Publications by authors named "Philip Silberman"

Purpose: Broad-based molecular testing with next-generation sequencing (NGS) is now the standard of care in advanced non-small cell lung cancer (NSCLC). Two approaches to molecular testing are (1) reflexive testing at pathologic NSCLC confirmation, often using an in-house molecular panel, and (2) send-out testing to private vendors, ordered by a clinician. This study explored the outcomes with reflex versus send-out testing.

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Quality Improvement Success Stories are published by the American Diabetes Association in collaboration with the American College of Physicians and the National Diabetes Education Program. This series is intended to highlight best practices and strategies from programs and clinics that have successfully improved the quality of care for people with diabetes or related conditions. Each article in the series is reviewed and follows a standard format developed by the editors of .

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The 2018 American College of Cardiology/American Heart Association cholesterol guidelines for secondary prevention identified a group of "very high risk" (VHR) patients, those with multiple major atherosclerotic cardiovascular disease (ASCVD) events or 1 major ASCVD event with multiple high-risk features. A second group, "high risk" (HR), was defined as patients without any of the risk features in the VHR group. The incidence and relative risk differences of these 2 groups in a nontrial population has not been well characterized.

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Background: Oral anticoagulant (OAC) therapy is proven to be effective at reducing risk of stroke in patients with atrial fibrillation (AF). However, racial minorities with AF are less likely to be prescribed vitamin K anticoagulants (VKA). There is little information on the racial disparity in the prescription of the non-vitamin K oral anticoagulants (NOACs) and the associated risks of stroke and bleeding.

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Purpose: Bladder cancer is initially diagnosed and staged with a transurethral resection of bladder tumor (TURBT). Patient survival is dependent on appropriate sampling of layers of the bladder, but pathology reports are dictated as free text, making large-scale data extraction for quality improvement challenging. We sought to automate extraction of stage, grade, and quality information from TURBT pathology reports using natural language processing (NLP).

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