Seth A. Berkowitz

Bio: Seth A. Berkowitz is an academic researcher from University of North Carolina at Chapel Hill. The author has contributed to research in topics: Medicine & Health care. The author has an hindex of 33, co-authored 126 publications receiving 3273 citations. Previous affiliations of Seth A. Berkowitz include Brigham and Women's Hospital & Johns Hopkins University.

MIMIC-CXR, a de-identified publicly available database of chest radiographs with free-text reports

Abstract: Chest radiography is an extremely powerful imaging modality, allowing for a detailed inspection of a patient's chest, but requires specialized training for proper interpretation. With the advent of high performance general purpose computer vision algorithms, the accurate automated analysis of chest radiographs is becoming increasingly of interest to researchers. Here we describe MIMIC-CXR, a large dataset of 227,835 imaging studies for 65,379 patients presenting to the Beth Israel Deaconess Medical Center Emergency Department between 2011-2016. Each imaging study can contain one or more images, usually a frontal view and a lateral view. A total of 377,110 images are available in the dataset. Studies are made available with a semi-structured free-text radiology report that describes the radiological findings of the images, written by a practicing radiologist contemporaneously during routine clinical care. All images and reports have been de-identified to protect patient privacy. The dataset is made freely available to facilitate and encourage a wide range of research in computer vision, natural language processing, and clinical data mining.

Social Determinants of Health and Diabetes: A Scientific Review.

Abstract: Decades of research have demonstrated that diabetes affects racial and ethnic minority and low-income adult populations in the U.S. disproportionately, with relatively intractable patterns seen in these populations’ higher risk of diabetes and rates of diabetes complications and mortality (1). With a health care shift toward greater emphasis on population health outcomes and value-based care, social determinants of health (SDOH) have risen to the forefront as essential intervention targets to achieve health equity (2–4). Most recently, the COVID-19 pandemic has highlighted unequal vulnerabilities borne by racial and ethnic minority groups and by disadvantaged communities. In the wake of concurrent pandemic and racial injustice events in the U.S., the American College of Physicians, American Academy of Pediatrics, Society of General Internal Medicine, National Academy of Medicine, and other professional organizations have published statements on SDOH (5–8), and calls to action focus on amelioration of these determinants at individual, organizational, and policy levels (9–11). In diabetes, understanding and mitigating the impact of SDOH are priorities due to disease prevalence, economic costs, and disproportionate population burden (12–14). In 2013, the American Diabetes Association (ADA) published a scientific statement on socioecological determinants of prediabetes and type 2 diabetes (15). Toward the goal ofunderstanding and advancing opportunities for health improvement among the population with diabetes through addressing SDOH, ADA convened the current SDOH and diabetes writing committee, prepandemic, to review the literature on 1 ) associations of SDOH with diabetes risk and outcomes and 2 ) impact of interventions targeting amelioration of SDOH on diabetes outcomes. This article begins with an overview of key definitions and SDOH frameworks. The literature review focuses primarily on U.S.-based studies of adults with diabetes and on five SDOH: socioeconomic status (education, income, occupation); neighborhood and physical environment (housing, built environment, toxic environmental …

MIMIC-CXR: A large publicly available database of labeled chest radiographs

Abstract: Chest radiography is an extremely powerful imaging modality, allowing for a detailed inspection of a patient's thorax, but requiring specialized training for proper interpretation. With the advent of high performance general purpose computer vision algorithms, the accurate automated analysis of chest radiographs is becoming increasingly of interest to researchers. However, a key challenge in the development of these techniques is the lack of sufficient data. Here we describe MIMIC-CXR-JPG v2.0.0, a large dataset of 377,110 chest x-rays associated with 227,827 imaging studies sourced from the Beth Israel Deaconess Medical Center between 2011 - 2016. Images are provided with 14 labels derived from two natural language processing tools applied to the corresponding free-text radiology reports. MIMIC-CXR-JPG is derived entirely from the MIMIC-CXR database, and aims to provide a convenient processed version of MIMIC-CXR, as well as to provide a standard reference for data splits and image labels. All images have been de-identified to protect patient privacy. The dataset is made freely available to facilitate and encourage a wide range of research in medical computer vision.

Association of Primary Care Physician Supply With Population Mortality in the United States, 2005-2015.

Abstract: Importance Recent US health care reforms incentivize improved population health outcomes and primary care functions. It remains unclear how much improving primary care physician supply can improve population health, independent of other health care and socioeconomic factors. Objectives To identify primary care physician supply changes across US counties from 2005-2015 and associations between such changes and population mortality. Design, Setting, and Participants This epidemiological study evaluated US population data and individual-level claims data linked to mortality from 2005 to 2015 against changes in primary care and specialist physician supply from 2005 to 2015. Data from 3142 US counties, 7144 primary care service areas, and 306 hospital referral regions were used to investigate the association of primary care physician supply with changes in life expectancy and cause-specific mortality after adjustment for health care, demographic, socioeconomic, and behavioral covariates. Analysis was performed from March to July 2018. Main Outcomes and Measures Age-standardized life expectancy, cause-specific mortality, and restricted mean survival time. Results Primary care physician supply increased from 196 014 physicians in 2005 to 204 419 in 2015. Owing to disproportionate losses of primary care physicians in some counties and population increases, the mean (SD) density of primary care physicians relative to population size decreased from 46.6 per 100 000 population (95% CI, 0.0-114.6 per 100 000 population) to 41.4 per 100 000 population (95% CI, 0.0-108.6 per 100 000 population), with greater losses in rural areas. In adjusted mixed-effects regressions, every 10 additional primary care physicians per 100 000 population was associated with a 51.5-day increase in life expectancy (95% CI, 29.5-73.5 days; 0.2% increase), whereas an increase in 10 specialist physicians per 100 000 population corresponded to a 19.2-day increase (95% CI, 7.0-31.3 days). A total of 10 additional primary care physicians per 100 000 population was associated with reduced cardiovascular, cancer, and respiratory mortality by 0.9% to 1.4%. Analyses at different geographic levels, using instrumental variable regressions, or at the individual level found similar benefits associated with primary care supply. Conclusions and Relevance Greater primary care physician supply was associated with lower mortality, but per capita supply decreased between 2005 and 2015. Programs to explicitly direct more resources to primary care physician supply may be important for population health.

Standards of Medical Care in Diabetes

Abstract: XI. STRATEGIES FOR IMPROVING DIABETES CARE D iabetes is a chronic illness that requires continuing medical care and patient self-management education to prevent acute complications and to reduce the risk of long-term complications. Diabetes care is complex and requires that many issues, beyond glycemic control, be addressed. A large body of evidence exists that supports a range of interventions to improve diabetes outcomes. These standards of care are intended to provide clinicians, patients, researchers, payors, and other interested individuals with the components of diabetes care, treatment goals, and tools to evaluate the quality of care. While individual preferences, comorbidities, and other patient factors may require modification of goals, targets that are desirable for most patients with diabetes are provided. These standards are not intended to preclude more extensive evaluation and management of the patient by other specialists as needed. For more detailed information, refer to Bode (Ed.): Medical Management of Type 1 Diabetes (1), Burant (Ed): Medical Management of Type 2 Diabetes (2), and Klingensmith (Ed): Intensive Diabetes Management (3). The recommendations included are diagnostic and therapeutic actions that are known or believed to favorably affect health outcomes of patients with diabetes. A grading system (Table 1), developed by the American Diabetes Association (ADA) and modeled after existing methods, was utilized to clarify and codify the evidence that forms the basis for the recommendations. The level of evidence that supports each recommendation is listed after each recommendation using the letters A, B, C, or E.

Classification and diagnosis of diabetes

Abstract: 1. Type 1 diabetes (due to b-cell destruction, usually leading to absolute insulin deficiency) 2. Type 2 diabetes (due to a progressive insulin secretory defect on the background of insulin resistance) 3. Gestational diabetes mellitus (GDM) (diabetes diagnosed in the second or third trimester of pregnancy that is not clearly overt diabetes) 4. Specific types of diabetes due to other causes, e.g., monogenic diabetes syndromes (such as neonatal diabetes and maturity-onset diabetes of the young [MODY]), diseases of the exocrine pancreas (such as cystic fibrosis), and drugor chemical-induced diabetes (such as in the treatment of HIV/AIDS or after organ transplantation)

Heart Disease and Stroke Statistics—2022 Update: A Report From the American Heart Association

Abstract: The American Heart Association, in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, diet, and weight) and health factors (cholesterol, blood pressure, and glucose control) that contribute to cardiovascular health. The Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, congenital heart disease, rhythm disorders, subclinical atherosclerosis, coronary heart disease, heart failure, valvular disease, venous disease, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs).The American Heart Association, through its Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States to provide the most current information available in the annual Statistical Update. The 2022 Statistical Update is the product of a full year's worth of effort by dedicated volunteer clinicians and scientists, committed government professionals, and American Heart Association staff members. This year's edition includes data on the monitoring and benefits of cardiovascular health in the population and an enhanced focus on social determinants of health, adverse pregnancy outcomes, vascular contributions to brain health, and the global burden of cardiovascular disease and healthy life expectancy.Each of the chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics.The Statistical Update represents a critical resource for the lay public, policymakers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.