, and nasopharyngeal protein biomarkers of acute respiratory virus infection and methods of using same. H. C. and S. C. B. are employees of and hold or may hold stock in AstraZeneca. J. W. reports being an employee of and owns stock/stock options in and received equipment, materials, drugs, medical writing, gifts, and other services from Johnson & Johnson and, as CMO, has been deposed in litigation; patents issued that do not relate to the current article (available on request); and a role on the Brooklyn College Cancer Center Advisory Board, a Brooklyn College Foundation Trustee, and on the Fellowships at Auschwitz for the Study of Professional Ethics, Academic Committee. J. R. D. is an employee and shareholder in Eli Lilly and Company. L. H. C. reports consulting fees from Regeneron for the NFL Players Association and grants or contracts from NIH for PCORI. L. S. reports stock/stock options in Novartis. L. R. is an employee of and owns stock/stock options in and received support for attending meetings and/or travel from Bayer AG. M. S. reports consulting fees from AbbVie, Assembly Bio, Antios, Arbutus, Gilead Sciences, Precision Bio, and GSK for scientific advisory boards and participation on a DSMB for Gilead Sciences and AbbVie and a role as editor of the Journal Viral Hepatitis. O. V. is an employee of Boehringer Ingelheim. P. P. has a patent pending for sotrovimab and is an employee and shareholder of Vir Biotechnology. S. N. reports consulting fees from Pardes Biosciences, Theratechnologies, and Silverback Therapeutics; stock/stock options in Vir Biotechnology; grants or contracts (paid to institution) from Gilead Sciences and AbbVie; participation on an advisory board for Vir Biotechnology, a DSMB for Personal Health Insights, Inc; and serving on an event adjudication committee for Bristol–Myers Squibb/PRA. M. A. M. reports consulting fees from Abcam; stock/stock options in Grid Therapeutics; a role as an advisory board member for GSK Belimumab Pregnancy Registry; and funding to Duke from NIAD (U01 AI151378): Centers for Research in Emerging Infectious Disease (CREID) Network Coordinating Center, HHS 75N93019C00050: Duke Collaborative Influenza Vaccine Innovation Centers (CIVICs) A: Vaccine Center, HHS 75N93019C00054: Duke CIVICs C: Clinical Core, U19 AI144177: A Global Syphilis Vaccine Targeting Outer Membrane Proteins Of Treponema pallidum, 2P01 AI089618: Structure-Function Analysis Of Infection- And Vaccine-Induced B Cell Repertoires. S. E. T. reports royalties from UptoDate; grants or contracts (paid to institution) from the CDC; payment or honoraria (to author) from the Infectious Disease Society of America (IDSA) and Emerson Hospital; support from DCRI to attend the meeting upon which this article was based. L. R. B. is involved in human immunodeficiency virus (HIV) and SARS-CoV-2 vaccine clinical trials conducted in collaboration with the NIH, HIV Vaccine Trials Network, COVID Vaccine Prevention Network, International AIDS Vaccine Initiative, Crucell/Janssen, Moderna, Military HIV Research Program, the Gates Foundation, and Harvard Medical School. reports participation on a DSMB for NIH and AMDAC Committee for the FDA (research funded by the NIH, Welcome Trust, and the Gates Foundation). R. T. G. reports a leadership or fiduciary role on the NIH COVID Treatment Guidelines Panel and IDSA COVID Treatment Guidelines Panel. R. G. reports grants (to institution) from NIH/NIAID, book chapter royalties from Elsevier, and section editor royalties from UpToDate. All remaining authors: No reported conflicts of interest. 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) 2023. Published by Oxford University Press on behalf of Infectious Diseases Society of America.)

Translational research is a data-driven process that involves transforming scientific laboratory- and clinic-based discoveries into products and activities with real-world impact to improve individual and population health. Successful execution of translational research requires collaboration between clinical and translational science researchers, who have expertise in a wide variety of domains across the field of medicine, and qualitative and quantitative scientists, who have specialized methodologic expertise across diverse methodologic domains. While many institutions are working to build networks of these specialists, a formalized process is needed to help researchers navigate the network to find the best match and to track the navigation process to evaluate an institution's unmet collaborative needs. In 2018, a novel analytic resource navigation process was developed at Duke University to connect potential collaborators, leverage resources, and foster a community of researchers and scientists. This analytic resource navigation process can be readily adopted by other academic medical centers. The process relies on navigators with broad qualitative and quantitative methodologic knowledge, strong communication and leadership skills, and extensive collaborative experience. The essential elements of the analytic resource navigation process are as follows: (1) strong institutional knowledge of methodologic expertise and access to analytic resources, (2) deep understanding of research needs and methodologic expertise, (3) education of researchers on the role of qualitative and quantitative scientists in the research project, and (4) ongoing evaluation of the analytic resource navigation process to inform improvements. Navigators help researchers determine the type of expertise needed, search the institution to find potential collaborators with that expertise, and document the process to evaluate unmet needs. Although the navigation process can create a basis for an effective solution, some challenges remain, such as having resources to train navigators, comprehensively identifying all potential collaborators, and keeping updated information about resources as methodologists join and leave the institution., (Copyright © 2023 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the Association of American Medical Colleges.)

Real-world data (RWD)-derived external controls can be used to contextualize efficacy findings for investigational therapies evaluated in uncontrolled trials. As the number of submissions to regulatory and health technology assessment (HTA) bodies using external controls rises, and in light of recent regulatory and HTA guidance on the appropriate use of RWD, there is a need to address the operational and methodological challenges impeding the quality of real-world evidence (RWE) generation and the consistency in evaluation of RWE across agencies. This systematic review summarizes publicly available information on the use of external controls to contextualize outcomes from uncontrolled trials for all indications from January 1, 2015, through August 20, 2021, that were submitted to the European Medicines Agency, the US Food and Drug Administration, and/or select major HTA bodies (National Institute for Health and Care Excellence (NICE), Haute Autorité de Santé (HAS), Institut für Qualität und Wirtschaftlichkeit im Gesundheitswesen (IQWiG), and Gemeinsamer Bundesausschuss (G-BA)). By systematically reviewing submissions to regulatory and HTA bodies in the context of recent guidance, this study provides quantitative and qualitative insights into how external control design and analytic choices may be viewed by different agencies in practice. The primary operational and methodological aspects identified for discussion include, but are not limited to, engagement of regulators and HTA bodies, approaches to handling missing data (a component of data quality), and selection of real-world endpoints. Continued collaboration and guidance to address these and other aspects will inform and assist stakeholders attempting to generate evidence using external controls., (© 2023 Regeneron Pharmaceuticals Inc and The Authors. Clinical Pharmacology & Therapeutics published by Wiley Periodicals LLC on behalf of American Society for Clinical Pharmacology and Therapeutics.)

Regulators and Health Technology Assessment (HTA) bodies are increasingly familiar with, and publishing guidance on, external controls derived from real-world data (RWD) to generate real-world evidence (RWE). We recently conducted a systematic literature review (SLR) evaluating publicly available information on the use of RWD-derived external controls to contextualize outcomes from uncontrolled trials submitted to the European Medicines Agency (EMA), the US Food and Drug Administration (FDA), and/or select HTA bodies. The review identified several key operational and methodological aspects for which more detailed guidance and alignment within and between regulatory agencies and HTA bodies is necessary. This paper builds on the SLR findings by delineating a set of key takeaways for the responsible generation of fit-for-purpose RWE. Practical methodological and operational guidelines for designing, conducting, and reporting RWD-derived external control studies are explored and discussed. These considerations include: (i) early engagement with regulators and HTA bodies during the study planning phase; (ii) consideration of the appropriateness and comparability of external controls across multiple dimensions, including eligibility criteria, temporality, population representation, and clinical evaluation; (iii) ensuring adequate sample sizes, including hypothesis testing considerations; (iv) implementation of a clear and transparent strategy for assessing and addressing data quality, including data missingness across trials and RWD; (v) selection of comparable and meaningful endpoints that are operationalized and analyzed using appropriate analytic methods; and (vi) conduct of sensitivity analyses to assess the robustness of findings in the context of uncertainty and sources of potential bias., (© 2023 Regeneron Pharmaceuticals Inc and The Authors. Clinical Pharmacology & Therapeutics published by Wiley Periodicals LLC on behalf of American Society for Clinical Pharmacology and Therapeutics.)

Importance: Patient-reported health data can facilitate clinical event capture in pragmatic clinical trials. However, few data are available on the fitness for use of patient-reported data in large-scale health research., Objective: To evaluate the concordance of a set of variables reported by patients and available in the electronic health record as part of a pragmatic clinical trial., Design, Setting, and Participants: Data from ADAPTABLE (Aspirin Dosing: A Patient-Centric Trial Assessing Benefits and Long-term Effectiveness), a pragmatic clinical trial, were used in a concordance substudy of a comparative effectiveness research trial. The trial randomized 15 076 patients with existing atherosclerotic cardiovascular disease in a 1:1 ratio to low- or high-dose aspirin from April 2016 through June 30, 2019., Main Outcomes and Measures: Concordance of data was evaluated from 4 domains (demographic characteristics, encounters, diagnoses, and procedures) present in 2 data sources: patient-reported data captured through an online portal and data from electronic sources (electronic health record data). Overall agreement, sensitivity, specificity, positive predictive value, negative predictive value, and κ statistics with 95% CIs were calculated using patient report as the criterion standard for demographic characteristics and the electronic health record as the criterion standard for clinical outcomes., Results: Of 15 076 patients with complete information, the median age was 67.6 years (range, 21-99 years), and 68.7% were male. With the use of patient-reported data as the criterion standard, agreement (κ) was high for Black and White race and ethnicity but only moderate for current smoking status. Electronic health record data were highly specific (99.6%) but less sensitive (82.5%) for Hispanic ethnicity. Compared with electronic health record data, patient report of clinical end points had low sensitivity for myocardial infarction (33.0%), stroke (34.2%), and major bleeding (36.6%). Positive predictive value was similarly low for myocardial infarction (40.7%), stroke (38.8%), and major bleeding (21.9%). Coronary revascularization was the most concordant event by data source, with only moderate agreement (κ = 0.54) and positive predictive value. Agreement metrics varied by site for all demographic characteristics and several clinical events., Conclusions and Relevance: In a concordance substudy of a large, pragmatic comparative effectiveness research trial, sensitivity and chance-corrected agreement of patient-reported data captured through an online portal for cardiovascular events were low to moderate. Findings suggest that additional work is needed to optimize integration of patient-reported health data into pragmatic research studies., Trial Registration: ClinicalTrials.gov Identifier: NCT02697916.

Background: Despite the extensive use of real-world data for retrospective, observational clinical research, our understanding of how real-world data might increase the efficiency of data collection in patient-level randomized clinical trials is largely unknown. The structure of real-world data is inherently heterogeneous, with each source electronic health record and claims database different from the next. Their fitness-for-use as data sources for multisite trials in the United States has not been established., Methods: For a subset of participants in the HARMONY Outcomes Trial, we obtained electronic health record data from recruiting sites or Medicare claims data from the Centers for Medicare & Medicaid Services. For baseline characteristics and follow-up events, we assessed the level of agreement between these real-world data and data documented in the trial database., Results: Real-world data-derived demographic information tended to agree with trial-reported demographic information, although real-world data were less accurate in identifying medical history. The ability of real-world data to identify baseline medication usage differed by real-world data source, with claims data demonstrating substantially better performance than electronic health record data. The limited number of lab results in the collected electronic health record data matched closely with values in the trial database. There were not enough follow-up events in the ancillary study population to draw meaningful conclusions about the performance of real-world data for identification of events. Based on the conduct of this ancillary study, the challenges and opportunities of using real-world data within clinical trials are discussed., Conclusion: Based on a subset of participants from the HARMONY Outcomes Trial, our results suggest that electronic health record or claims data, as currently available, are unlikely to be a complete substitute for trial data collection of medical history or baseline lab results, but that Medicare claims were able to identify most medications. The limited size of the study population prevents us from drawing strong conclusions based on these results, and other studies are clearly needed to confirm or refute these findings.

Background: The COVID-19 pandemic has considerably disrupted nearly all aspects of daily life, including healthcare delivery and clinical research. Because pragmatic clinical trials are often embedded within healthcare delivery systems, they may be at high risk of disruption due to the dual impacts on the conduct of both care and research., Methods: We collected qualitative data using multiple methods to characterize the impact of COVID-19 on the research activities of 14 active pragmatic clinical trials in the National Institutes of Health (NIH) Health Care Systems Research Collaboratory. A COVID-19 impact questionnaire was administered electronically to principal investigators in June 2020. Text responses were analyzed thematically, and qualitative summaries were subsequently reviewed by five independent reviewers, who made iterative revisions. Additional COVID-19-related impacts were identified during virtual meetings with trial teams during April-July 2020 and combined with questionnaire responses for analysis., Results: Impacts of the pandemic were broadly classified into two main types: healthcare operations and social distancing. In some instances, trial delays created statistical challenges, particularly with trials using stepped-wedge designs, and necessitated changing data collection strategies or modifying interventions. The majority of projects used existing stakeholder-driven approaches to adapt interventions. Several benefits of these adaptions were identified, including expanded outreach capabilities and ability to study virtual intervention delivery. All trial teams were able to adapt to pandemic-related modifications., Conclusion: In a group of 14 ongoing pragmatic clinical trials, there was significant impact of COVID-19 on trial activities. Engaging appropriate stakeholders was critical to designing and implementing trial modifications and making continued safe progress toward meeting research objectives., (© 2022. The Author(s).)

Background: Improving diversity in clinical trials is essential in order to produce generalizable results. Although the importance of representation has become increasingly recognized, identifying strategies to approach this work remains elusive. This article reviews the proceedings of a multi-stakeholder conference about the current state of diversity in clinical trials and outlines actionable steps for improvement., Methods: Conference attendees included representatives from the United States Food and Drug Administration (FDA), National Institutes of Health (NIH), practicing clinical investigators, pharmaceutical and device companies, community-based organizations, data analytics companies, and patient advocacy groups. At this virtual event, attendees were asked to consider key questions around best practices for engagement of underrepresented populations., Results: Community engagement is an integral part of recruitment and retention of underrepresented groups. Decentralization of sites and use of digital tools can enhance the accessibility of clinical research. Finally, improving representation among investigators and clinical research staff may translate to diverse clinical trial participants., Conclusion: Improving diversity in clinical trials is an ethical and scientific imperative, which requires a multifaceted approach., (Copyright © 2022 Elsevier Inc. All rights reserved.)

Objective: To empirically explore how pragmatic clinical trials (PCTs) that used real-world data (RWD) assessed study-specific fitness-for-use., Methods: We conducted interviews and surveys with PCT teams who used electronic health record (EHR) data to ascertain endpoints. The survey cataloged key concerns about RWD, activities used to assess data fitness-for-use, and related barriers encountered by study teams. Patterns and commonalities across trials were used to develop recommendations for study-specific fitness-for-use assessments., Results: Of 15 invited trial teams, 7 interviews were conducted. Of 31 invited trials, 15 responded to the survey. Most respondents had prior experience using RWD (93%). Major concerns about EHR data were data reliability, missingness or incompleteness of EHR elements, variation in data quality across study sites, and presence of implausible or incorrect values. Although many PCTs conducted fitness-for-use activities (eg, data quality assessments, 11/14, 79%), less than a quarter did so before choosing a data source. Fitness-for-use activities, findings, and resulting study design changes were not often publically documented. Overall costs and personnel costs were barriers to fitness-for-use assessments., Discussion: These results support three recommendations for PCTs that use EHR data for endpoint ascertainment. Trials should detail the rationale and plan for study-specific fitness-for-use activities, conduct study-specific fitness-for-use assessments early in the prestudy phase to inform study design changes before the trial begins, and share results of fitness-for-use assessments and description of relevant challenges and facilitators., Conclusion: These recommendations can help researchers and end-users of real-world evidence improve characterization of RWD reliability and relevance in the PCT-specific context., (© The Author(s) 2022. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Background: Understanding the relationship between patterns of peripheral artery disease and outcomes is an essential step toward improving care and outcomes. We hypothesized that clinician specialty would be associated with occurrence of major adverse vascular events (MAVE)., Methods: Patients with at least 1 peripheral artery disease-related encounter in our health system and fee-for-service Medicare were divided into groups based on the specialty of the clinician (ie, cardiologist, surgeon, podiatrist, primary care, or other) providing a plurality of peripheral artery disease-coded care in the year prior to index encounter. The primary outcome was MAVE (a composite of all-cause mortality, myocardial infarction, stroke, lower extremity revascularization, and lower extremity amputation)., Results: The cohort included 1768 patients, of whom 30.0% were Black, 23.9% were Medicaid dual-enrollment eligible, and 31.1% lived in rural areas. Patients receiving a plurality of their care from podiatrists had the highest 1-year rates of MAVE (34.4%, P <.001), hospitalization (65.9%, P <.001), and amputations (22.6%, P <.001). Clinician specialty was not associated with outcomes after adjustment. Patients who were Medicaid dual-eligible had higher adjusted risks of mortality (adjusted hazard ratio [HR adj ] 1.54, 95% confidence interval [CI] 1.11-2.14) and all-cause hospitalization (HR adj 1.20, 95% CI 1.03-1.40) and patients who were Black had a higher adjusted risk of amputation (HR adj 1.49, 95% CI 1.03-2.15)., Conclusions: Clinician specialty was not associated with worse outcomes after adjustment, but certain socioeconomic factors were. The effects of clinician specialty and socioeconomic status were likely attenuated by the fact that all patients in this study had health insurance; these analyses require confirmation in a more representative cohort., (Copyright © 2021 Elsevier Inc. All rights reserved.)

The Sentinel System is a major component of the United States Food and Drug Administration's (FDA) approach to active medical product safety surveillance. While Sentinel has historically relied on large quantities of health insurance claims data, leveraging longitudinal electronic health records (EHRs) that contain more detailed clinical information, as structured and unstructured features, may address some of the current gaps in capabilities. We identify key challenges when using EHR data to investigate medical product safety in a scalable and accelerated way, outline potential solutions, and describe the Sentinel Innovation Center's initiatives to put solutions into practice by expanding and strengthening the existing system with a query-ready, large-scale data infrastructure of linked EHR and claims data. We describe our initiatives in four strategic priority areas: (1) data infrastructure, (2) feature engineering, (3) causal inference, and (4) detection analytics, with the goal of incorporating emerging data science innovations to maximize the utility of EHR data for medical product safety surveillance., (© 2021. The Author(s).)

Background: Individuals with chronic kidney disease (CKD), hypertension (HTN), or diabetes mellitus (DM) are at increased risk for cardiovascular disease (CVD). The extent to which psychosocial factors are associated with increased CVD risk within these individuals is unclear. Black individuals experience a high degree of psychosocial stressors due to socioeconomic factors, environment, racism, and discrimination. We examined the association between psychosocial factors and risk of CVD events among Black men and women with CKD and CKD risk factors in the Jackson Heart Study., Methods and Results: We identified 1919 participants with prevalent CKD or CKD risk factors at baseline. We used rotated principal component analysis - a form of unsupervised machine learning that may identify constructs not intuitively identified by a person - to describe five groups of psychosocial components (including negative moods, religiosity, discrimination, negative outlooks, and negative coping resources) based on a battery of questionnaires. Multiple imputation by chained equation (MICE) was used to impute missing covariate data. Cox models were used to quantify the association between psychosocial components and incident CVD, defined as a fatal coronary heart disease event, myocardial infarction, cardiac procedure (angiography or revascularization procedure), or stroke. Of the 929 participants in the analysis, 67% were female, 28% were current/former smokers with mean age of 56 years and mean BMI of 33 kg/m 2 . Over a median follow-up of 8 years, 6% had an incident CVD event. In multivariable models, each standard deviation (SD) increase in the religiosity component was associated with an increased hazard for CVD event (hazard ratio [HR] = 1.52, 95% CI: 1.09-2.13)., Conclusions: Religiosity was associated with CVD among participants with prevalent CKD or CKD risk factors. Studies to better understand the mechanisms of this relationship are needed., (© 2021. The Author(s).)

Background: PAD increases the risk of cardiovascular mortality and limb loss, and disparities in treatment and outcomes have been described. However, the association of patient-specific characteristics with variation in outcomes is less well known., Methods: Patients with PAD from Duke University Health System (DUHS) between January 1, 2015 and March 31, 2016 were identified. PAD status was confirmed through ground truth adjudication and predictive modeling using diagnosis codes, procedure codes, and other administrative data. Symptom severity, lower extremity imaging, and ankle-brachial index (ABI) were manually abstracted from the electronic health record (EHR). Data was linked to Centers for Medicare and Medicaid Services data to provide longitudinal follow up. Primary outcome was major adverse vascular events (MAVE), a composite of all-cause mortality, myocardial infarction (MI), stroke, lower extremity revascularization and amputation., Results: Of 1,768 patients with PAD, 31.6% were asymptomatic, 41.2% had intermittent claudication (IC), and 27.3% had chronic limb-threatening ischemia (CLTI). At 1 year, patients with CLTI had higher rates of MAVE compared with asymptomatic or IC patients. CLTI and Medicaid dual eligibility were independent predictors of mortality. CLTI and Black race were associated with amputation., Conclusions: Rates of MAVE were highest in patients with CLTI, but patients with IC or asymptomatic disease also had high rates of adverse events. Black and Medicaid dual-eligible patients were disproportionately present in the CLTI subgroup and were at higher risk of amputation and mortality, respectively. Future studies must focus on early identification of high-risk patient groups to improve outcomes in patients with PAD., (Copyright © 2021. Published by Elsevier Inc.)

Background Sacubitril/Valsartan has been highly efficacious in randomized trials of heart failure with reduced ejection fraction (HFrEF). However, the effectiveness of sacubitril/valsartan in older patients hospitalized for HFrEF in real-world US practice is unclear. Methods and Results This study included Medicare beneficiaries age ≥65 years who were hospitalized for HFrEF ≤40% in the Get With The Guidelines-Heart Failure registry between October 2015 and December 2018, and eligible for sacubitril/valsartan. Associations between discharge prescription of sacubitril/valsartan and clinical outcomes were assessed after inverse probability of treatment weighting and adjustment for other HFrEF medications. Overall, 1551 (10.9%) patients were discharged on sacubitril/valsartan. Of those not prescribed sacubitril/valsartan, 7857 (62.0%) were prescribed an angiotensin-converting enzyme inhibitor/angiotensin II receptor blocker. Over 12-month follow-up, compared with a discharge prescription of angiotensin-converting enzyme inhibitor/angiotensin II receptor blocker, sacubitril/valsartan was independently associated with lower all-cause mortality (adjusted hazard ratio [HR], 0.82; 95% CI, 0.72-0.94; P =0.004) but not all-cause hospitalization (adjusted HR, 0.97; 95% CI, 0.89-1.07; P =0.55) or heart failure hospitalization (adjusted HR, 1.04; 95% CI, 0.91-1.18; P =0.59). Patients prescribed sacubitril/valsartan versus those without a prescription had lower risk of all-cause mortality (adjusted HR, 0.69; 95% CI, 0.60-0.79; P <0.001), all-cause hospitalization (adjusted HR, 0.90; 95% CI, 0.82-0.98; P =0.02), but not heart failure hospitalization (adjusted HR, 0.94; 95% CI, 0.82-1.08; P =0.40). Conclusions Among patients hospitalized for HFrEF, prescription of sacubitril/valsartan at discharge was independently associated with reduced postdischarge mortality compared with angiotensin-converting enzyme inhibitor/angiotensin II receptor blocker, and reduced mortality and all-cause hospitalization compared with no sacubitril/valsartan. These findings support the use of sacubitril/valsartan to improve postdischarge outcomes among older patients hospitalized for HFrEF in routine US clinical practice.

Background: The electronic health record (EHR) contains a wealth of clinical data that may be used to streamline the identification of potential clinical trial participants. However, there is little empirical information on site-level facilitators of and barriers to optimal use of EHR systems with respect to trial recruitment., Methods: We conducted qualitative focus groups and quantitative surveys as part of the EHR Ancillary Study, which is being conducted alongside the multicenter, global, Harmony Outcomes Trial comparing albiglutide to standard care for the prevention of cardiovascular events in type 2 diabetes. Subject matter experts used findings from focus groups to draft a 20-question survey examining the use of the EHR for participant identification, common site recruitment strategies, and variation in perceived barriers to optimal use of the EHR. The final survey was fielded with 446 site investigators actively enrolling participants in the main trial., Results: Nearly two-thirds of respondents were study coordinators (63.2%), 23.1% were principal investigators, and 13.7% held other research roles. Approximately half of the respondents reported using the EHR to find potential trial participants. Of these, 79.4% reported using EHR searches in conjunction with other recruitment methods, including reviewing of upcoming clinic schedules (75.3%) and contacting past trial participants (71.2%). Important barriers to optimal use of the EHR included the lack of availability of certain research-focused EHR modules and limitations on the ability to contact patients cared for by other providers. Of survey respondents who did not use the EHR to find potential participants, one-quarter reported that the EHR was not accessible in their country; this finding varied from 2.6% of respondents in North America to 50% of respondents in the Asia Pacific., Conclusions: While EHR screening was commonly used for recruitment in a cardiovascular outcomes trial, important technical, governance, and regulatory barriers persist. Multifaceted, scalable, and customizable strategies are needed to support the optimal use of the EHR for trial participant identification., Trial Registration: ClinicalTrials.gov NCT02465515. Registered on 8 June 2015., (© 2021. The Author(s).)

Introduction: In the 2016 U.S. Presidential election, voters in communities with recent stagnation or decline in life expectancy were more likely to vote for the Republican candidate than in prior Presidential elections. We aimed to assess the association between change in life expectancy and voting patterns in the 2020 Presidential election., Methods: With data on county-level life expectancy from the Institute for Health Metrics and Evaluation and voting data from a GitHub repository of results scraped from news outlets, we used weighted multivariable linear regression to estimate the association between the change in life expectancy from 1980 to 2014 and the proportion of votes for the Republican candidate and change in the proportion of votes cast for the Republican candidate in the 2020 Presidential election., Results: Among 3110 U.S counties and Washington, D.C., change in life expectancy at the county level was negatively associated with Republican share of the vote in the 2020 Presidential election (parameter estimate -7.2, 95% confidence interval, -7.8 to -6.6). With the inclusion of state, sociodemographic, and economic variables in the model, the association was attenuated (parameter estimate -0.8; 95% CI, -1.5 to -0.2). County-level change in life expectancy was positively associated with change in Republican vote share 0.29 percentage points (95% CI, 0.23 to 0.36). The association was attenuated when state, sociodemographic, and economic variables were added (parameter estimate 0.24; 95% CI, 0.15 to 0.33)., Conclusion: Counties with a less positive trajectory in life expectancy were more likely to vote for the Republican candidate in the 2020 U.S. Presidential election, but the Republican candidate's share improved in some counties that experienced marked gains in life expectancy. Associations were moderated by demographic, social and economic factors., Competing Interests: LC, MN and BH declare no conflicts of interest. RMC reports employment from Google Health and Verily Life Sciences and Corporate Board for Cytokinetics and Centessa with payment and stock., (© 2021 Published by Elsevier Ltd.)

Background: The appropriate dose of aspirin to lower the risk of death, myocardial infarction, and stroke and to minimize major bleeding in patients with established atherosclerotic cardiovascular disease is a subject of controversy., Methods: Using an open-label, pragmatic design, we randomly assigned patients with established atherosclerotic cardiovascular disease to a strategy of 81 mg or 325 mg of aspirin per day. The primary effectiveness outcome was a composite of death from any cause, hospitalization for myocardial infarction, or hospitalization for stroke, assessed in a time-to-event analysis. The primary safety outcome was hospitalization for major bleeding, also assessed in a time-to-event analysis., Results: A total of 15,076 patients were followed for a median of 26.2 months (interquartile range [IQR], 19.0 to 34.9). Before randomization, 13,537 (96.0% of those with available information on previous aspirin use) were already taking aspirin, and 85.3% of these patients were previously taking 81 mg of daily aspirin. Death, hospitalization for myocardial infarction, or hospitalization for stroke occurred in 590 patients (estimated percentage, 7.28%) in the 81-mg group and 569 patients (estimated percentage, 7.51%) in the 325-mg group (hazard ratio, 1.02; 95% confidence interval [CI], 0.91 to 1.14). Hospitalization for major bleeding occurred in 53 patients (estimated percentage, 0.63%) in the 81-mg group and 44 patients (estimated percentage, 0.60%) in the 325-mg group (hazard ratio, 1.18; 95% CI, 0.79 to 1.77). Patients assigned to 325 mg had a higher incidence of dose switching than those assigned to 81 mg (41.6% vs. 7.1%) and fewer median days of exposure to the assigned dose (434 days [IQR, 139 to 737] vs. 650 days [IQR, 415 to 922])., Conclusions: In this pragmatic trial involving patients with established cardiovascular disease, there was substantial dose switching to 81 mg of daily aspirin and no significant differences in cardiovascular events or major bleeding between patients assigned to 81 mg and those assigned to 325 mg of aspirin daily. (Funded by the Patient-Centered Outcomes Research Institute; ADAPTABLE ClinicalTrials.gov number, NCT02697916.)., (Copyright © 2021 Massachusetts Medical Society.)

Introduction: Transfusion-related acute lung injury (TRALI), an adverse event occurring during or within 6 hours of transfusion, is a leading cause of transfusion-associated fatalities reported to the US Food and Drug Administration. There is limited information on the validity of diagnosis codes for TRALI recorded in inpatient electronic medical records (EMRs)., Study Designs and Methods: We conducted a validation study to establish the positive predictive value (PPV) of TRALI International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) diagnosis codes recorded within a large hospital system between 2013 and 2015. A physician with critical care expertise confirmed the TRALI diagnosis. As TRALI is likely underdiagnosed, we used the specific code (518.7), and codes for respiratory failure (518.82) in combination with transfusion reaction (999.80, 999.89, E934.7)., Results: Among almost four million inpatient stays, we identified 208 potential TRALI cases with ICD-9-CM codes and reviewed 195 medical records; 68 (35%) met clinical definitions for TRALI (26 [38%] definitive, 15 [22%] possible, 27 [40%] delayed). Overall, the PPV for all inpatient TRALI diagnoses was 35% (95% confidence interval (CI), 28-42). The PPV for the TRALI-specific code was 44% (95% CI, 35-54)., Conclusion: We observed low PPVs (<50%) for TRALI ICD-9-CM diagnosis codes as validated by medical charts, which may relate to inconsistent code use, incomplete medical records, or other factors. Future studies using TRALI diagnosis codes in EMR databases may consider confirming diagnoses with medical records, assessing TRALI ICD, Tenth Revision, Clinical Modification codes, or exploring alternative ways for of accurately identifying TRALI in EMR databases., Key Points: In 169 hospitals, we identified 208 potential TRALI cases, reviewed 195 charts, and confirmed 68 (35%) cases met TRALI clinical definitions. As many potential TRALI cases identified with diagnosis codes did not meet clinical definitions, medical record confirmation may be prudent., (© 2021 AABB.)