Real-World Prevalence of Type 2 Diabetes Remission in a U.S. Insured Population Using a Large Administrative Claims Database.

Objective: A 2021 international consensus statement defined type 2 diabetes remission as A1C <6.5% measured at least 3 months after cessation of glucose-lowering therapy. We aimed to investigate whether retrospective claims-based data can assess remission based on this definition, whether three increasingly strict alternative definitions affect the prevalence of remission and characteristics of remission cohorts, and how cohorts with and without sufficient data to assess for remission differ.

Real-world utilization of SARS-CoV-2 serological testing in RNA positive patients across the United States.

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.

Real-world performance of SARS-Cov-2 serology tests in the United States, 2020.

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.

Patterns of Prenatal Care Delivery and Obstetric Outcomes before and during the COVID-19 Pandemic.

Objective: Health care providers and health systems confronted new challenges to deliver timely, high-quality prenatal care during the coronavirus disease 2019 (COVID-19) pandemic as the pandemic raised concerns that care would be delayed or substantively changed. This study describes trends in prenatal care delivery in 2020 compared with 2018 to 2019 in a large, commercially insured population and investigates changes in obstetric care processes and outcomes.

Study Design: This retrospective cohort study uses de-identified administrative claims for commercially insured patients.

SARS-CoV-2 Sequelae and Postdischarge Health Care Visits Over 5 Months Follow-up Among Children Hospitalized for COVID-19 or MIS-C.

Although post-acute sequelae of COVID-19 among adult survivors has gained significant attention, data in children hospitalized for severe acute respiratory syndrome coronavirus 2 is limited. This study of commercially insured US children shows that those hospitalized with COVID-19 or multisystem inflammatory syndrome in children have a substantial burden of severe acute respiratory syndrome coronavirus 2 sequelae and associated health care visits postdischarge.

Benchmarking AutoML frameworks for disease prediction using medical claims.

Objectives: Ascertain and compare the performances of Automated Machine Learning (AutoML) tools on large, highly imbalanced healthcare datasets.

Materials And Methods: We generated a large dataset using historical de-identified administrative claims including demographic information and flags for disease codes in four different time windows prior to 2019. We then trained three AutoML tools on this dataset to predict six different disease outcomes in 2019 and evaluated model performances on several metrics.

Distributed learning for heterogeneous clinical data with application to integrating COVID-19 data across 230 sites.

Integrating real-world data (RWD) from several clinical sites offers great opportunities to improve estimation with a more general population compared to analyses based on a single clinical site. However, sharing patient-level data across sites is practically challenging due to concerns about maintaining patient privacy. We develop a distributed algorithm to integrate heterogeneous RWD from multiple clinical sites without sharing patient-level data.

Medication Fill Patterns for Cognitive and Behavioral or Psychological Symptoms of Alzheimer Disease and Related Dementias.

This cohort study investigates prescription drug fill patterns for cognitive and behavioral symptoms among patients with Alzheimer disease and related dementias.

Distributed Quasi-Poisson regression algorithm for modeling multi-site count outcomes in distributed data networks.

Background: Observational studies incorporating real-world data from multiple institutions facilitate study of rare outcomes or exposures and improve generalizability of results. Due to privacy concerns surrounding patient-level data sharing across institutions, methods for performing regression analyses distributively are desirable. Meta-analysis of institution-specific estimates is commonly used, but has been shown to produce biased estimates in certain settings.

Comparative effectiveness over time of the mRNA-1273 (Moderna) vaccine and the BNT162b2 (Pfizer-BioNTech) vaccine.

Real-world analysis of the incidence of SARS-CoV-2 infection post vaccination is important in determining the comparative effectiveness of the available vaccines. In this retrospective cohort study using deidentified administrative claims for Medicare Advantage and commercially insured individuals in a research database we examine over 3.5 million fully vaccinated individuals, including 8,848 individuals with SARS-CoV-2 infection, with a follow-up period between 14 and 151 days after their second dose.

Describing the Health Status of Women Experiencing Violence or Abuse: An Observational Study Using Claims Data.

Introduction: Violence against women (VAW) can result in long-term and varied sequela for survivors, making it difficult to evaluate healthcare intervention. This study seeks to improve understanding of the healthcare experiences of women survivors prior to a violence-related diagnosis, allowing healthcare systems to better design strategies to meet the needs of this population.

Methods: Using population-based data from 2016 to 2019, this cross-sectional observational study presents healthcare spending, utilization, and diagnostic patterns of privately insured women, age 18 or older, in the 10-months prior to an episode of care for a documented experience of violence (DEV).

Trends in US Patients Receiving Care for Eating Disorders and Other Common Behavioral Health Conditions Before and During the COVID-19 Pandemic.

This cohort study examines trends in care for eating disorders and other behavioral health conditions before and during the COVID-19 pandemic among commercially insured individuals in the US.

Pooling in a Pod: A Strategy for COVID-19 Testing to Facilitate a Safe Return to School.

The COVID-19 pandemic prompted widespread closures of primary and secondary schools. Routine testing of asymptomatic students and staff members, as part of a comprehensive mitigation program, can help schools open safely. "Pooling in a pod" is a public health surveillance strategy whereby testing cohorts (pods) are based on social relationships and physical proximity.

Patient and Hospital Factors Associated With Differences in Mortality Rates Among Black and White US Medicare Beneficiaries Hospitalized With COVID-19 Infection.

Importance: Black patients hospitalized with COVID-19 may have worse outcomes than White patients because of excess individual risk or because Black patients are disproportionately cared for in hospitals with worse outcomes for all.

Objectives: To examine differences in COVID-19 hospital mortality rates between Black and White patients and to assess whether the mortality rates reflect differences in patient characteristics by race or by the hospitals to which Black and White patients are admitted.

Design, Setting, And Participants: This cohort study assessed Medicare beneficiaries admitted with a diagnosis of COVID-19 to 1188 US hospitals from January 1, 2020, through September 21, 2020.

Identifying optimal COVID-19 testing strategies for schools and businesses: Balancing testing frequency, individual test technology, and cost.

Background: COVID-19 test sensitivity and specificity have been widely examined and discussed, yet optimal use of these tests will depend on the goals of testing, the population or setting, and the anticipated underlying disease prevalence. We model various combinations of key variables to identify and compare a range of effective and practical surveillance strategies for schools and businesses.

Methods: We coupled a simulated data set incorporating actual community prevalence and test performance characteristics to a susceptible, infectious, removed (SIR) compartmental model, modeling the impact of base and tunable variables including test sensitivity, testing frequency, results lag, sample pooling, disease prevalence, externally-acquired infections, symptom checking, and test cost on outcomes including case reduction and false positives.

Variation in US Hospital Mortality Rates for Patients Admitted With COVID-19 During the First 6 Months of the Pandemic.

Importance: It is unknown how much the mortality of patients with coronavirus disease 2019 (COVID-19) depends on the hospital that cares for them, and whether COVID-19 hospital mortality rates are improving.

Objective: To identify variation in COVID-19 mortality rates and how those rates have changed over the first months of the pandemic.

Design, Setting, And Participants: This cohort study assessed 38 517 adults who were admitted with COVID-19 to 955 US hospitals from January 1, 2020, to June 30, 2020, and a subset of 27 801 adults (72.

Non-steady-state heat conduction in composite walls.

The problem of heat conduction in one-dimensional piecewise homogeneous composite materials is examined by providing an explicit solution of the one-dimensional heat equation in each domain. The location of the interfaces is known, but neither temperature nor heat flux is prescribed there. Instead, the physical assumptions of their continuity at the interfaces are the only conditions imposed.

Entrainment ranges of forced phase oscillators.

In the vertebrate spinal cord, a neural circuit called the central pattern generator produces the basic locomotory rhythm. Short and long distance intersegmental connections serve to maintain coordination along the length of the body. As a way of examining the influence of such connections, we consider a model of a chain of coupled phase oscillators in which one oscillator receives a periodic forcing stimulus.