Using Artificial Intelligence With Natural Language Processing to Combine Electronic Health Record's Structured and Free Text Data to Identify Nonvalvular Atrial Fibrillation to Decrease Strokes and Death: Evaluation and Case-Control Study.

Background: Nonvalvular atrial fibrillation (NVAF) affects almost 6 million Americans and is a major contributor to stroke but is significantly undiagnosed and undertreated despite explicit guidelines for oral anticoagulation.

Objective: The aim of this study is to investigate whether the use of semisupervised natural language processing (NLP) of electronic health record's (EHR) free-text information combined with structured EHR data improves NVAF discovery and treatment and perhaps offers a method to prevent thousands of deaths and save billions of dollars.

Methods: We abstracted 96,681 participants from the University of Buffalo faculty practice's EHR.

Longitudinal K-means approaches to clustering and analyzing EHR opioid use trajectories for clinical subtypes.

Identification of patient subtypes from retrospective Electronic Health Record (EHR) data is fraught with inherent modeling issues, such as missing data and variable length time intervals, and the results obtained are highly dependent on data pre-processing strategies. As we move towards personalized medicine, assessing accurate patient subtypes will be a key factor in creating patient specific treatment plans. Partitioning longitudinal trajectories from irregularly spaced and variable length time intervals is a well-established, but open problem.

COVID-19: Incidental Diagnosis by 18F-FDG PET/CT.

A 73-year-old man with chronic obstructive pulmonary disease and no known malignancies was evaluated for back pain. MR examination showed lumbar spine compression fractures, and an F-FDG PET/CT scan was requested to assess for skeletal metastatic disease and potential detection of a primary neoplasm. The PET/CT examination revealed scattered FDG-avid pulmonary opacities with upper lobe preponderance highly suspicious for COVID-19.

Clinical Data Warehouse Query and Learning Tool Using a Human-Centered Participatory Design Process.

BMI Investigator (BMII) is an interactive web-based tool with a learning knowledge base, which provides a way for researchers to query structured, unstructured, genomic and image data contained in a data warehouse. We demonstrate how development of an efficient, usable, and learnable web interface for a diverse group of research stakeholders benefits from an iterative human-centered participatory design process utilizing a team of clinicians, students, programmers, and informatics experts.

Prescription Opioid Dependence in Western New York: Using Data Analytics to Find an Answer to the Opioid Epidemic.

Opioid dependence and overdose is on the rise. One indicator is the increasing trends of prescription buprenorphine use among patient on chronic pain medication. In addition to the New York State Department of Health's prescription drug monitoring programs and training programs for providers and first responders to detect and treat a narcotic overdose, further examination of the population may provide important information for multidisciplinary interventions to address this epidemic.

Safe Opioid Prescription: A SMART on FHIR Approach to Clinical Decision Support.

Background Prescription opioid pain medication overuse, misuse and abuse have been a significant contributing factor in the opioid epidemic. The rising death rates from opioid overdose have caused healthcare practitioners and researchers to work on optimizing pain therapy and limiting the prescriptions for pain medications. The state of New York has implemented a prescription drug monitoring program(PDMP), amended public health law to limit the prescription of opioids for acute pain and utilized the resources of the state and county health departments to help in curbing this epidemic.

Secondary Use of EHR: Interpreting Clinician Inter-Rater Reliability Through Qualitative Assessment.

In a retrospective secondary-use EHR study identifying a cohort of Non-Valvular Atrial Fibrillation (NVAF) patients, chart abstraction was done by two sets of clinicians to create a gold standard for risk measures CHA2DS2-VASc and HAS-BLED. Inter-rater reliability between each set of clinicians for NVAF and the outcomes of interest were variable, ranging from extremely low agreement to high agreement. To assess the chart abstraction process, a focus group and a survey was conducted.

Comparison of iodixanol with iohexol for delayed pelvic venous opacification: a preliminary study of potential use for CT venography.

Objective: The goal of this prospective randomized study was to determine whether isosmolar contrast material offers an advantage over low-osmolar contrast material for delayed venous opacification in CT venography. SUBJECTS AND METHODS. We prospectively enrolled 200 adult outpatients.