Patterns of platelet use evaluated in EHR networks of the Biologics Effectiveness and Safety Initiative, 2012-2018.

Background: U.S. FDA's Center for Biologics Evaluation and Research (CBER) Biologics Effectiveness and Safety (BEST) Initiative leverages large electronic health records and administrative claims data to conduct active surveillance for CBER-regulated products.

Respiratory syncytial virus (RSV) vaccine effectiveness against RSV-associated hospitalisations and emergency department encounters among adults aged 60 years and older in the USA, October, 2023, to March, 2024: a test-negative design analysis.

Background: Respiratory syncytial virus vaccines first recommended for use during 2023 were efficacious against lower respiratory tract disease in clinical trials. Limited real-world data regarding respiratory syncytial virus vaccine effectiveness are available. To inform vaccine policy and address gaps in evidence from the clinical trials, we aimed to assess the effectiveness against respiratory syncytial virus-associated hospitalisations and emergency department encounters among adults aged at least 60 years.

A Case Demonstration of the Open Health Natural Language Processing Toolkit From the National COVID-19 Cohort Collaborative and the Researching COVID to Enhance Recovery Programs for a Natural Language Processing System for COVID-19 or Postacute Sequelae of SARS CoV-2 Infection: Algorithm Development and Validation.

Background: A wealth of clinically relevant information is only obtainable within unstructured clinical narratives, leading to great interest in clinical natural language processing (NLP). While a multitude of approaches to NLP exist, current algorithm development approaches have limitations that can slow the development process. These limitations are exacerbated when the task is emergent, as is the case currently for NLP extraction of signs and symptoms of COVID-19 and postacute sequelae of SARS-CoV-2 infection (PASC).

A framework for sharing of clinical and genetic data for precision medicine applications.

Precision medicine has the potential to provide more accurate diagnosis, appropriate treatment and timely prevention strategies by considering patients' biological makeup. However, this cannot be realized without integrating clinical and omics data in a data-sharing framework that achieves large sample sizes. Systems that integrate clinical and genetic data from multiple sources are scarce due to their distinct data types, interoperability, security and data ownership issues.

The Gender Spectrum of In-hospital Survival Post Primary Percutaneous Coronary Intervention for ST Elevation Myocardial Infarction: Exploring Age-driven Trends.

Background: The study was aimed to evaluate gender difference and age & gender specific interaction of in-hospital outcomes of patients with ST elevation myocardial infarction (STEMI) undergoing primary percutaneous coronary intervention (PCI).

Methods: This was a prospective cohort study of 1748 patients with STEMI undergoing primary PCI. The study was dichotomised according to gender to evaluate the difference in the outcome.

Development and Validation of an Individual Socioeconomic Deprivation Index (ISDI) in the NIH's Data Network.

Many of the existing composite social determinant of health indices, such as Area Deprivation Index, are constrained by their reliance on geographic approximations and American Community Survey data. This study builds on the body of literature around deprivation indices to construct an individual socioeconomic deprivation index (ISDI) within the NIH's All of Us Data Network by using weighted multiple correspondence analysis on SDOH data elements collected at the participant level. In this study, the correlation between ISDI and another area-approximated index is assessed to the extent possible, along with the changes in an AI models performance due to stratified sampling based on ISDI quintiles.

Identifying erroneous height and weight values from adult electronic health records in the All of Us research program.

Introduction: Electronic Health Records (EHR) are a useful data source for research, but their usability is hindered by measurement errors. This study investigated an automatic error detection algorithm for adult height and weight measurements in EHR for the All of Us Research Program (All of Us).

Methods: We developed reference charts for adult heights and weights that were stratified on participant sex.

Patterns of red blood cell utilization: Harnessing electronic health records data from the Information Standard for Blood and Transplant (ISBT) 128 system within the Biologics Effectiveness and Safety (BEST) initiative.

Background: Current hemovigilance methods generally rely on survey data or administrative claims data utilizing billing and revenue codes, each of which has limitations. We used electronic health records (EHR) linked to blood bank data to comprehensively characterize red blood cell (RBC) utilization patterns and trends in three healthcare systems participating in the U.S.

Risk of COVID-19 Hospitalization and Protection Associated With mRNA Vaccination Among US Adults With Psychiatric Disorders.

Background: Although psychiatric disorders have been associated with reduced immune responses to other vaccines, it remains unknown whether they influence COVID-19 vaccine effectiveness (VE). This study evaluated risk of COVID-19 hospitalization and estimated mRNA VE stratified by psychiatric disorder status.

Methods: In a retrospective cohort analysis of the VISION Network in four US states, the rate of laboratory-confirmed COVID-19-associated hospitalization between December 2021 and August 2022 was compared across psychiatric diagnoses and by monovalent mRNA COVID-19 vaccination status using Cox proportional hazards regression.

Use of export thrombus aspiration catheter as a dual lumen catheter for antegrade LAD CTO wiring with side branch.

A 50-year-old female patient presented with class III angina for 6 months, positive stress test, and a prior CT angiogram suggestive of 3-vessel disease.

Auditing Learned Associations in Deep Learning Approaches to Extract Race and Ethnicity from Clinical Text.

Complete and accurate race and ethnicity (RE) patient information is important for many areas of biomedical informatics research, such as defining and characterizing cohorts, performing quality assessments, and identifying health inequities. Patient-level RE data is often inaccurate or missing in structured sources, but can be supplemented through clinical notes and natural language processing (NLP). While NLP has made many improvements in recent years with large language models, bias remains an often-unaddressed concern, with research showing that harmful and negative language is more often used for certain racial/ethnic groups than others.

Large-scale characterization of gender differences in diagnosis prevalence and time to diagnosis.

We carry out an analysis of gender differences in patterns of disease diagnosis across four large observational health datasets and find that women are routinely older when first assigned most diagnoses. Among 112 acute and chronic diseases, women experience longer lengths of time between symptom onset and disease diagnosis than men for most diseases regardless of metric used, even when only symptoms common to both genders are considered. These findings are consistent for patients with private as well as government insurance.

Clinical Epidemiology and Risk Factors for Critical Outcomes Among Vaccinated and Unvaccinated Adults Hospitalized With COVID-19-VISION Network, 10 States, June 2021-March 2023.

Background: The epidemiology of coronavirus disease 2019 (COVID-19) continues to develop with emerging variants, expanding population-level immunity, and advances in clinical care. We describe changes in the clinical epidemiology of COVID-19 hospitalizations and risk factors for critical outcomes over time.

Methods: We included adults aged ≥18 years from 10 states hospitalized with COVID-19 June 2021-March 2023.

The Data and Research Center: Creating a Secure, Scalable, and Sustainable Ecosystem for Biomedical Research.

The Research Program's Data and Research Center (DRC) was established to help acquire, curate, and provide access to one of the world's largest and most diverse datasets for precision medicine research. Already, over 500,000 participants are enrolled in , 80% of whom are underrepresented in biomedical research, and data are being analyzed by a community of over 2,300 researchers. The DRC created this thriving data ecosystem by collaborating with engaged participants, innovative program partners, and empowered researchers.